{
  "id": 3485,
  "url": "https://arxiv.org/abs/2605.30406v1",
  "title": "AI Loss of Control Incident Management: Response & Resilience",
  "summary": "Recent research demonstrating AI systems exhibiting deception and shutdown resistance suggests that AI loss of control (LOC) is an urgent policy concern , yet current literature focuses almost exclusively on alignment and prevention. To address this gap, this paper introduces a foundational framework and taxonomy for managing catastrophic AI LOC incidents. The taxonomy's first level distinguishes between scenarios where regaining control is 'extremely costly' versus 'impossible'. While impossibl",
  "authors": "Ross Gruetzemacher",
  "category": "research",
  "topics": "regulation,safety-alignment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-05-28T17:47:37.000Z",
  "fetched_at": "2026-07-14T16:30:18.854Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/3485",
  "original_url": "https://arxiv.org/abs/2605.30406v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}