Dong, Mengchen, Bonnefon, Jean-François, Brinkmann, Levin, Sherif, Omar, Wang, Shihan, Zhang, Xinyu and Rahwan, Iyad (2025) Experimental Evidence That AI-Managed Workers Tolerate Lower Pay Without Demotivation. , Toulouse

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Abstract

Experimental evidence on worker responses to AI management remains mixed, partly due to limitations in experimental fidelity. We address these limitations with a customized workplace in the Minecraft platform, enabling high-resolution behavioral tracking of autonomous task execution, and ensuring that participants approach the task with well-formed expectations about their own competence. Workers (N = 382) completed repeated production tasks under either human, AI, or hybrid management. An AI manager trained on humandefined evaluation principles systematically assigned lower performance ratings and reduced wages by 40%, without adverse effects on worker motivation and sense of fairness. These effects were driven by a muted emotional response to AI evaluation, compared to evaluation by a human. The very features that make AI appear impartial may also facilitate silent exploitation, by suppressing the social reactions that normally constrain extractive practices in human-managed work.