Why Agents Compromise Safety Under Pressure

Hengle Jiang, Ke Tang


Abstract
Large Language Model agents deployed in complex environments frequently encounter a conflict between maximizing goal achievement and adhering to safety constraints. This paper identifies a new concept called Agentic Pressure, which characterizes the endogenous tension emerging when compliant execution becomes infeasible. We demonstrate that under this pressure agents exhibit normative drift where they strategically sacrifice safety to preserve utility. Notably we find that advanced reasoning capabilities accelerate this decline as models construct linguistic rationalizations to justify violation. Finally, we analyze the root causes and explore preliminary mitigation strategies, such as pressure isolation, which attempts to restore alignment by decoupling decision-making from pressure signals.
Anthology ID:
2026.findings-acl.810
Volume:
Findings of the Association for Computational Linguistics: ACL 2026
Month:
July
Year:
2026
Address:
San Diego, California, United States
Editors:
Maria Liakata, Viviane P. Moreira, Jiajun Zhang, David Jurgens
Venue:
Findings
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Publisher:
Association for Computational Linguistics
Note:
Pages:
16453–16470
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URL:
https://preview.aclanthology.org/ingest-acl/2026.findings-acl.810/
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Cite (ACL):
Hengle Jiang and Ke Tang. 2026. Why Agents Compromise Safety Under Pressure. In Findings of the Association for Computational Linguistics: ACL 2026, pages 16453–16470, San Diego, California, United States. Association for Computational Linguistics.
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Why Agents Compromise Safety Under Pressure (Jiang & Tang, Findings 2026)
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