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Decentralized Infrastructure for (Neuro)science

Published 1 Sep 2022 in cs.GL | (2209.07493v1)

Abstract: The most pressing problems in science are neither empirical nor theoretical, but infrastructural. Scientific practice is defined by coproductive, mutually reinforcing infrastructural deficits and incentive systems that everywhere constrain and contort our art of curiosity in service of profit and prestige. Our infrastructural problems are not unique to science, but reflective of the broader logic of digital enclosure where platformatized control of information production and extraction fuels some of the largest corporations in the world. I have taken lessons learned from decades of intertwined digital cultures within and beyond academia like wikis, pirates, and librarians in order to draft a path towards more liberatory infrastructures for both science and society. Based on a system of peer-to-peer linked data, I sketch interoperable systems for shared data, tools, and knowledge that map onto three domains of platform capture: storage, computation and communication. The challenge of infrastructure is not solely technical, but also social and cultural, and so I attempt to ground a practical development blueprint in an ethics for organizing and maintaining it. I intend this draft as a rallying call for organization, to be revised with the input of collaborators and through the challenges posed by its implementation. I argue that a more liberatory future for science is neither utopian nor impractical -- the truly impractical choice is to continue to organize science as prestige fiefdoms resting on a pyramid scheme of underpaid labor, playing out the clock as every part of our work is swallowed whole by circling information conglomerates. It was arguably scientists looking for a better way to communicate that created something as radical as the internet in the first place, and I believe we can do it again.

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