Working Paper
Better Technology, Worse Motivation: GenAI and the Mediocrity Trap
This version: July 2025
Abstract
While generative AI (GenAI) promises productive efficiency, it can paradoxically lead to lower-quality work. We conducted an experiment with professional illustrators and found that AI assistance flattens the quality curve—it accelerates initial gains but sharply diminishes the returns on sustained effort. Faced with this, a significant number of professionals made a strategic choice: they sacrificed the final quality to save time. Our finding highlights a critical challenge for GenAI, which can weaken the motivation required for creative excellence and innovation.
Acknowledgements
We are grateful to Jen Brown, Jiahua Che, Wouter Dessein, Florian Englmaier, Daniel Ferreira, Guido Friebel, Alfonso Gambardella, Luis Garicano, Juan Pantano, Uta Schonberg, Marshall Van Alstyne, Yanhui Wu, Jubo Yan, Songfa Zhong, participants at ACOE, OESS and various seminars for helpful comments and suggestions. We thank Peixuan Huang, Yele Ma, Zhiwei Shang, Xinjue Yao for providing excellent research assistance. The content is solely the responsibility of the authors.
Related Research
Suggested Citation
Chen, Y. J., Gong, J., Li, J., & Zhao, Z. (2025). Better technology, worse motivation: Genai’s mediocrity trap∗ (CAMO Working Paper No. 2025-01). HKU Centre for AI, Management and Organization. https://camo.hku.hk/2025-01-better-technology-worse/
BibTeX
@techreport{chen_gong_li_zhao_2025,
author = {Chen, Yvonne Jie and Gong, Jie and Li, Jin and Zhao, Zibo},
title = {Better Technology, Worse Motivation: GenAI’s Mediocrity Trap∗},
institution = {HKU Centre for AI, Management and Organization},
type = {{CAMO} Working Paper},
number = {2025-01},
year = {2025},
month = jul,
url = {https://camo.hku.hk/2025-01-better-technology-worse/}
}