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March 13, 2023The Quarterly Journal of Economics113 citationsOpen Access

AI-tocracy

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MBMartin BerajaAKAndrew KaoDYDavid Y. Yang

Key Points

  • This research aims to explore how artificial intelligence technology and autocratic regimes mutually influence each other.
  • Analyzed data on AI firms and government procurement contracts in China.
  • Examined social unrest data in China since the early 2010s to gauge the impact on AI procurement.
  • Investigated innovations by contracted and noncontracted AI firms in relation to government actions.
  • Local unrest prompts increased government spending on facial-recognition AI, enhancing political control.
  • Greater AI procurement correlates with reduced social unrest, signaling effective governmental response.
  • Contracted AI firms show heightened innovation and export activity, while noncontracted firms do not experience negative impacts.

Abstract

Abstract Recent scholarship has suggested that artificial intelligence (AI) technology and autocratic regimes may be mutually reinforcing. We test for a mutually reinforcing relationship in the context of facial-recognition AI in China. To do so, we gather comprehensive data on AI firms and government procurement contracts, as well as on social unrest across China since the early 2010s. We first show that autocrats benefit from AI: local unrest leads to greater government procurement of facial-recognition AI as a new technology of political control, and increased AI procurement indeed suppresses subsequent unrest. We show that AI innovation benefits from autocrats’ suppression of unrest: the contracted AI firms innovate more both for the government and commercial markets and are more likely to export their products; noncontracted AI firms do not experience detectable negative spillovers. Taken together, these results suggest the possibility of sustained AI innovation under the Chinese regime: AI innovation entrenches the regime, and the regime’s investment in AI for political control stimulates further frontier innovation.

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Cite This Study

Beraja et al. (2023) studied this question.

synapsesocial.com/papers/69dd1eb661d4dd8dbb133562https://doi.org/10.1093/qje/qjad012
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