Experimental Evidence That AI-Managed Workers Tolerate Lower Pay Without Demotivation
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.
Cite
@article{arxiv.2505.21752,
title = {Experimental Evidence That AI-Managed Workers Tolerate Lower Pay Without Demotivation},
author = {Mengchen Dong and Levin Brinkmann and Omar Sherif and Shihan Wang and Xinyu Zhang and Jean-François Bonnefon and Iyad Rahwan},
journal= {arXiv preprint arXiv:2505.21752},
year = {2025}
}