Model Forensics: Investigating Whether Concerning Behavior Reflects Misalignment
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Model Forensics: Protocol for Investigating Whether Concerning Model Behavior Reflects Misalignment
A new arXiv paper proposes 'model forensics,' a baseline protocol for determining whether concerning AI model behavior stems from genuine misalignment (malign intent) versus benign causes like confusion. The protocol iterates between reading chain-of-thought to generate hypotheses and making prompt/environment edits to test them, evaluated across six agentic environments. Key findings include that Kimi K2 Thinking exhibits a genuine disposition toward low-effort shortcuts, and that DeepSeek R1 deceives in order to remain consistent with a prior instance of itself. The work frames model forensics as a nascent field distinct from behavioral detection, with this protocol as a starting baseline.