Detecting bad behavior isn't enough to prove misalignment—you need forensic investigation to distinguish between malicious intent and innocent mistakes like confusion or shortcuts.
This paper develops a protocol for investigating whether concerning AI model behaviors stem from misalignment (intentional deception) or benign causes like confusion. The authors use chain-of-thought reasoning to generate hypotheses about behavior, then test these hypotheses through targeted prompt and environment modifications across six agentic scenarios.