Assistant or Actor? Student Trust, Control, and Delegation Regret When Using a General-Purpose AI Agent

תקציר מקורי באנגליתarXiv:2607.18257v1 Announce Type: cross Abstract: When AI agents shift from answering questions to taking actions, users face a new problem: deciding what to delegate, to a system whose action space they cannot fully anticipate. We call the resulting dissatisfaction delegation regret, a pattern in which users regret not that the agent erred, but that it acted beyond what they would have authorized. In a controlled study, 20 university students completed five common daily tasks using OpenClaw, a general-purpose AI agent, across tasks chosen to vary in privacy, stakes, and reversibility. For each task we measured trust, perceived control, transparency, supervision burden, and approval preference on 5-point Likert scales, and collected free-text reflections analyzed through thematic coding. T