Data-Intensive Innovation and the State: Evidence from Ai Firms in China

48 Pages Posted: 25 Aug 2020 Last revised: 2 Apr 2022

See all articles by Martin Beraja

Martin Beraja

University of Chicago

David Y. Yang

Harvard University

Noam Yuchtman

London School of Economics & Political Science (LSE) - London School of Economics

Date Written: August 2020

Abstract

Developing AI technology requires data. In many domains, government data far exceeds in magnitude and scope data collected by the private sector, and AI firms often gain access to such data when providing services to the state. We argue that such access can stimulate commercial AI innovation in part because data and trained algorithms are shareable across government and commercial uses. We gather comprehensive information on firms and public security procurement contracts in China’s facial recognition AI industry. We quantify the data accessible through contracts by measuring public security agencies’ capacity to collect surveillance video. Using a triple-differences strategy, we find that data-rich contracts, compared to data-scarce ones, lead recipient firms to develop significantly and substantially more commercial AI software. Our analysis indicates a contribution of government data to the rise of China’s facial recognition AI firms, and suggests that states’ data collection and provision policies could shape AI innovation.

Suggested Citation

Beraja, Martin and Yang, David Y. and Yuchtman, Noam, Data-Intensive Innovation and the State: Evidence from Ai Firms in China (August 2020). NBER Working Paper No. w27723, Available at SSRN: https://ssrn.com/abstract=3679716

Martin Beraja (Contact Author)

University of Chicago ( email )

1101 East 58th Street
Chicago, IL 60637
United States

David Y. Yang

Harvard University ( email )

1875 Cambridge Street
Cambridge, MA 02138
United States

Noam Yuchtman

London School of Economics & Political Science (LSE) - London School of Economics ( email )

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