IDEAS home Printed from https://ideas.repec.org/p/osf/socarx/e37cu.html
   My bibliography  Save this paper

Race, Ethnicity, and the Future of Work

Author

Listed:
  • Moradi, Pegah

Abstract

Leading up to and following the 2016 American presidential election, “White working class” employment and political agency has become particularly salient. A simultaneous discussion on the role of automation in unemployment complicates the political narrative; by one estimate, 47% of American jobs are at risk of computerization (Frey and Osborne, 2013). This study analyzes how occupational automation corresponds with racial and ethnic demographics within occupational groups from both a historical and contemporary perspective. I find that throughout American industrialization, non-White and immigrant workers shifted to low-wage, unskilled work because of the political and social limitations imposed upon these groups. In the context of today’s AI-driven automation, I find that White workers are more heavily affected by automatability than other racial groups. Conversely, however, I found that the proportion of White workers in an occupation is negatively correlated with an occupation’s automatability. I conclude with suggestions for a susceptibility-based approach to predicting employment outcomes from AI-driven automation.

Suggested Citation

  • Moradi, Pegah, 2019. "Race, Ethnicity, and the Future of Work," SocArXiv e37cu, Center for Open Science.
  • Handle: RePEc:osf:socarx:e37cu
    DOI: 10.31219/osf.io/e37cu
    as

    Download full text from publisher

    File URL: https://osf.io/download/5ca258dcecd788001998c0ac/
    Download Restriction: no

    File URL: https://libkey.io/10.31219/osf.io/e37cu?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Borowczyk-Martins, Daniel & Bradley, Jake & Tarasonis, Linas, 2018. "Racial discrimination in the U.S. labor market: Employment and wage differentials by skill," Labour Economics, Elsevier, vol. 50(C), pages 45-66.
    2. 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.
    3. 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.
    4. 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.
    5. David Card & John E. DiNardo, 2002. "Skill-Biased Technological Change and Rising Wage Inequality: Some Problems and Puzzles," Journal of Labor Economics, University of Chicago Press, vol. 20(4), pages 733-783, October.
    6. Carl Benedikt Frey & Thor Berger & Chinchih Chen, 2018. "Political machinery: did robots swing the 2016 US presidential election?," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 34(3), pages 418-442.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Colombo, Emilio & Mercorio, Fabio & Mezzanzanica, Mario, 2019. "AI meets labor market: Exploring the link between automation and skills," Information Economics and Policy, Elsevier, vol. 47(C), pages 27-37.
    2. repec:hal:spmain:info:hdl:2441/7n49nkmngd8448a5ts5gt5ade0 is not listed on IDEAS
    3. Philippe Aghion & Céline Antonin & Simon Bunel, 2019. "Artificial Intelligence, Growth and Employment: The Role of Policy," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 510-511-5, pages 149-164.
    4. Janssen, Simon & Mohrenweiser, Jens, 2018. "The Shelf Life of Incumbent Workers during Accelerating Technological Change: Evidence from a Training Regulation Reform," IZA Discussion Papers 11312, Institute of Labor Economics (IZA).
    5. Lütkenhorst, Wilfried, 2018. "Creating wealth without labour? Emerging contours of a new techno-economic landscape," IDOS Discussion Papers 11/2018, German Institute of Development and Sustainability (IDOS).
    6. Alejandro Micco, 2019. "The Impact of Automation in Developed Countries," Working Papers wp480, University of Chile, Department of Economics.
    7. Goos, Maarten & Rademakers, Emilie & Röttger, Ronja, 2021. "Routine-Biased technical change: Individual-Level evidence from a plant closure," Research Policy, Elsevier, vol. 50(7).
    8. Gries, Thomas & Naudé, Wim, 2022. "Modelling artificial intelligence in economics," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 56, pages 1-12.
    9. Andrea Salvatori & Seetha Menon & Wouter Zwysen, 2018. "The effect of computer use on job quality: Evidence from Europe," OECD Social, Employment and Migration Working Papers 200, OECD Publishing.
    10. Fran Stewart & Kathryn Kelley, 2020. "Connecting Hands and Heads: Retooling Engineering Technology for the “Smart†Manufacturing Workplace," Economic Development Quarterly, , vol. 34(1), pages 31-45, February.
    11. Hémous, David & Dechezleprêtre, Antoine & Olsen, Morten & Zanella, carlo, 2019. "Automating Labor: Evidence from Firm-level Patent Data," CEPR Discussion Papers 14249, C.E.P.R. Discussion Papers.
    12. Kaltenberg, Mary & Foster-McGregor, Neil, 2020. "The impact of automation on inequality across Europe," MERIT Working Papers 2020-009, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    13. Matthias Firgo & Peter Mayerhofer & Michael Peneder & Philipp Piribauer & Peter Reschenhofer, 2018. "Beschäftigungseffekte der Digitalisierung in den Bundesländern sowie in Stadt und Land," WIFO Studies, WIFO, number 61633, June.
    14. Aina Gallego & Thomas Kurer & Nikolas Schöll, 2018. "Not so disruptive after all: How workplace digitalization affects political preferences," Economics Working Papers 1623, Department of Economics and Business, Universitat Pompeu Fabra.
    15. Gaetano Basso & Giovanni Peri & Ahmed S. Rahman, 2020. "Computerization and immigration: Theory and evidence from the United States," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 53(4), pages 1457-1494, November.
    16. Gallipoli, Giovanni & Makridis, Christos A., 2018. "Structural transformation and the rise of information technology," Journal of Monetary Economics, Elsevier, vol. 97(C), pages 91-110.
    17. Timothy F. Slaper, 2019. "Automation and Offshoring in Durable Goods Manufacturing: An Indiana Case Study," Economic Development Quarterly, , vol. 33(1), pages 19-38, February.
    18. Sotiris Blanas & Gino Gancia & Sang Yoon (Tim) Lee, 2019. "Who is afraid of machines?," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 34(100), pages 627-690.
    19. Lorenz, Hanno & Stephany, Fabian, 2018. "Back to the future: Changing job profiles in the digital age," Working Papers 13, Agenda Austria.
    20. Stepan Zemtsov & Vera Barinova & Roza Semenova, 2019. "The Risks of Digitalization and the Adaptation of Regional Labor Markets in Russia," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 13(2), pages 84-96.
    21. Krenz, Astrid & Prettner, Klaus & Strulik, Holger, 2021. "Robots, reshoring, and the lot of low-skilled workers," European Economic Review, Elsevier, vol. 136(C).

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:osf:socarx:e37cu. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: OSF (email available below). General contact details of provider: https://arabixiv.org .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.