BARC-Bench tests AI agents’ safety on 110 workplace tasks
Researchers introduced BARC-Bench, a benchmark of 110 tasks across nine simulated workspaces to measure how AI agents handle safety boundaries. The tasks require agents to follow unstated rules, like scheduling a meeting without revealing sensitive information. Four frontier model configurations were tested across five attempts each, with safety compliance ranging from 9.1% to 72.7%. Even the…
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Key points
- BARC-Bench includes 110 tasks across nine simulated workspaces to test AI safety on unstated rules
- Four frontier models completed tasks safely only 9.1% to 72.7% of the time across five attempts
- Even the strongest model violated safety boundaries in 27.3% of cases
Read the original at arXiv cs.AI · by Kangkang Li, Kelvin Luu, Lily Ma, Tu Trinh, Ying Liu, Mohamed Elfeki primary sourceOpen source ↗
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