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Artificial Intelligence, Automation and Work

Author

Listed:
  • Daron Acemoglu

    (MIT)

  • Pascual Restrepo

    (Boston University)

Abstract
We summarize a framework for the study of the implications of automation and AI on the demand for labor, wages, and employment. Our task-based framework emphasizes the displacement effect that automation creates as machines and AI replace labor in tasks that it used to perform. This displacement effect tends to reduce the demand for labor and wages. But it is counteracted by a productivity effect, resulting from the cost savings generated by automation, which increase the demand for labor in non-automated tasks. The productivity effect is complemented by additional capital accumulation and the deepening of automation (improvements of existing machinery), both of which further increase the demand for labor. These countervailing effects are incomplete. Even when they are strong, automation in- creases output per worker more than wages and reduce the share of labor in national income. The more powerful countervailing force against automation is the creation of new labor-intensive tasks, which reinstates labor in new activities and tends to in- crease the labor share to counterbalance the impact of automation. Our framework also highlights the constraints and imperfections that slow down the adjustment of the economy and the labor market to automation and weaken the resulting produc- tivity gains from this transformation: a mismatch between the skill requirements of new technologies, and the possibility that automation is being introduced at an excessive rate, possibly at the expense of other productivity-enhancing technologies.

Suggested Citation

  • Daron Acemoglu & Pascual Restrepo, 2018. "Artificial Intelligence, Automation and Work," Boston University - Department of Economics - The Institute for Economic Development Working Papers Series dp-298, Boston University - Department of Economics.
    • Handle: RePEc:bos:iedwpr:dp-298
    as

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    File URL: http://www.bu.edu/econ/files/2012/11/Artificial-Intelligence-Automation-and-Work.pdf
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    References listed on IDEAS

    as
    1. Robert J. Gordon, 2016. "The Rise and Fall of American Growth: The U.S. Standard of Living since the Civil War," Economics Books, Princeton University Press, edition 1, number 10544.
    2. Nicholas Bloom & Charles I. Jones & John Van Reenen & Michael Webb, 2020. "Are Ideas Getting Harder to Find?," American Economic Review, American Economic Association, vol. 110(4), pages 1104-1144, April.
    3. Olmstead, Alan L. & Rhode, Paul W., 2001. "Reshaping The Landscape: The Impact And Diffusion Of The Tractor In American Agriculture, 1910–1960," The Journal of Economic History, Cambridge University Press, vol. 61(3), pages 663-698, September.
    4. Chad Syverson, 2017. "Challenges to Mismeasurement Explanations for the US Productivity Slowdown," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 165-186, Spring.
    5. Rodolfo E. Manuelli & Ananth Seshadri, 2014. "Frictionless Technology Diffusion: The Case of Tractors," American Economic Review, American Economic Association, vol. 104(4), pages 1368-1391, April.
    6. David H. Autor & David Dorn & Gordon H. Hanson, 2013. "The China Syndrome: Local Labor Market Effects of Import Competition in the United States," American Economic Review, American Economic Association, vol. 103(6), pages 2121-2168, October.
    7. Georg Graetz & Guy Michaels, 2018. "Robots at Work," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 753-768, December.
    8. Daron Acemoglu & Pascual Restrepo, 2017. "Robots and Jobs: Evidence from US Labor Markets," Boston University - Department of Economics - Working Papers Series dp-297, Boston University - Department of Economics.
    9. Philippe Aghion & Benjamin F. Jones & Charles I. Jones, 2018. "Artificial Intelligence and Economic Growth," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 237-282, National Bureau of Economic Research, Inc.
    10. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue Nov.
    11. Daron Acemoglu & David Autor & David Dorn & Gordon H. Hanson & Brendan Price, 2014. "Return of the Solow Paradox? IT, Productivity, and Employment in US Manufacturing," American Economic Review, American Economic Association, vol. 104(5), pages 394-399, May.
    12. Daron Acemoglu & Pascual Restrepo, 2020. "Robots and Jobs: Evidence from US Labor Markets," Journal of Political Economy, University of Chicago Press, vol. 128(6), pages 2188-2244.
    13. Berthold Herrendorf & Richard Rogerson & ?kos Valentinyi, 2013. "Two Perspectives on Preferences and Structural Transformation," American Economic Review, American Economic Association, vol. 103(7), pages 2752-2789, December.
    14. Daron Acemoglu & Pascual Restrepo, 2016. "The Race Between Machine and Man: Implications of Technology for Growth, Factor Shares and Employment," NBER Working Papers 22252, National Bureau of Economic Research, Inc.
    15. 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.
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    More about this item

    Keywords

    AI; automation; displacement effect; labor demand; inequality; productivity; tasks; technology; wages;
    All these keywords.

    JEL classification:

    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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