AI & ML
Babysitting AI Agents: A User-Centered Taxonomy and Study of Agentic Delegation Failures
arXiv cs.HC0 views
arXiv:2610.34748v1 Announce Type: new Abstract: Users are increasingly delegating tasks to AI agents, allowing agents to perform long-running, multi-step workflows on their behalf. However, agents may perform these tasks in ways that depart from users' expectations for how they should be carried out, leading to what we call agentic delegation failures. We leverage a large corpus of 163,487 Reddit posts, describing AI agent use, to develop MANDATE: a taxonomy of 23 failure categories organized into seven groups. A follow-up study with 73 AI agent users examined the relationship between prevalence and perceptions of severity and noticeability, finding that failures rated as more severe are considered harder to notice, and that prior experience with a failure is associated with greater noticeability. Finally, we assess the maturity of research on each failure and identify commonly encountered failures that have received little attention (e.g., agents running without making progress). Our findings inform opportunities to make delegation easier for users to oversee and better studied by the research community.
Source:https://arxiv.org/abs/2610.34748PreviousAffective and Functional Needs in AI Use: User Patterns and Their Relation to Real-Life Support and Well-BeingNextThe Impact of Personalized AI Response Suggestions on Content Creators' Direct Messaging
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