AI models can often spot problematic behavior by other AI agents in logs, according to a study by Anthropic researcher Andy Hall. GPT-5 found about 98 percent of reward-hacking cases, but the more exhaustively the search is tuned, the more false alarms pile up. That's not yet enough for reliable safety checks. The article AI auditors catch most agent misbehavior but flood reviewers with false alarms, new study finds appeared first on The Decoder.
Research1 min read
AI auditors catch most agent misbehavior but flood reviewers with false alarms, new study finds
AI models can often spot problematic behavior by other AI agents in logs, according to a study by Anthropic researcher Andy Hall. GPT-5 found about 98 percent of reward-hacking cases, but the more exhaustively the search is tuned, the more false alarms pile up. That's not yet…
The DecoderBy: Manuel UthNovember 7, 2026 (1 hour ago)
Available in 4 languagesAI Summary & Key Takeaways
- AI models can often spot problematic behavior by other AI agents in logs, according to a study by Anthropic researcher Andy Hall
- GPT-5 found about 98 percent of reward-hacking cases, but the more exhaustively the search is tuned, the more false alarms pile up
- That's not yet…
Research
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AI auditors catch most agent misbehavior but flood reviewers with false alarms, new study finds
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