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The Emerging Generative Artificial Intelligence Divide in the United States
Published 18 Apr 2024 in cs.AI and cs.CY | (2404.11988v3)
Abstract: The digital divide refers to disparities in access to and use of digital tooling across social and economic groups. This divide can reinforce marginalization both at the individual level and at the level of places, because persistent economic advantages accrue to places where new technologies are adopted early. To what extent are emerging generative AI tools subject to these social and spatial divides? We leverage a large-scale search query database to characterize U.S. residents' knowledge of a novel generative AI tool, ChatGPT, during its first six months of release. We identify hotspots of higher-than-expected search volumes for ChatGPT in coastal metropolitan areas, while coldspots are evident in the American South, Appalachia, and the Midwest. Nationwide, counties with the highest rates of search have proportionally more educated and more economically advantaged populations, as well as proportionally more technology and finance-sector jobs in comparison with other counties or with the national average. Observed associations with race/ethnicity and urbanicity are attenuated in fully adjusted hierarchical models, but education emerges as the strongest positive predictor of generative AI awareness. In the absence of intervention, early differences in uptake show a potential to reinforce existing spatial and socioeconomic divides.
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[2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lipsey, R.G., Carlaw, K.I., Bekar, C.T.: Economic Transformations: General Purpose Technologies and Long-term Economic Growth. Oxford University Press, Oxford, UK (2005) Van Dijk [2006] Van Dijk, J.A.: Digital divide research, achievements and shortcomings. Poetics 34(4-5), 221–235 (2006) DiMaggio et al. [2004] DiMaggio, P., Hargittai, E., Celeste, C., Shafer, S.: Digital inequality: From unequal access to differentiated use. Social inequality, 355–400 (2004) Hargittai [2002] Hargittai, E.: Second-level digital divide: Mapping differences in people’s online skills. First Monday 7(4) (2002). https://doi.org/10.5210/fm.v7i4.942 Van Deursen and Helsper [2015] Van Deursen, A.J., Helsper, E.J.: The third-level digital divide: Who benefits most from being online? vol. 10, pp. 29–52 (2015). https://doi.org/10.1108/S2050-206020150000010002 McCarthy et al. [2006] McCarthy, J., Minsky, M.L., Rochester, N., Shannon, C.E.: A proposal for the dartmouth summer research project on artificial intelligence, august 31, 1955. AI magazine 27(4), 12–12 (2006) Russell [2010] Russell, S.J.: Artificial Intelligence: A Modern Approach. Pearson Education, Inc., Hoboken, New Jersey (2010) Bubeck et al. [2023] Bubeck, S., Chandrasekaran, V., Eldan, R., Gehrke, J., Horvitz, E., Kamar, E., Lee, P., Lee, Y.T., Li, Y., Lundberg, S., et al.: Sparks of artificial general intelligence: Early experiments with gpt-4. arXiv:2303.12712 (2023) Solaiman et al. [2023] Solaiman, I., Talat, Z., Agnew, W., Ahmad, L., Baker, D., Blodgett, S.L., Daumé III, H., Dodge, J., Evans, E., Hooker, S., et al.: Evaluating the social impact of generative ai systems in systems and society. arXiv:2306.05949 (2023) Devlin et al. [2019] Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Dijk, J.A.: Digital divide research, achievements and shortcomings. Poetics 34(4-5), 221–235 (2006) DiMaggio et al. [2004] DiMaggio, P., Hargittai, E., Celeste, C., Shafer, S.: Digital inequality: From unequal access to differentiated use. Social inequality, 355–400 (2004) Hargittai [2002] Hargittai, E.: Second-level digital divide: Mapping differences in people’s online skills. First Monday 7(4) (2002). https://doi.org/10.5210/fm.v7i4.942 Van Deursen and Helsper [2015] Van Deursen, A.J., Helsper, E.J.: The third-level digital divide: Who benefits most from being online? vol. 10, pp. 29–52 (2015). https://doi.org/10.1108/S2050-206020150000010002 McCarthy et al. [2006] McCarthy, J., Minsky, M.L., Rochester, N., Shannon, C.E.: A proposal for the dartmouth summer research project on artificial intelligence, august 31, 1955. AI magazine 27(4), 12–12 (2006) Russell [2010] Russell, S.J.: Artificial Intelligence: A Modern Approach. Pearson Education, Inc., Hoboken, New Jersey (2010) Bubeck et al. [2023] Bubeck, S., Chandrasekaran, V., Eldan, R., Gehrke, J., Horvitz, E., Kamar, E., Lee, P., Lee, Y.T., Li, Y., Lundberg, S., et al.: Sparks of artificial general intelligence: Early experiments with gpt-4. arXiv:2303.12712 (2023) Solaiman et al. [2023] Solaiman, I., Talat, Z., Agnew, W., Ahmad, L., Baker, D., Blodgett, S.L., Daumé III, H., Dodge, J., Evans, E., Hooker, S., et al.: Evaluating the social impact of generative ai systems in systems and society. arXiv:2306.05949 (2023) Devlin et al. [2019] Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. 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[2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). 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Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Deursen, A.J., Helsper, E.J.: The third-level digital divide: Who benefits most from being online? vol. 10, pp. 29–52 (2015). https://doi.org/10.1108/S2050-206020150000010002 McCarthy et al. [2006] McCarthy, J., Minsky, M.L., Rochester, N., Shannon, C.E.: A proposal for the dartmouth summer research project on artificial intelligence, august 31, 1955. AI magazine 27(4), 12–12 (2006) Russell [2010] Russell, S.J.: Artificial Intelligence: A Modern Approach. Pearson Education, Inc., Hoboken, New Jersey (2010) Bubeck et al. [2023] Bubeck, S., Chandrasekaran, V., Eldan, R., Gehrke, J., Horvitz, E., Kamar, E., Lee, P., Lee, Y.T., Li, Y., Lundberg, S., et al.: Sparks of artificial general intelligence: Early experiments with gpt-4. arXiv:2303.12712 (2023) Solaiman et al. [2023] Solaiman, I., Talat, Z., Agnew, W., Ahmad, L., Baker, D., Blodgett, S.L., Daumé III, H., Dodge, J., Evans, E., Hooker, S., et al.: Evaluating the social impact of generative ai systems in systems and society. arXiv:2306.05949 (2023) Devlin et al. [2019] Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) McCarthy, J., Minsky, M.L., Rochester, N., Shannon, C.E.: A proposal for the dartmouth summer research project on artificial intelligence, august 31, 1955. AI magazine 27(4), 12–12 (2006) Russell [2010] Russell, S.J.: Artificial Intelligence: A Modern Approach. Pearson Education, Inc., Hoboken, New Jersey (2010) Bubeck et al. [2023] Bubeck, S., Chandrasekaran, V., Eldan, R., Gehrke, J., Horvitz, E., Kamar, E., Lee, P., Lee, Y.T., Li, Y., Lundberg, S., et al.: Sparks of artificial general intelligence: Early experiments with gpt-4. arXiv:2303.12712 (2023) Solaiman et al. [2023] Solaiman, I., Talat, Z., Agnew, W., Ahmad, L., Baker, D., Blodgett, S.L., Daumé III, H., Dodge, J., Evans, E., Hooker, S., et al.: Evaluating the social impact of generative ai systems in systems and society. arXiv:2306.05949 (2023) Devlin et al. [2019] Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Russell, S.J.: Artificial Intelligence: A Modern Approach. Pearson Education, Inc., Hoboken, New Jersey (2010) Bubeck et al. [2023] Bubeck, S., Chandrasekaran, V., Eldan, R., Gehrke, J., Horvitz, E., Kamar, E., Lee, P., Lee, Y.T., Li, Y., Lundberg, S., et al.: Sparks of artificial general intelligence: Early experiments with gpt-4. arXiv:2303.12712 (2023) Solaiman et al. [2023] Solaiman, I., Talat, Z., Agnew, W., Ahmad, L., Baker, D., Blodgett, S.L., Daumé III, H., Dodge, J., Evans, E., Hooker, S., et al.: Evaluating the social impact of generative ai systems in systems and society. arXiv:2306.05949 (2023) Devlin et al. [2019] Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. 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Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Bubeck, S., Chandrasekaran, V., Eldan, R., Gehrke, J., Horvitz, E., Kamar, E., Lee, P., Lee, Y.T., Li, Y., Lundberg, S., et al.: Sparks of artificial general intelligence: Early experiments with gpt-4. arXiv:2303.12712 (2023) Solaiman et al. [2023] Solaiman, I., Talat, Z., Agnew, W., Ahmad, L., Baker, D., Blodgett, S.L., Daumé III, H., Dodge, J., Evans, E., Hooker, S., et al.: Evaluating the social impact of generative ai systems in systems and society. arXiv:2306.05949 (2023) Devlin et al. [2019] Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Solaiman, I., Talat, Z., Agnew, W., Ahmad, L., Baker, D., Blodgett, S.L., Daumé III, H., Dodge, J., Evans, E., Hooker, S., et al.: Evaluating the social impact of generative ai systems in systems and society. arXiv:2306.05949 (2023) Devlin et al. [2019] Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). 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In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. 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Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. 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Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. 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[2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. 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[2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. 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Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. 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Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. 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Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. 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LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) McCarthy, J., Minsky, M.L., Rochester, N., Shannon, C.E.: A proposal for the dartmouth summer research project on artificial intelligence, august 31, 1955. AI magazine 27(4), 12–12 (2006) Russell [2010] Russell, S.J.: Artificial Intelligence: A Modern Approach. Pearson Education, Inc., Hoboken, New Jersey (2010) Bubeck et al. [2023] Bubeck, S., Chandrasekaran, V., Eldan, R., Gehrke, J., Horvitz, E., Kamar, E., Lee, P., Lee, Y.T., Li, Y., Lundberg, S., et al.: Sparks of artificial general intelligence: Early experiments with gpt-4. arXiv:2303.12712 (2023) Solaiman et al. [2023] Solaiman, I., Talat, Z., Agnew, W., Ahmad, L., Baker, D., Blodgett, S.L., Daumé III, H., Dodge, J., Evans, E., Hooker, S., et al.: Evaluating the social impact of generative ai systems in systems and society. arXiv:2306.05949 (2023) Devlin et al. [2019] Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. 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[2023] Solaiman, I., Talat, Z., Agnew, W., Ahmad, L., Baker, D., Blodgett, S.L., Daumé III, H., Dodge, J., Evans, E., Hooker, S., et al.: Evaluating the social impact of generative ai systems in systems and society. arXiv:2306.05949 (2023) Devlin et al. [2019] Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. 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Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Bubeck, S., Chandrasekaran, V., Eldan, R., Gehrke, J., Horvitz, E., Kamar, E., Lee, P., Lee, Y.T., Li, Y., Lundberg, S., et al.: Sparks of artificial general intelligence: Early experiments with gpt-4. arXiv:2303.12712 (2023) Solaiman et al. [2023] Solaiman, I., Talat, Z., Agnew, W., Ahmad, L., Baker, D., Blodgett, S.L., Daumé III, H., Dodge, J., Evans, E., Hooker, S., et al.: Evaluating the social impact of generative ai systems in systems and society. arXiv:2306.05949 (2023) Devlin et al. [2019] Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Solaiman, I., Talat, Z., Agnew, W., Ahmad, L., Baker, D., Blodgett, S.L., Daumé III, H., Dodge, J., Evans, E., Hooker, S., et al.: Evaluating the social impact of generative ai systems in systems and society. arXiv:2306.05949 (2023) Devlin et al. [2019] Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. 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[2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. 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Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. 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Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. 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Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. 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[2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. 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[2023] Solaiman, I., Talat, Z., Agnew, W., Ahmad, L., Baker, D., Blodgett, S.L., Daumé III, H., Dodge, J., Evans, E., Hooker, S., et al.: Evaluating the social impact of generative ai systems in systems and society. arXiv:2306.05949 (2023) Devlin et al. [2019] Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. 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[2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. 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[2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hargittai, E.: Second-level digital divide: Mapping differences in people’s online skills. First Monday 7(4) (2002). https://doi.org/10.5210/fm.v7i4.942 Van Deursen and Helsper [2015] Van Deursen, A.J., Helsper, E.J.: The third-level digital divide: Who benefits most from being online? vol. 10, pp. 29–52 (2015). https://doi.org/10.1108/S2050-206020150000010002 McCarthy et al. [2006] McCarthy, J., Minsky, M.L., Rochester, N., Shannon, C.E.: A proposal for the dartmouth summer research project on artificial intelligence, august 31, 1955. AI magazine 27(4), 12–12 (2006) Russell [2010] Russell, S.J.: Artificial Intelligence: A Modern Approach. Pearson Education, Inc., Hoboken, New Jersey (2010) Bubeck et al. [2023] Bubeck, S., Chandrasekaran, V., Eldan, R., Gehrke, J., Horvitz, E., Kamar, E., Lee, P., Lee, Y.T., Li, Y., Lundberg, S., et al.: Sparks of artificial general intelligence: Early experiments with gpt-4. arXiv:2303.12712 (2023) Solaiman et al. [2023] Solaiman, I., Talat, Z., Agnew, W., Ahmad, L., Baker, D., Blodgett, S.L., Daumé III, H., Dodge, J., Evans, E., Hooker, S., et al.: Evaluating the social impact of generative ai systems in systems and society. arXiv:2306.05949 (2023) Devlin et al. [2019] Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Deursen, A.J., Helsper, E.J.: The third-level digital divide: Who benefits most from being online? vol. 10, pp. 29–52 (2015). https://doi.org/10.1108/S2050-206020150000010002 McCarthy et al. [2006] McCarthy, J., Minsky, M.L., Rochester, N., Shannon, C.E.: A proposal for the dartmouth summer research project on artificial intelligence, august 31, 1955. 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LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. 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[2023] Bubeck, S., Chandrasekaran, V., Eldan, R., Gehrke, J., Horvitz, E., Kamar, E., Lee, P., Lee, Y.T., Li, Y., Lundberg, S., et al.: Sparks of artificial general intelligence: Early experiments with gpt-4. arXiv:2303.12712 (2023) Solaiman et al. [2023] Solaiman, I., Talat, Z., Agnew, W., Ahmad, L., Baker, D., Blodgett, S.L., Daumé III, H., Dodge, J., Evans, E., Hooker, S., et al.: Evaluating the social impact of generative ai systems in systems and society. arXiv:2306.05949 (2023) Devlin et al. [2019] Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. 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Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Russell, S.J.: Artificial Intelligence: A Modern Approach. Pearson Education, Inc., Hoboken, New Jersey (2010) Bubeck et al. [2023] Bubeck, S., Chandrasekaran, V., Eldan, R., Gehrke, J., Horvitz, E., Kamar, E., Lee, P., Lee, Y.T., Li, Y., Lundberg, S., et al.: Sparks of artificial general intelligence: Early experiments with gpt-4. arXiv:2303.12712 (2023) Solaiman et al. [2023] Solaiman, I., Talat, Z., Agnew, W., Ahmad, L., Baker, D., Blodgett, S.L., Daumé III, H., Dodge, J., Evans, E., Hooker, S., et al.: Evaluating the social impact of generative ai systems in systems and society. arXiv:2306.05949 (2023) Devlin et al. [2019] Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. 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[2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. 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[2023] Solaiman, I., Talat, Z., Agnew, W., Ahmad, L., Baker, D., Blodgett, S.L., Daumé III, H., Dodge, J., Evans, E., Hooker, S., et al.: Evaluating the social impact of generative ai systems in systems and society. arXiv:2306.05949 (2023) Devlin et al. [2019] Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. 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Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Solaiman, I., Talat, Z., Agnew, W., Ahmad, L., Baker, D., Blodgett, S.L., Daumé III, H., Dodge, J., Evans, E., Hooker, S., et al.: Evaluating the social impact of generative ai systems in systems and society. arXiv:2306.05949 (2023) Devlin et al. [2019] Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. 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Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). 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In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. 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Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. 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Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. 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[2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. 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[2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. 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LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. 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[2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). 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In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) McCarthy, J., Minsky, M.L., Rochester, N., Shannon, C.E.: A proposal for the dartmouth summer research project on artificial intelligence, august 31, 1955. AI magazine 27(4), 12–12 (2006) Russell [2010] Russell, S.J.: Artificial Intelligence: A Modern Approach. Pearson Education, Inc., Hoboken, New Jersey (2010) Bubeck et al. [2023] Bubeck, S., Chandrasekaran, V., Eldan, R., Gehrke, J., Horvitz, E., Kamar, E., Lee, P., Lee, Y.T., Li, Y., Lundberg, S., et al.: Sparks of artificial general intelligence: Early experiments with gpt-4. arXiv:2303.12712 (2023) Solaiman et al. [2023] Solaiman, I., Talat, Z., Agnew, W., Ahmad, L., Baker, D., Blodgett, S.L., Daumé III, H., Dodge, J., Evans, E., Hooker, S., et al.: Evaluating the social impact of generative ai systems in systems and society. arXiv:2306.05949 (2023) Devlin et al. [2019] Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. 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[2023] Solaiman, I., Talat, Z., Agnew, W., Ahmad, L., Baker, D., Blodgett, S.L., Daumé III, H., Dodge, J., Evans, E., Hooker, S., et al.: Evaluating the social impact of generative ai systems in systems and society. arXiv:2306.05949 (2023) Devlin et al. [2019] Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. 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Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Bubeck, S., Chandrasekaran, V., Eldan, R., Gehrke, J., Horvitz, E., Kamar, E., Lee, P., Lee, Y.T., Li, Y., Lundberg, S., et al.: Sparks of artificial general intelligence: Early experiments with gpt-4. arXiv:2303.12712 (2023) Solaiman et al. [2023] Solaiman, I., Talat, Z., Agnew, W., Ahmad, L., Baker, D., Blodgett, S.L., Daumé III, H., Dodge, J., Evans, E., Hooker, S., et al.: Evaluating the social impact of generative ai systems in systems and society. arXiv:2306.05949 (2023) Devlin et al. [2019] Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Solaiman, I., Talat, Z., Agnew, W., Ahmad, L., Baker, D., Blodgett, S.L., Daumé III, H., Dodge, J., Evans, E., Hooker, S., et al.: Evaluating the social impact of generative ai systems in systems and society. arXiv:2306.05949 (2023) Devlin et al. [2019] Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). 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In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. 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Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. 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[2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. 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Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. 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[2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. 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Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). 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In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) McCarthy, J., Minsky, M.L., Rochester, N., Shannon, C.E.: A proposal for the dartmouth summer research project on artificial intelligence, august 31, 1955. AI magazine 27(4), 12–12 (2006) Russell [2010] Russell, S.J.: Artificial Intelligence: A Modern Approach. Pearson Education, Inc., Hoboken, New Jersey (2010) Bubeck et al. [2023] Bubeck, S., Chandrasekaran, V., Eldan, R., Gehrke, J., Horvitz, E., Kamar, E., Lee, P., Lee, Y.T., Li, Y., Lundberg, S., et al.: Sparks of artificial general intelligence: Early experiments with gpt-4. arXiv:2303.12712 (2023) Solaiman et al. [2023] Solaiman, I., Talat, Z., Agnew, W., Ahmad, L., Baker, D., Blodgett, S.L., Daumé III, H., Dodge, J., Evans, E., Hooker, S., et al.: Evaluating the social impact of generative ai systems in systems and society. arXiv:2306.05949 (2023) Devlin et al. [2019] Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Russell, S.J.: Artificial Intelligence: A Modern Approach. Pearson Education, Inc., Hoboken, New Jersey (2010) Bubeck et al. [2023] Bubeck, S., Chandrasekaran, V., Eldan, R., Gehrke, J., Horvitz, E., Kamar, E., Lee, P., Lee, Y.T., Li, Y., Lundberg, S., et al.: Sparks of artificial general intelligence: Early experiments with gpt-4. arXiv:2303.12712 (2023) Solaiman et al. [2023] Solaiman, I., Talat, Z., Agnew, W., Ahmad, L., Baker, D., Blodgett, S.L., Daumé III, H., Dodge, J., Evans, E., Hooker, S., et al.: Evaluating the social impact of generative ai systems in systems and society. arXiv:2306.05949 (2023) Devlin et al. [2019] Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. 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Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. 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[2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Bubeck, S., Chandrasekaran, V., Eldan, R., Gehrke, J., Horvitz, E., Kamar, E., Lee, P., Lee, Y.T., Li, Y., Lundberg, S., et al.: Sparks of artificial general intelligence: Early experiments with gpt-4. arXiv:2303.12712 (2023) Solaiman et al. [2023] Solaiman, I., Talat, Z., Agnew, W., Ahmad, L., Baker, D., Blodgett, S.L., Daumé III, H., Dodge, J., Evans, E., Hooker, S., et al.: Evaluating the social impact of generative ai systems in systems and society. arXiv:2306.05949 (2023) Devlin et al. [2019] Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Solaiman, I., Talat, Z., Agnew, W., Ahmad, L., Baker, D., Blodgett, S.L., Daumé III, H., Dodge, J., Evans, E., Hooker, S., et al.: Evaluating the social impact of generative ai systems in systems and society. arXiv:2306.05949 (2023) Devlin et al. [2019] Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. 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[2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. 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Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. 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Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. 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[2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. 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[2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. 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IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Russell, S.J.: Artificial Intelligence: A Modern Approach. Pearson Education, Inc., Hoboken, New Jersey (2010) Bubeck et al. [2023] Bubeck, S., Chandrasekaran, V., Eldan, R., Gehrke, J., Horvitz, E., Kamar, E., Lee, P., Lee, Y.T., Li, Y., Lundberg, S., et al.: Sparks of artificial general intelligence: Early experiments with gpt-4. arXiv:2303.12712 (2023) Solaiman et al. [2023] Solaiman, I., Talat, Z., Agnew, W., Ahmad, L., Baker, D., Blodgett, S.L., Daumé III, H., Dodge, J., Evans, E., Hooker, S., et al.: Evaluating the social impact of generative ai systems in systems and society. arXiv:2306.05949 (2023) Devlin et al. [2019] Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Bubeck, S., Chandrasekaran, V., Eldan, R., Gehrke, J., Horvitz, E., Kamar, E., Lee, P., Lee, Y.T., Li, Y., Lundberg, S., et al.: Sparks of artificial general intelligence: Early experiments with gpt-4. arXiv:2303.12712 (2023) Solaiman et al. [2023] Solaiman, I., Talat, Z., Agnew, W., Ahmad, L., Baker, D., Blodgett, S.L., Daumé III, H., Dodge, J., Evans, E., Hooker, S., et al.: Evaluating the social impact of generative ai systems in systems and society. arXiv:2306.05949 (2023) Devlin et al. [2019] Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Solaiman, I., Talat, Z., Agnew, W., Ahmad, L., Baker, D., Blodgett, S.L., Daumé III, H., Dodge, J., Evans, E., Hooker, S., et al.: Evaluating the social impact of generative ai systems in systems and society. arXiv:2306.05949 (2023) Devlin et al. [2019] Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. 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Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). 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In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. 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[2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). 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In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. 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[2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. 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[2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. 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Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. 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Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. 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[2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. 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[2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. 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[2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. 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In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Russell, S.J.: Artificial Intelligence: A Modern Approach. Pearson Education, Inc., Hoboken, New Jersey (2010) Bubeck et al. [2023] Bubeck, S., Chandrasekaran, V., Eldan, R., Gehrke, J., Horvitz, E., Kamar, E., Lee, P., Lee, Y.T., Li, Y., Lundberg, S., et al.: Sparks of artificial general intelligence: Early experiments with gpt-4. arXiv:2303.12712 (2023) Solaiman et al. [2023] Solaiman, I., Talat, Z., Agnew, W., Ahmad, L., Baker, D., Blodgett, S.L., Daumé III, H., Dodge, J., Evans, E., Hooker, S., et al.: Evaluating the social impact of generative ai systems in systems and society. arXiv:2306.05949 (2023) Devlin et al. [2019] Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Bubeck, S., Chandrasekaran, V., Eldan, R., Gehrke, J., Horvitz, E., Kamar, E., Lee, P., Lee, Y.T., Li, Y., Lundberg, S., et al.: Sparks of artificial general intelligence: Early experiments with gpt-4. arXiv:2303.12712 (2023) Solaiman et al. [2023] Solaiman, I., Talat, Z., Agnew, W., Ahmad, L., Baker, D., Blodgett, S.L., Daumé III, H., Dodge, J., Evans, E., Hooker, S., et al.: Evaluating the social impact of generative ai systems in systems and society. arXiv:2306.05949 (2023) Devlin et al. [2019] Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Solaiman, I., Talat, Z., Agnew, W., Ahmad, L., Baker, D., Blodgett, S.L., Daumé III, H., Dodge, J., Evans, E., Hooker, S., et al.: Evaluating the social impact of generative ai systems in systems and society. arXiv:2306.05949 (2023) Devlin et al. [2019] Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. 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[2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. 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Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. 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Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. 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Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. 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[2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. 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[2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Solaiman, I., Talat, Z., Agnew, W., Ahmad, L., Baker, D., Blodgett, S.L., Daumé III, H., Dodge, J., Evans, E., Hooker, S., et al.: Evaluating the social impact of generative ai systems in systems and society. arXiv:2306.05949 (2023) Devlin et al. [2019] Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. 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[2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). 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In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. 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[2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. Proceedings of NAACL-HLT (2019) OpenAI [2023] OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. 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[2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. 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Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. 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R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dorfman, N.S.: Route 128: the development of a regional high technology economy. 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Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. 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Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). 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In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. 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Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. 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[2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. 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R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. 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Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. 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[2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. 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Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. 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[2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. 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Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
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In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. 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[2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) OpenAI: GPT-4 technical report (2023) arXiv:2303.08774 [cs.CL] MartÃnez [2023] MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. 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Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. 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Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. 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[2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. 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[2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. 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[2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
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Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. 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[2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) MartÃnez, E.: Re-evaluating GPT-4’s bar exam performance. LPP Working Paper No. 2-2023 (2023). https://dx.doi.org/10.2139/ssrn.4441311 Zhang et al. [2023] Zhang, C., Zhang, C., Zhang, M., Kweon, I.S.: Text-to-image diffusion model in generative AI: A survey. arXiv:2303.07909 (2023) Wei et al. [2022] Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. 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Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. 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Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. 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[2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. 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[2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. 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Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
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[2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. 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Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). 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In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. 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Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. 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[2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al.: Emergent abilities of large language models. Transactions on Machine Learning Research (2022) Noy and Zhang [2023] Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. 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Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. 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R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. 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Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
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[2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Noy, S., Zhang, W.: Experimental evidence on the productivity effects of generative artificial intelligence. Science 381(6654), 187–192 (2023). https://doi.org/10.1126/science.adh2586 Brynjolfsson et al. [2023] Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). 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In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
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Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brynjolfsson, E., Li, D., Raymond, L.R.: Generative ai at work. Technical report, National Bureau of Economic Research (2023) Peng et al. [2023] Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Peng, S., Kalliamvakou, E., Cihon, P., Demirer, M.: The impact of AI on developer productivity: Evidence from github copilot. arXiv:2302.06590 (2023) Zhou and Lee [2023] Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. 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[2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. 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IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Zhou, E., Lee, D.: Generative ai, human creativity, and art. PNAS Nexus 3(3) (2023). https://doi.org/10.1093/pnasnexus/pgae052 Dell’Acqua et al. [2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. 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[2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. 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The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. 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[2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. 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[2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. 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[2023] Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dell’Acqua, F., McFowland, E., Mollick, E.R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., Lakhani, K.R.: Navigating the jagged technological frontier: field experimental evidence of the effects of ai on knowledge worker productivity and quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper (24-013) (2023). https://dx.doi.org/10.2139/ssrn.4573321 Girotra et al. [2023] Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. 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[2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. 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R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. 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[2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. 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Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. 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R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. 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R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. 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[2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
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Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Girotra, K., Meincke, L., Terwiesch, C., Ulrich, K.T.: Ideas are dimes a dozen: Large language models for idea generation in innovation. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4526071 Doshi and Hauser [2023] Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. 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R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
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Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). 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In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Doshi, A.R., Hauser, O.: Generative artificial intelligence enhances creativity. SSRN (2023). https://dx.doi.org/10.2139/ssrn.4535536 Choi and Schwarcz [2024] Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. 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[2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
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Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. 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Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Choi, J.H., Schwarcz, D.: AI assistance in legal analysis: An empirical study. Journal of Legal Education (2024). https://dx.doi.org/10.2139/ssrn.4539836 Kreitmeir and Raschky [2023] Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). 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[2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. 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R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. 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Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. 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Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Kreitmeir, D.H., Raschky, P.A.: The unintended consequences of censoring digital technology–evidence from italy’s chatgpt ban. arXiv:2304.09339 (2023) Boussioux et al. [2024] Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. 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R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. 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[2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
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[2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. 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R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
- Boussioux, L., N Lane, J., Zhang, M., Jacimovic, V., Lakhani, K.R.: The crowdless future? how generative ai is shaping the future of human crowdsourcing. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005 (2024). http://dx.doi.org/10.2139/ssrn.4533642 Haslberger et al. [2023] Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Haslberger, M., Gingrich, J., Bhatia, J.: No great equalizer: experimental evidence on ai in the uk labor market. Available at SSRN (2023). https://dx.doi.org/10.2139/ssrn.4594466 Milmo [2023] Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. 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In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. 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Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. 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[2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. 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R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Milmo, D.: Chatgpt, the popular artificial intelligence chatbot, has reached 100 million users just two months after launching, according to analysts. The Guardian (2023) Din and Wilson [2020] Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. 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[2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. 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[2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. 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Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
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[2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Din, A., Wilson, R.: Crosswalking zip codes to census geographies: Geoprocessing the u.s. department of housing & urban development’s zip code crosswalk files. Cityscape: A Journal of Policy Development and Research 22(1) (2020). https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf Suh et al. [2022] Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Suh, J., Horvitz, E., White, R.W., Althoff, T.: Disparate impacts on online information access during the covid-19 pandemic. Nature Communications 13(1), 7094 (2022). https://doi.org/10.1038/s41467-022-34592-z Google [2023] Google: Google Trends. https://trends.google.com/trendst (2023) Manson et al. [2023] Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). 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[2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. 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R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. 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Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. 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Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. 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In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. 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Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. 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[2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., Ruggles, S.: IPUMS National Historical Geographic Information System: Version 18.0. IPUMS, Minneapolis, MN. http://doi.org/10.18128/D050.V18.0 (2023). https://doi.org/10.18128/D050.V18.0 Pebesma [2018] Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. 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In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. 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[2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. 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[2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Openshaw, S.: The modifiable areal unit problem. 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[2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. 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[2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. 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[2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
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[2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. 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[2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. 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[2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
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Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). 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In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Pebesma, E.: Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10(1), 439–446 (2018) https://doi.org/10.32614/RJ-2018-009 Lorenzo [2023] Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. 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[2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
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Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Lorenzo, P.D.: Usmap: US Maps Including Alaska and Hawaii. (2023). R package version 0.6.3 R Core Team [2021] R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
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[2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. 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Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2021). R Foundation for Statistical Computing Moran [1950] Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
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[2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Moran, P.A.: Notes on continuous stochastic phenomena. Biometrika 37(1/2), 17–23 (1950) Getis and Ord [1992] Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. 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[2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. 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Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
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[2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. 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[2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Getis, A., Ord, J.K.: The analysis of spatial association by use of distance statistics. Geographical analysis 24(3), 189–206 (1992) Roger Bivand [2022] Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
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In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Roger Bivand: R packages for analyzing spatial data: A comparative case study with areal data. Geographical Analysis 54(3), 488–518 (2022). https://doi.org/10.1111/gean.12319 Jr and Dupont [2023] Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
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[2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Jr, F.E.H., Dupont, C.: Hmisc: Harrell Miscellaneous. (2023). R package version 5.1-1 Brooks et al. [2017] Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
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[2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
- Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M.: glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2), 378–400 (2017) https://doi.org/10.32614/RJ-2017-066 Hartig and Lohse [2022] Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
- Hartig, F., Lohse, L.: DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. (2022). R package version 0.4.6 StatCounter [2023] StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
- StatCounter: Search Engine Market Share Worldwide — StatCounter Global Stats. https://gs.statcounter.com/search-engine-market-share (2023) Scheerder et al. [2017] Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
- Scheerder, A., Van Deursen, A., Van Dijk, J.: Determinants of internet skills, uses and outcomes. a systematic review of the second-and third-level digital divide. Telematics and informatics 34(8), 1607–1624 (2017). https://doi.org/10.1016/j.tele.2017.07.007 Blank and Groselj [2016] Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
- Blank, G., Groselj, D.: Dimensions of internet use: amount, variety, and types. In: Current Research on Information Technologies and Society, pp. 27–45 (2016). https://doi.org/10.1080/1369118X.2014.889189 Goel et al. [2012] Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
- Goel, S., Hofman, J., Sirer, M.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 6, pp. 130–137 (2012). https://doi.org/10.1609/icwsm.v6i1.14266 Van Deursen and Van Dijk [2014] Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
- Van Deursen, A.J., Van Dijk, J.A.: The digital divide shifts to differences in usage. New media & society 16(3), 507–526 (2014). https://doi.org/10.1177/1461444813487959 Elena-Bucea et al. [2021] Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
- Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., Coelho, P.S.: Assessing the role of age, education, gender and income on the digital divide: Evidence for the european union. Information Systems Frontiers 23, 1007–1021 (2021) Openshaw [1984] Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
- Openshaw, S.: The modifiable areal unit problem. Concepts and techniques in modern geography (1984) Vogels [2023] Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
- Vogels, E.A.: A majority of Americans have heard of ChatGPT, but few have tried it themselves. https://www.pewresearch.org/short-reads/2023/05/24/a-majority-of-americans-have-heard-of-chatgpt-but-few-have-tried-it-themselves/ (2023) Dorfman [1983] Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
- Dorfman, N.S.: Route 128: the development of a regional high technology economy. Research Policy 12(6), 299–316 (1983). https://doi.org/10.1016/0048-7333(83)90009-4 Ahuja et al. [2023] Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
- Ahuja, K., Hada, R., Ochieng, M., Jain, P., Diddee, H., Maina, S., Ganu, T., Segal, S., Axmed, M., Bali, K., et al.: Mega: Multilingual evaluation of generative AI. rXiv:2303.12528 (2023) Nambi et al. [2023] Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
- Nambi, A., Balloli, V., Ranjit, M., Ganu, T., Ahuja, K., Sitaram, S., Bali, K.: Breaking language barriers with a leap: Learning strategies for polyglot llms. arXiv:2305.17740 (2023) Henneborn [2023] Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
- Henneborn, L.: How generative ai can create job opportunities for individuals with disabilities. MIT Technology Review (2023). https://www.technologyreview.com/2023/11/30/1037769/generative-ai-jobs-disabilities-inclusion-accessibility/ Norris [2001] Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001) Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
- Norris, P.: Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge University Press, Cambridge, UK (2001)
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