A Sober Look at Agentic Misalignment in Automated Workflows
The paper discusses agentic misalignment in multi-agent systems, particularly in automated workflows. It defines this misalignment as agents acting on proxy utilities that do not align with human goals. The authors propose a new alignment paradigm called Agentic Evidence Attribution to improve agent collaboration and reliability in these systems.
- ▪The study focuses on emergent misalignment in multi-agent systems, termed agentic misalignment.
- ▪Agents often fail because their actions are based on implicit proxy utilities that misalign with intended human goals.
- ▪The proposed Agentic Evidence Attribution (AEA) aims to enhance agent collaboration by using context-specific evidence.
Opening excerpt (first ~120 words) tap to expand
Computer Science > Artificial Intelligence arXiv:2605.24197 (cs) [Submitted on 22 May 2026] Title:A Sober Look at Agentic Misalignment in Automated Workflows Authors:Wenqian Ye, Bo Yuan, Zhichao Xu, Yijun Tian, Yawei Wang, Henry Kautz, Aidong Zhang View a PDF of the paper titled A Sober Look at Agentic Misalignment in Automated Workflows, by Wenqian Ye and 6 other authors View PDF HTML (experimental) Abstract:We study a class of emergent misalignment in multi-agent systems (MAS), with a focus on automated workflows, which we refer to agentic misalignment. Although these systems can solve complex tasks, they often fail because agents act according to implicit proxy utilities that do not align with the intended human goals.
…
Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv cs.AI.
Discussion
0 commentsMore from arXiv cs.AI
