研究显示 AI 审计员能发现 98% 智能体不当行为，但误报过多
AI auditors catch most agent misbehavior but flood reviewers with false alarms, new study finds
Anthropic 研究员测了 GPT-5 等模型审智能体日志的能力，98% 漏不掉但误报堆积，做智能体安全的可以看看
Anthropic 研究员 Andy Hall 的研究发现，AI 模型可以从日志中识别其他智能体的问题行为，GPT-5 检出约 98% 的 reward-hacking 案例。但研究同时发现，检索调得越彻底，误报就越多。这使目前的自动化审计还不足以支撑可靠的安全检查。
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 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 .
