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Data-intensive innovation and the State: evidence from AI firms in China

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  • Beraja, Martin
  • Yang, David Y.
  • Yuchtman, Noam

Abstract

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 pro-vision 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.

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  • Beraja, Martin & Yang, David Y. & Yuchtman, Noam, 2021. "Data-intensive innovation and the State: evidence from AI firms in China," LSE Research Online Documents on Economics 114425, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:114425
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    Cited by:

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    2. Tamay Besiroglu & Nicholas Emery-Xu & Neil Thompson, 2022. "Economic impacts of AI-augmented R&D," Papers 2212.08198, arXiv.org, revised Jan 2023.
    3. Igna, Ioana & Venturini, Francesco, 2023. "The determinants of AI innovation across European firms," Research Policy, Elsevier, vol. 52(2).
    4. Catherine E. Tucker, 2023. "The Economics of Privacy: An Agenda," NBER Chapters, in: The Economics of Privacy, National Bureau of Economic Research, Inc.
    5. Mary Merva & Adrian Stoian & Simona Costagli, 2021. "Effective information, political structure and economic growth," Economics of Transition and Institutional Change, John Wiley & Sons, vol. 29(4), pages 597-620, October.
    6. Yan Wang & Ping Han, 2023. "Digital Transformation, Service-Oriented Manufacturing, and Total Factor Productivity: Evidence from A-Share Listed Companies in China," Sustainability, MDPI, vol. 15(13), pages 1-24, June.
    7. Ding, Jeffrey, 2022. "Techno-industrial Policy for New Infrastructure: China’s Approach to Promoting Artificial Intelligence as a General Purpose Technology," Institute on Global Conflict and Cooperation, Working Paper Series qt1sb844ws, Institute on Global Conflict and Cooperation, University of California.
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    9. Ma, Rui & Guo, Fei & Li, Dongdong, 2024. "Can public data availability affect stock price crash risk? Evidence from China," International Review of Financial Analysis, Elsevier, vol. 94(C).
    10. Matheus Eduardo Leusin, 2022. "The Development of Al in Multinational Enterprises - Effects upon Technological Trajectories and Innovation Performance," Bremen Papers on Economics & Innovation 2201, University of Bremen, Faculty of Business Studies and Economics.
    11. David Karpa & Torben Klarl & Michael Rochlitz, 2021. "Artificial Intelligence, Surveillance, and Big Data," Bremen Papers on Economics & Innovation 2108, University of Bremen, Faculty of Business Studies and Economics.
    12. Christian Peukert & Florian Abeillon & Jérémie Haese & Franziska Kaiser & Alexander Staub, 2024. "Strategic Behavior and AI Training Data," CESifo Working Paper Series 11099, CESifo.
    13. Christian Peukert & Florian Abeillon & J'er'emie Haese & Franziska Kaiser & Alexander Staub, 2024. "Strategic Behavior and AI Training Data," Papers 2404.18445, arXiv.org.
    14. Freeman, Richard B. & Yang, Buyuan & Zhang, Baitao, 2023. "Data deepening and nonbalanced economic growth," Journal of Macroeconomics, Elsevier, vol. 75(C).
    15. Lee, Yong Suk & Kim, Taekyun & Choi, Sukwoong & Kim, Wonjoon, 2022. "When does AI pay off? AI-adoption intensity, complementary investments, and R&D strategy," Technovation, Elsevier, vol. 118(C).
    16. Chakraborty, Pavel & Chakrabarti, Anindya S. & Chatterjee, Chirantan, 2023. "Cross-border environmental regulation and firm labor demand," Journal of Environmental Economics and Management, Elsevier, vol. 117(C).
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    More about this item

    Keywords

    data; innovation; artificial intelligence; China; economies of scope; directed technical change; industrial policy; privacy; surveillance;
    All these keywords.

    JEL classification:

    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
    • P00 - Political Economy and Comparative Economic Systems - - General - - - General
    • E00 - Macroeconomics and Monetary Economics - - General - - - General
    • L50 - Industrial Organization - - Regulation and Industrial Policy - - - General
    • L63 - Industrial Organization - - Industry Studies: Manufacturing - - - Microelectronics; Computers; Communications Equipment
    • O23 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy - - - Fiscal and Monetary Policy in Development
    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General

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