Excerpt
September 2, 2025, Paper (Draft): "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 ex pertise 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, pro moting 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."
Citations
Zoë Cullen, Danielle Li, and Shengwu Li, Labor as Capital: AI and the Ownership of Expertise, preliminary & incomplete draft, first draft August 12, 2025; this draft September 2, 2025 (unpublished manuscript), accessed September 3, 2025, https://zcullen.github.io/assets/docs/Labor‑as‑Capital_WP.pdf