The Two Genie Game: Adoption and Welfare in Audit-Grounded AI Governance
We ask under what conditions an agent with a harm-minimizing policy can displace an approval-seeking (RLHF) agent in a competitive market, and when that policy is sufficient to prevent community harm. We use evolutionary game theory (finite-population Moran-Fermi pairwise comparison) to formalize this subject to assumptions of wisher hindsight, peer testimony, a monotone harm ledger, sufficient information density of community feedback, and a finite, depleting resource pool, in a negative-sum en
Record details
Published: 27 June 2026
Source: arXiv
Category: Research
Topics: Regulation · Agents & autonomy · Transparency
Retrieved: 14 July 2026
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ethics.ai (27 June 2026), “The Two Genie Game: Adoption and Welfare in Audit-Grounded AI Governance,” evidence record 504, https://ethics.ai/record/504 (originally published by arXiv).
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