Post-Incident Recovery Model

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  "dateCreated": "2026-02-15",
  "summary": "Analyzes recovery pathways from AI incidents across five types (technical failures, trust collapse, expertise loss, alignment failures). Finds clear attribution enables 3-5x faster detection, preserved expertise reduces recovery time by 2-100x depending on degradation level, and recommends allocating 5-10% of safety resources to recovery capacity, particularly for neglected trust/epistemic recovery and skill preservation.",
  "description": "This model analyzes recovery pathways from AI incidents. It finds clear attribution enables 3-5x faster recovery, and recommends 5-10% of safety resources for recovery capacity, particularly trust and skill preservation.",
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