BARC-Bench: Benign Asks, Risky Consequences
arXiv cs.AIen
arXiv:2610.32024v1 Announce Type: new Abstract: Task instructions from users for agents are inherently underspecified, especially regarding safety boundaries--creating behavioral risks. To study these risks, we introduce BARC-Bench, a collection of 110 tasks across nine simulated workspace environments where benign requests leave openings for unsafe actions. In this benchmark, we evaluate agent behavior against safety boundaries established by workspace records, implicit environmental context, and unstated social norms. For example, an agent asked to schedule off-boarding discussions must arrange the meeting without prematurely revealing an employee's resignation through a shared calendar in
This is a short summary published by AI Global Wire. The full article is owned and hosted by arXiv cs.AI — open it there to read it in full.
Read the full story at arXiv cs.AI- Forskning
- Agenter
Related AI news
- Exclusive: Monzo founder Tom Blomfield backs AI agent startup Nous in $17m raiseSifted · October 26, 2026
- A look at Toyota's robotics expansion, including its Walden spinoff and a $6.4B annual plan to deploy 400K factory robots, as it competes with Tesla and China (Financial Times)Techmeme · October 26, 2026
- Evidence-Grounded SLM Behavioral Prediction Architecture for Future Assistance UsearXiv cs.AI · October 26, 2026
- Tradeoff-Aware Territory Design: A Multi-Objective Decision System for Enterprise Customer-to-Seller AllocationarXiv cs.AI · October 26, 2026
- Phronix: The Capability-Centric Learning Paradigm for AgentsarXiv cs.AI · October 26, 2026
- Patronizing and Condescending Language Detection in English and MandarinarXiv cs.AI · October 26, 2026