Data-intensive technologies such as AI may reshape the modern world. We propose that two features of data interact to shape innovation in data-intensive economies: first, states are key collectors and repositories of data; second, data is a non-rival input in innovation. We document the importance of state-collected data for innovation using comprehensive data on Chinese facial recognition AI firms and government contracts. Firms produce more commercial software and patents, particularly data-intensive ones, after receiving government public security contracts. Moreover, effects are largest when contracts provide more data. We then build a directed technical change model to study the state's role in three applications: autocracies demanding AI for surveillance purposes, data-driven industrial policy, and data regulation due to privacy concerns. When the degree of non-rivalry is as strong as our empirical evidence suggests, the state's collection and processing of data can shape the direction of innovation and growth of data-intensive economies.
David Yang’s research focuses on political economy, behavioral and experimental economics, economic history, and cultural economics. In particular, David studies the forces of stability and forces of changes in authoritarian regimes, drawing lessons from historical and contemporary China. David received a B.A. in Statistics and B.S. in Business Administration from University of California at Berkeley, and PhD in Economics from Stanford. David is currently a Prize Fellow in Economics, History, and Politics at Harvard and a Postdoctoral Fellow at J-PAL at MIT. He also joined Harvard’s Economics Department as an Assistant Professor as of 2020.