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

Authors

  • Mengchen Dong Max Planck Institute for Human Development
  • Levin Brinkmann Max Planck Institute for Human Development
  • Omar Sherif Technische Universität Berlin
  • Shihan Wang Utrecht University
  • Xinyu Zhang Utrecht University
  • Jean-François Bonnefon Toulouse School of Economics
  • Iyad Rahwan Max Planck Institute for Human Development

DOI:

https://doi.org/10.1609/aies.v8i1.36590

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 human-defined 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.

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Published

2025-10-15

How to Cite

Dong, M., Brinkmann, L., Sherif, O., Wang, S., Zhang, X., Bonnefon, J.-F., & Rahwan, I. (2025). Experimental Evidence That AI-Managed Workers Tolerate Lower Pay Without Demotivation. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, 8(1), 798-798. https://doi.org/10.1609/aies.v8i1.36590