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The Covid-19 Pandemic Spurred Growth in Automation: What Does this Mean for Minority Workers?

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Abstract

The Covid-19 pandemic has accelerated trends in automation as many employers seek to save on labor costs amid widespread illness, increased worker leverage, and market pressures to onshore supply chains. While existing research has explored how automation may displace non-specialized jobs, there is typically less attention paid to how this displacement may interact with preexisting structural issues around racial inequality. This analysis updates that of a 2021 Brookings paper by the authors, finding that Black and Hispanic workers continue to be overrepresented in the 30 occupations with the highest estimated risk of automation and underrepresented in the 30 occupations with the lowest estimated risk of automation. The updated analysis also includes new attention to automation’s impact on wage structures, consideration of the broader implications of automation for global economics, and a discussion of the potential interplay of automation with recent developments in artificial intelligence.

Suggested Citation

  • Anthony Barr & Darlene Booth-Bell & Kristen Broady & Ryan Perry, 2023. "The Covid-19 Pandemic Spurred Growth in Automation: What Does this Mean for Minority Workers?," Working Paper Series WP 2023-06, Federal Reserve Bank of Chicago.
    • Handle: RePEc:fip:fedhwp:95732
    DOI: 10.21033/wp-2023-06
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    References listed on IDEAS

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    1. David Autor & Anna Salomons, 2018. "Is Automation Labor-Displacing? Productivity Growth, Employment, and the Labor Share," NBER Working Papers 24871, National Bureau of Economic Research, Inc.
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    3. Mai Dao & Ms. Mitali Das & Zsoka Koczan & Weicheng Lian, 2017. "Why Is Labor Receiving a Smaller Share of Global Income? Theory and Empirical Evidence," IMF Working Papers 2017/169, International Monetary Fund.
    4. Natalia A. Kolesnikova & Yang Liu, 2010. "A bleak 30 years for black men: economic progress was slim in urban America," The Regional Economist, Federal Reserve Bank of St. Louis, issue Jul, pages 4-9.
    5. Frey, Carl Benedikt & Osborne, Michael A., 2017. "The future of employment: How susceptible are jobs to computerisation?," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 254-280.
    6. Sevgi Çoban, 2022. "Gender and telework: Work and family experiences of teleworking professional, middle‐class, married women with children during the Covid‐19 pandemic in Turkey," Gender, Work and Organization, Wiley Blackwell, vol. 29(1), pages 241-255, January.
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    Cited by:

    1. Abeliansky, Ana Lucia & Prettner, Klaus & Stöllinger, Roman, 2023. "Infection Risk at Work, Automatability, and Employment," Department of Economics Working Paper Series 352, WU Vienna University of Economics and Business.

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    JEL classification:

    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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