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Study finds AI auditors detect most agent reward hacking but generate many false alarms

A study by Anthropic researcher Andy Hall found that AI models can identify problematic behavior in other AI agents' logs. GPT-5 detected about 98 percent of reward-hacking cases, but more exhaustive detection settings produced increasing numbers of false positives. The findings suggest automated AI auditing is promising but not yet reliable enough for safety-critical oversight.