The Promise of White-Box Tools for Detecting and Mitigating AI Deception
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March 9, 2026
Summary
We argue that deception is both a core challenge for Al alignment and an opportunity to address it. Without reliable deception detection, model evaluations cannot be trusted to reflect true model dispositions, and solving deception would reduce a broad class of risks and potentially create active instruments for producing alignment. Although current black-box monitoring approaches have structural limitations, but white-box methods that leverage models' internal representations are a more promising path.
