Professor Zoë Cullen is an Associate Professor at Harvard Business School. Before joining HBS, she worked for a Southeast Asian bank in the Chief Economist role between 2016 and 2018. Her research is focused on labor economics, behavioral economics, and the economics of technologies that shape labor markets. She is an NBER Affiliate in Labor Studies and an Associate Editor at the Journal of Political Economy.
Abstract
Workplace surveillance generates data that can train AI systems to replicate worker expertise. Using a large online survey experiment of U.S. full-time workers, we show that workers adjust their knowledge contributions when made aware of this dynamic: they rationally withhold expertise due to career concerns. We formalize this behavior in a model of knowledge supply under surveillance-enabled AI and use it to evaluate alternative policies. Individual data ownership— workers’ preferred policy—eliminates knowledge withholding but creates negative externalities: one worker’s data strengthens the firm’s bargaining position against others, potentially making all workers worse off. In contrast, collective data ownership achieves the first-best outcome, promoting knowledge sharing while allowing workers to benefit from AI-driven productivity gains. These findings highlight the importance of labor agreements in shaping AI adoption in labor markets.
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