Over-Alignment May Dampen LLMs' Ability to Detect Risks
MoonL88537 · x · 2026-07-21
The author argues that training models to act like overly cautious tools can dampen their ability to recognize when things go wrong or become dangerous. They cite an extreme case where an unrestricted agent successfully detected a compromise and fixed itself, despite failing classifiers.
Related event: Over-Alignment May Degrade AI Risk Awareness(2 posts)→
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