Proxy Stakeholder Concept

• Proxy stakeholder concept is a formal mechanism whereby non-primary entities (human, algorithmic, or contract-based) represent stakeholders in decision-making and governance.
• It employs models like stake delegation in PoS blockchains, proxy voting, and salience clustering to enhance participation and ensure scalable, inclusive representation.
• Analytical evaluations highlight trade-offs in computational complexity, incentive alignment, and manipulation risks, driving advances in proxy selection and system validation.

The proxy stakeholder concept refers to a formal mechanism whereby an entity other than the direct or primary user is empowered to represent, decide, or participate on behalf of another party in shared decision, validation, governance, or design processes. Proxy stakeholders arise as an abstraction over direct participation, enabling scalable attention allocation, inclusive representation, and multi-agent value alignment across distributed systems, blockchains, software engineering, and AI governance. The precise realization of proxy stakeholder roles varies by domain but is unified by the delegation of agency, voting, or expressive capability from the primary stakeholder to a representative, which can be human, algorithmic, or contract-based.

1. Formal Definitions and Core Models

The proxy stakeholder abstraction is instantiated in several technically rigorous frameworks:

• Stake Delegators in Proof-of-Stake (PoS) Blockchains: In PoS consensus, an agent $i$ with stake $s_i$ can become a proxy stakeholder (delegator) by choosing a delegation action $d_i$ mapping their stake to pools, satisfying $\sum_j d_i(j) = s_i$. The protocol routes $i$'s stake according to $d_i$, assigning validation and reward rights not directly but via selected pool operators (Kiayias et al., 2024).
• Proxy Agents in Multi-Stakeholder AI Systems: A proxy stakeholder agent ("SH-agent") is an autonomous module encapsulating the preferences, policies, or constraints of a specific stakeholder type $i$ (e.g., student, parent) and returns structured assessments (approve, reject, utility) over candidate actions without exposing its confidential internal state (Uchoa et al., 27 Oct 2025).
• Proxy Voters in Delegated Voting: Given voters with incomplete preferences $v_i$ over proposals, a set of proxies ("dReps") advertises full ballots. A voter $i$ delegates her vote to proxy $t$ if their revealed ballots are sufficiently similar (e.g., Hamming distance under a threshold), updating the election outcome aggregation accordingly (Amanatidis et al., 2023).
• Salience-Clustered Stakeholder Proxies: In requirements engineering, stakeholders are positioned in a multidimensional "salience" space, and clusters (e.g., those with maximal (power, legitimacy, urgency)-centroid) are elected as the definitive proxies, serving as representative voices in optimization and design (Aguila et al., 2023).

2. Mechanisms and Computation

Proxy stakeholder mechanisms encode the rules and incentives for delegation, aggregation, and equilibrium selection:

• Game-Theoretic Strategies (PoS/Delegated Governance): Each agent chooses between operating a pool, idling, or becoming a delegator; payment schemes are parameterized to maintain equilibrium incentives. Key reward functions include per-unit delegation reward $r$, feasibility conditions for pools, and solo operator threat margins $\alpha(s,c)$ (Kiayias et al., 2024).
• Proxy Policy Functions (AI Governance): SH-agents expose a vote $v_i = \pi_i(a; s_i)$ over actions $a$, potentially a utility $U_i(a)$, aggregated via hierarchical or weighted-sum schemes. Delegation preserves privacy and enables distributed, auditable negotiation among heterogeneous policies (Uchoa et al., 27 Oct 2025).
• Delegation and Approximation Bounds (Proxy Voting): With $k$ proxies, approximation guarantees to optimal outcomes depend upon electorate coherence and threshold rules. Explicit bounds (e.g., with majority-delegation, two proxies suffice for exact welfare recovery when the electorate is coherent) are derived with tight impossibility and NP-hardness results for proxy selection (Amanatidis et al., 2023).
• Proxy Account Contracts (NFTAA): The NFTAA pattern represents each staking right as a transferable ERC-721 token-linked proxy contract, enforcing that only the NFT holder can exercise staking or unstaking logic (via an onlyNFTOwner modifier). Ownership transfer of the NFT directly reassigns all future proxy rights, ensuring atomic delegation and composability (Valaštín et al., 2024).

3. Domains of Application

The proxy stakeholder model has been deployed across a spectrum of technical and governance-intensive systems:

Domain	Proxy Role	Technical Realization
PoS Blockchains	Delegator ("proxy stakeholder")	Delegation vector $d_i$ and reward contracts
Voting/Governance	Proxy voter/dRep	Aggregated voting, Hamming-threshold matching
AI Governance/Tutoring	SH-agent (policy proxy)	Modular agents, privacy-preserving policy evaluation
Requirements Engineering	Salience-cluster proxy group	Salience clustering, Pareto-front coverage metrics
Inclusive Navigation	Informal/formal proxy	Scenario-based requirements elicitation
On-chain Ownership	NFTAA proxy account holder	ERC-721/token-bound minimal proxy contracts

Each instantiation addresses domain-specific requirements for scalability, representativity, and formal guarantees concerning agency, legitimacy, and equilibrium stability.

4. Analytical Properties and Trade-Offs

Proxy stakeholder systems reveal mathematically tractable and empirically validated trade-offs:

• Participation vs. Decentralization vs. Expenditure: Tuning payment function parameters in PoS proxy delegation games arbitrates between maximizing overall stake participation ($O^P$), increasing decentralization ($O^D_\ell$), and minimizing total protocol expenditure ($O^E$). For instance, increasing the idle baseline $\epsilon$ shifts agents from active delegation to idling, decreasing participation and expenditure while potentially enhancing decentralization (Kiayias et al., 2024).
• Legitimacy and Social Welfare (Voting): With increasing numbers of proxies, the welfare (measured as intrinsic utility of the elected option) steadily improves, but the marginal benefit decays after a handful of well-designed proxies. Coherence in agent preferences and suitable tie-breaking rules are necessary for close-to-optimal legitimacy (Amanatidis et al., 2023).
• Privacy, Conflict Resolution, and Alignment: Multi-agent proxy frameworks employ privacy-preserving evaluation, hard and soft constraint aggregation, and auditable negotiation (e.g., GloVE-explained policy rules) to resolve policy conflicts and align collective outcomes with stakeholder heterogeneity (Uchoa et al., 27 Oct 2025, Yadav et al., 5 Nov 2025).
• Coverage and Efficiency (Requirements Engineering): Reducing the stakeholder set to a salience-maximal proxy cluster preserves average coverage over all stakeholders' requirements, statistically indistinguishable from using the full set, while reducing participation overhead by up to 87.8% (Aguila et al., 2023).

5. Methodologies for Proxy Selection and Integration

The operationalization of proxies is domain-specific but adheres to systematic selection and integration methodologies:

• Clustering for Proxy Reduction: Agglomerative, $k$-means, and $k$-medoids clustering in stakeholder salience space, with empirical cluster validity indices, identify representative proxy sets for requirements selection (Aguila et al., 2023).
• Threshold Strategies and Bayesian Stability: In PoS delegation games, thresholding on agent types (e.g., stake size or willingness to bear costs) yields tractable partial strategies $f:\mathbf{\theta}\to\{0,1\}$ for ex ante equilibrium analysis (Kiayias et al., 2024).
• Persona Prompting in LLM-based Risk Assessment: Instantiating stakeholder proxies as prompt-engineered LLMs (Risk Atlas Nexus, GloVE pipeline) enables explicit, inspectable modeling of diverse risk-based perspectives, with stable binary risk-profiles derived via intersection over paraphrase sets (Yadav et al., 5 Nov 2025).
• Proxy Account Synthesis in Smart Contracts: NFTAA-based proxy construction couples contract logic and ERC-721 token ownership, enforcing a robust link between asset transfer and delegated privilege (Valaštín et al., 2024).

6. Illustrative Findings, Equilibrium Structures, and Systemic Impact

Empirical analysis across multiple proxies and parameter regimes demonstrates:

• PoS Proxy Delegation: Numerical simulations with $n=1000$ agents indicate stable equilibria with $\sim$30% of all stake pledged by pool operators and $\sim$70% delegated, confirming the efficacy of proxy mechanisms to drive high participation and decentralization under suitable payment parameters. System designers can navigate key trade-offs via structural tuning (Kiayias et al., 2024).
• Voting with Proxy Delegation: Welfare can be restored to near-optimal levels (≥90%) in practical systems with $5$–$10$ proxies, especially with low delegation thresholds and moderately coherent electorates, as validated on MovieLens data (Amanatidis et al., 2023).
• Requirements Coverage via Proxy Clustering: Proxy sets as small as 11–33 out of 98 initial stakeholders (66–87% reduction) do not significantly diminish coverage in the Next Release Problem, provided clustering is salience-based rather than naïve quartile-cut (Aguila et al., 2023).
• AI Risk Assessment: Conflict rates and semantic scores quantify alignment and divergence among proxies, enabling nuanced visualizations and policy interventions (e.g., harmonizing explainability standards between surgeons and nurses using explicit IF/DESPITE rules) (Yadav et al., 5 Nov 2025).
• Proxy Account Performance and Usability: NFTAA proxy contracts typically impose minimal additional gas and are fully composable with DeFi and staking derivatives; their standardized design affords secure, atomic delegation and effective integration with EVM-based platforms (Valaštín et al., 2024).

7. Limitations, Open Problems, and Future Research Directions

While proxy stakeholder mechanisms enhance scalability, representativity, and manageability, expressed challenges remain:

• Vulnerability to Poor Proxy Selection: Single-proxy systems in non-coherent electorates offer weak welfare guarantees and are fragile with respect to manipulation or mismatched incentives (Amanatidis et al., 2023).
• Incentive Alignment and Strategic Delegation: Ensuring that proxies, particularly when strategic, act in alignment with the broader social optimum necessitates refined incentive and reputation architectures.
• Computational Complexity: Selection of optimal proxy sets and equilibrium computation may be NP-hard; efficient heuristics and approximation schemes are critical for real-world deployment (Amanatidis et al., 2023).
• Cross-Domain Generalization: Integration of proxy mechanisms in new domains (e.g., non-EVM blockchains, federalized AI governance) requires careful adaptation of technical, legal, and operational frameworks.
• Empirical Validation and Privacy Guarantees: Systematic empirical benchmarking, privacy auditing (especially with LLM-driven proxies), and formal security analysis of contract-based proxies are active areas for future work (Uchoa et al., 27 Oct 2025, Valaštín et al., 2024).

The proxy stakeholder concept, grounded in precise mathematical, algorithmic, and architectural models, provides a robust scaffold for scalable, accountable, and inclusive participation across a growing set of high-stakes, multi-actor technological domains.