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AI, Ageing and Brain-Work Productivity: Technological Change in Professional Japanese Chess

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  • Eiji Yamamura
  • Ryohei Hayashi

Abstract

Using Japanese professional chess (Shogi) players records in the novel setting, this paper examines how and the extent to which the emergence of technological changes influences the ageing and innate ability of players winning probability. We gathered games of professional Shogi players from 1968 to 2019. The major findings are: (1) diffusion of artificial intelligence (AI) reduces innate ability, which reduces the performance gap among same-age players; (2) players winning rates declined consistently from 20 years and as they get older; (3) AI accelerated the ageing declination of the probability of winning, which increased the performance gap among different aged players; (4) the effects of AI on the ageing declination and the probability of winning are observed for high innate skill players but not for low innate skill ones. This implies that the diffusion of AI hastens players retirement from active play, especially for those with high innate abilities. Thus, AI is a substitute for innate ability in brain-work productivity.

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  • Eiji Yamamura & Ryohei Hayashi, 2022. "AI, Ageing and Brain-Work Productivity: Technological Change in Professional Japanese Chess," Papers 2204.07888, arXiv.org.
    • Handle: RePEc:arx:papers:2204.07888
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    References listed on IDEAS

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    1. Daron Acemoglu & Pascual Restrepo, 2020. "The wrong kind of AI? Artificial intelligence and the future of labour demand," Cambridge Journal of Regions, Economy and Society, Cambridge Political Economy Society, vol. 13(1), pages 25-35.
    2. Daron Acemoglu & Claire Lelarge & Pascual Restrepo, 2020. "Competing with Robots: Firm-Level Evidence from France," AEA Papers and Proceedings, American Economic Association, vol. 110, pages 383-388, May.
    3. David H. Autor, 2015. "Why Are There Still So Many Jobs? The History and Future of Workplace Automation," Journal of Economic Perspectives, American Economic Association, vol. 29(3), pages 3-30, Summer.
    4. Daron Acemoglu & David Autor & Jonathon Hazell & Pascual Restrepo, 2020. "AI and Jobs: Evidence from Online Vacancies," Working Papers 279, Princeton University, Department of Economics, Center for Economic Policy Studies..
    5. Acemoglu, Daron & Autor, David, 2011. "Skills, Tasks and Technologies: Implications for Employment and Earnings," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 12, pages 1043-1171, Elsevier.
    6. Daron Acemoglu & Pascual Restrepo, 2018. "The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment," American Economic Review, American Economic Association, vol. 108(6), pages 1488-1542, June.
    7. Alison Booth & Eiji Yamamura, 2018. "Performance in Mixed-Sex and Single-Sex Competitions: What We Can Learn from Speedboat Races in Japan," The Review of Economics and Statistics, MIT Press, vol. 100(4), pages 581-593, October.
    8. Daron Acemoglu & David Autor & Jonathon Hazell & Pascual Restrepo, 2020. "AI and Jobs: Evidence from Online Vacancies," Working Papers 279, Princeton University, Department of Economics, Center for Economic Policy Studies..
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