Data-intensive Innovation and the State: Evidence from AI Firms in China
Artificial intelligence (AI) innovation is data-intensive. States have historically collected large amounts of data, which is now being used by AI firms. Gathering comprehensive information on firms and government procurement contracts in China's facial recognition AI industry, we first study how government data shapes AI innovation. We find evidence of a precise mechanism: because data is sharable across uses, economies of scope arise. Firms awarded public security AI contracts providing access to more government data produce more software for both government and commercial purposes. In a directed technical change model incorporating this mechanism, we then study the trade-offs presented by states' AI procurement and data provision policies. Surveillance states' demand for AI may incidentally promote growth, but distort innovation, crowd-out resources, and infringe on civil liberties. Government data provision may be justified when economies of scope are strong and citizens' privacy concerns are limited.
Professor Martin Beraja is the Pentti Kouri Career Development Assistant Professor of Economics at the Massachusetts Institute of Technology (MIT), as well as a Faculty Research Fellow at the National Bureau of Economic Research (NBER). He is a macroeconomist who has studied business cycles and stabilization policy, the costs of inflation, and how technological innovations shape inequality and economic growth. He has tackled these questions by sometimes developing theory, sometimes using novel data and empirics, but most often by bringing the two together. He is the speaker in the 2016 Restud Tour. Professor Beraja received his Ph.D. in economics from the University of Chicago in 2016.