Data-intensive technologies, like AI, are increasingly widespread. We argue that the direction of innovation and growth in data-intensive economies may be crucially shaped by the state because: (i) the state is a key collector of data and (ii) data is sharable across uses within firms, potentially generating economies of scope. We study a prototypical setting: facial recognition AI in China. Collecting comprehensive data on firms and government procurement contracts, we find evidence of economies of scope arising from government data: firms awarded contracts providing access to more government data produce both more government and commercial software. We then build a directed technical change model to study the implications of government data access for the direction of innovation, growth, and welfare. We conclude with three applications showing how data-intensive innovation may be shaped by the state: both directly, by setting industrial policy; and indirectly, by choosing surveillance levels and privacy regulations.
Email us at digitalinitiative@hbs.edu for information on attending this seminar.