AI is reshaping workplace dynamics as people increasingly delegate tasks to intelligent assistants. Yet how AI delegates are perceived compared to human delegates—and how their performance and their received feedback shape perceptions—remains unclear. We conducted a 2×2×2 between-subject experiment where participants delegated a scheduling task to either a human or an AI agent, vary- ing their competence (high vs. low) and valence of received feed- back (positive vs. negative) toward their performance. Participants generally had higher trust in human assistants; yet a striking asym- metry emerged: when an AI assistant received negative feedback, participants felt the criticism as more self-directed—an “AI Phan- tom Limb” effect—whereas positive feedback transferred less. This asymmetry did not appear with human delegates. These findings highlight broader design implications, suggesting that AI delegation might blur the boundary between self and other. We also discuss how these findings extend theories of delegation and responsibility attribution to AI.
ACM CHI Conference on Human Factors in Computing Systems