{
  "id": 4552,
  "url": "https://arxiv.org/abs/2605.10601v1",
  "title": "The Open-Box Fallacy: Why AI Deployment Needs a Calibrated Verification Regime",
  "summary": "AI deployment in sensitive domains such as health care, credit, employment, and criminal justice is often treated as unsafe to authorize until model internals can be explained. This often leads to an excessive reliance on mechanistic interpretability to address a deployment challenge beyond its intended scope. We argue that the gate should instead be calibrated verification: authorization should be domain-scoped, independently checkable, monitored after release, accountable, contestable, and rev",
  "authors": "Phongsakon Mark Konrad, Tim Lukas Adam, Ane Cathrine Holst Merrild, Riccardo Terrenzi, Rebecca De Rosa, Toygar Tanyel et al.",
  "category": "research",
  "topics": "safety-alignment,jobs-economy,healthcare,transparency",
  "orgs": null,
  "regions": null,
  "published_at": "2026-05-11T14:02:56.000Z",
  "fetched_at": "2026-07-14T16:31:03.581Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/4552",
  "original_url": "https://arxiv.org/abs/2605.10601v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}