Experimental Evidence That AI-Managed Workers Tolerate Lower Pay Without Demotivation

Mengchen Dong, Levin Brinkmann, Omar Sherif, Shihan Wang, Xinyu Zhang, Jean-François Bonnefon and Iyad Rahwan ()
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Mengchen Dong: Max Planck Institute for Human Development - Max-Planck-Gesellschaft
Levin Brinkmann: Max Planck Institute for Human Development - Max-Planck-Gesellschaft
Omar Sherif: Max Planck Institute for Human Development - Max-Planck-Gesellschaft
Shihan Wang: Universiteit Utrecht / Utrecht University [Utrecht]
Xinyu Zhang: Universiteit Utrecht / Utrecht University [Utrecht]
Jean-François Bonnefon: TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, TSM - Toulouse School of Management Research - UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - CNRS - Centre National de la Recherche Scientifique - TSM - Toulouse School of Management - UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse
Iyad Rahwan: Max Planck Institute for Human Development - Max-Planck-Gesellschaft

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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.

Keywords: Peprint; Computers and Society; Human-Computer Interaction (search for similar items in EconPapers)
Date: 2025-08-29
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