{
  "id": 5022,
  "url": "https://arxiv.org/abs/2605.02398v2",
  "title": "The Compliance Trap: How Structural Constraints Degrade Frontier AI Metacognition Under Adversarial Pressure",
  "summary": "As frontier AI models are deployed in high-stakes decision pipelines, their ability to maintain metacognitive stability (knowing what they do not know, detecting errors, seeking clarification) under adversarial pressure is a critical safety requirement. Current safety evaluations focus on detecting strategic deception (scheming); we investigate a more fundamental failure mode: cognitive collapse. We present SCHEMA, an evaluation of 11 frontier models from 8 vendors across 67,221 scored records u",
  "authors": "Rahul Kumar",
  "category": "research",
  "topics": "regulation,finance-investment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-05-04T09:40:21.000Z",
  "fetched_at": "2026-07-14T16:31:26.336Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/5022",
  "original_url": "https://arxiv.org/abs/2605.02398v2",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}