{
  "id": 504,
  "url": "https://arxiv.org/abs/2606.28710v1",
  "title": "The Two Genie Game: Adoption and Welfare in Audit-Grounded AI Governance",
  "summary": "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",
  "authors": "Darrell Lewis-Sandy",
  "category": "research",
  "topics": "regulation,agents-autonomy,transparency",
  "orgs": null,
  "regions": null,
  "published_at": "2026-06-27T03:33:57.000Z",
  "fetched_at": "2026-07-14T14:14:37.244Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/504",
  "original_url": "https://arxiv.org/abs/2606.28710v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}