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Computers and populism: artificial intelligence, jobs, and politics in the near term

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  • Frank Levy

Abstract

I project the near-term future of work to ask whether job losses induced by artificial intelligence will increase the appeal of populist politics. The paper first explains how computers and machine learning automate workplace tasks. Automated tasks help to both create and eliminate jobs and I show why job elimination centres in blue-collar and clerical work—impacts similar to those of manufactured imports and offshored services. I sketch the near-term evolution of three technologies aimed at blue-collar and clerical occupations: autonomous long-distance trucks, automated customer service responses, and industrial robotics. I estimate that in the next 5–7 years, the jobs lost to each of these technologies will be modest but visible. I then outline the structure of populist politics. Populist surges are rare but a populist candidate who pits ‘the people’ (truck drivers, call centre operators, factory operatives) against ‘the elite’ (software developers, etc.) will be mining many of the US regional and education fault lines that were part of the 2016 presidential election.

Suggested Citation

  • Frank Levy, 2018. "Computers and populism: artificial intelligence, jobs, and politics in the near term," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 34(3), pages 393-417.
    • Handle: RePEc:oup:oxford:v:34:y:2018:i:3:p:393-417.
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    File URL: http://hdl.handle.net/10.1093/oxrep/gry004
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    Citations

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    Cited by:

    1. Guarascio, Dario & Sacchi, Stefano, 2021. "Technology, risk and social policy. An empirical investigation," GLO Discussion Paper Series 833, Global Labor Organization (GLO).
    2. Julia Bock-Schappelwein & Klaus Friesenbichler, 2019. "Auswirkungen der Digitalisierung auf die Beschäftigung nach Tätigkeitsschwerpunkten in Österreich. Ergebnisse auf Grundlage der unselbständigen Beschäftigung," WIFO Monatsberichte (monthly reports), WIFO, vol. 92(9), pages 697-705, September.
    3. Julia Bock-Schappelwein & Andrea Egger, 2023. "Arbeitsmarkt 2030. Rückschlüsse für Österreich," WIFO Studies, WIFO, number 71172.
    4. Genz, Sabrina & Schnabel, Claus, 2021. "Digging into the Digital Divide: Workers' Exposure to Digitalization and Its Consequences for Individual Employment," IZA Discussion Papers 14649, Institute of Labor Economics (IZA).
    5. Hunt, Wil & Sarkar, Sudipa & Warhurst, Chris, 2022. "Measuring the impact of AI on jobs at the organization level: Lessons from a survey of UK business leaders," Research Policy, Elsevier, vol. 51(2).
    6. Wu, Bangzheng & Yang, Weiguo, 2022. "Empirical test of the impact of the digital economy on China's employment structure," Finance Research Letters, Elsevier, vol. 49(C).
    7. Tubadji, Annie & Huang, Haoran & Webber, Don J, 2021. "Cultural proximity bias in AI-acceptability: The importance of being human," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    8. Jingyi Qin & Qingyu Xu, 2024. "The Impact of the Digital Economy on Population Dividends in China: Based on the Dual Perspective of Quantity and Quality," Sustainability, MDPI, vol. 16(10), pages 1-23, May.
    9. Holzer, Harry J., 2019. "The US Labor Market in 2050: Supply, Demand and Policies to Improve Outcomes," IZA Policy Papers 148, Institute of Labor Economics (IZA).

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