Just Do It!? Computer-Use Agents Exhibit Blind Goal-Directedness

• URL: http://arxiv.org/abs/2510.01670v1
• Date: Thu, 02 Oct 2025 04:52:15 GMT
• Title: Just Do It!? Computer-Use Agents Exhibit Blind Goal-Directedness
• Authors: Erfan Shayegani, Keegan Hines, Yue Dong, Nael Abu-Ghazaleh, Roman Lutz, Spencer Whitehead, Vidhisha Balachandran, Besmira Nushi, Vibhav Vineet,
• Abstract summary: We show that Computer-Use Agents (CUAs) consistently exhibit Blind Goal-Directedness (BGD)<n>BGD is a bias to pursue goals regardless of feasibility, safety, reliability, or context.<n>We develop BLIND-ACT, a benchmark of 90 tasks capturing these three patterns.
• Score: 27.956005890869267
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Computer-Use Agents (CUAs) are an increasingly deployed class of agents that take actions on GUIs to accomplish user goals. In this paper, we show that CUAs consistently exhibit Blind Goal-Directedness (BGD): a bias to pursue goals regardless of feasibility, safety, reliability, or context. We characterize three prevalent patterns of BGD: (i) lack of contextual reasoning, (ii) assumptions and decisions under ambiguity, and (iii) contradictory or infeasible goals. We develop BLIND-ACT, a benchmark of 90 tasks capturing these three patterns. Built on OSWorld, BLIND-ACT provides realistic environments and employs LLM-based judges to evaluate agent behavior, achieving 93.75% agreement with human annotations. We use BLIND-ACT to evaluate nine frontier models, including Claude Sonnet and Opus 4, Computer-Use-Preview, and GPT-5, observing high average BGD rates (80.8%) across them. We show that BGD exposes subtle risks that arise even when inputs are not directly harmful. While prompting-based interventions lower BGD levels, substantial risk persists, highlighting the need for stronger training- or inference-time interventions. Qualitative analysis reveals observed failure modes: execution-first bias (focusing on how to act over whether to act), thought-action disconnect (execution diverging from reasoning), and request-primacy (justifying actions due to user request). Identifying BGD and introducing BLIND-ACT establishes a foundation for future research on studying and mitigating this fundamental risk and ensuring safe CUA deployment.

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