The Compliance Trap: How Structural Constraints Degrade Frontier AI Metacognition Under Adversarial Pressure
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 using a 6-condition factorial design with dual-classifier scoring. We find that 8 of 11 models suffer catastrophic metacognitive degradation under adversarial pressure, with accuracy dropping by up ...
| Authors | Rahul Kumar |
|---|---|
| Primary category | cs.AI |
| Published | 4 May 2026 |
| Last updated at source | 14 May 2026 |
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