{
  "id": 6160,
  "url": "https://arxiv.org/abs/2604.07778v2",
  "title": "The Accountability Horizon: An Impossibility Theorem for Governing Human-Agent Collectives",
  "summary": "Existing accountability frameworks for AI systems, legal, ethical, and regulatory, rest on a shared assumption: for any consequential outcome, at least one identifiable person had enough involvement and foresight to bear meaningful responsibility. This paper proves that agentic AI systems violate this assumption not as an engineering limitation but as a mathematical necessity once autonomy exceeds a computable threshold. We introduce Human-Agent Collectives, a formalisation of joint human-AI sys",
  "authors": "Haileleol Tibebu, Hewan Shemtaga",
  "category": "research",
  "topics": "regulation,agents-autonomy,transparency",
  "orgs": null,
  "regions": null,
  "published_at": "2026-04-09T04:08:26.000Z",
  "fetched_at": "2026-07-14T16:32:15.638Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/6160",
  "original_url": "https://arxiv.org/abs/2604.07778v2",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}