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Generative AI and jobs a global analysis of potential effects on job quantity and quality

Author

Listed:
  • Gmyrek, Pawel,
  • Berg, Janine,
  • Bescond, David,

Abstract

This study assesses the potential global exposure of occupations to Generative AI, particularly GPT-4. It predicts that the overwhelming effect of the technology will be to augment occupations, rather than to automate them. The greatest impact is likely to be in high and upper-middle income countries due to a higher share of employment in clerical occupations. As clerical jobs are an important source of female employment, the effects are highly gendered. Insights from this study underline the need for proactive policies that focus on job quality, ensure fair transitions, and that are based on dialogue and adequate regulation.

Suggested Citation

  • Gmyrek, Pawel, & Berg, Janine, & Bescond, David,, 2023. "Generative AI and jobs a global analysis of potential effects on job quantity and quality," ILO Working Papers 995324892702676, International Labour Organization.
    • Handle: RePEc:ilo:ilowps:995324892702676
    DOI: 10.54394/FHEM8239
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    Citations

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    Cited by:

    1. Becker, Dominik & Deck, Luca & Feulner, Simon & Gutheil, Niklas & Schüll, Moritz & Decker, Stefan & Eymann, Torsten & Gimpel, Henner & Pippow, Andreas & Röglinger, Maximilian & Urbach, Nils, 2024. "Lohnt sich Microsoft 365 Copilot? Eine Potenzialanalyse für Unternehmen und Bildungseinrichtungen," Bayreuth Reports on Information Systems Management 72, University of Bayreuth, Chair of Information Systems Management.
    2. Albanesi, Stefania & Da Silva, António Dias & Jimeno, Juan F. & Lamo, Ana & Wabitsch, Alena, 2023. "New technologies and jobs in Europe," Working Paper Series 2831, European Central Bank.
    3. Engberg, Erik & Görg, Holger & Lodefalk, Magnus & Javed, Farrukh & Längkvist, Martin & Monteiro, Natália & Kyvik Nordås, Hildegunn & Pulito, Giuseppe & Schroeder, Sarah & Tang, Aili, 2023. "AI Unboxed and Jobs: A Novel Measure and Firm-Level Evidence from Three Countries," Ratio Working Papers 370, The Ratio Institute.
    4. Enrico Maria Fenoaltea & Dario Mazzilli & Aurelio Patelli & Angelica Sbardella & Andrea Tacchella & Andrea Zaccaria & Marco Trombetti & Luciano Pietronero, 2024. "Follow the money: a startup-based measure of AI exposure across occupations, industries and regions," Papers 2412.04924, arXiv.org, revised Dec 2024.
    5. Abigail Barr & Anna Hochleitner & Silvia Sonderegger, 2023. "Does increasing inequality threaten social stability? Evidence from the lab," Discussion Papers 2023-13, The Centre for Decision Research and Experimental Economics, School of Economics, University of Nottingham.
    6. Ernst Ekkehard & Feist Lisa, 2024. "Tomorrow at Work: The Age of Shortages," Intereconomics: Review of European Economic Policy, Sciendo, vol. 59(3), pages 125-131.
    7. Bachmann, Ronald & Gonschor, Myrielle & Milasi, Santo & Mitra, Alessio, 2023. "Technological progress and the dynamics of self-employment: Worker-level evidence for Europe," Ruhr Economic Papers 1023, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    8. Jing Wang & Zhanggong Tian & Yi Sun, 2024. "Digital Economy, Employment Structure and Labor Share," Sustainability, MDPI, vol. 16(21), pages 1-16, November.
    9. Àlena V. Vankevich & Iryna N. Kalinouskaya, 2024. "Digitalisation and jobs: The case of organisations in the Vitebsk area of Belarus," Journal of New Economy, Ural State University of Economics, vol. 25(4), pages 106-126, December.
    10. Mourelatos, Evangelos & Zervas, Panagiotis & Lagios, Dimitris & Tzimas, Giannis, 2024. "Can AI Bridge the Gender Gap in Competitiveness?," GLO Discussion Paper Series 1404, Global Labor Organization (GLO).
    11. Pawel Gmyrek & Hernan Winkler & Santiago Garganta, 2024. "Buffer or Bottleneck? Employment Exposure to Generative AI and the Digital Divide in Latin America," CEDLAS, Working Papers 0340, CEDLAS, Universidad Nacional de La Plata.

    More about this item

    Keywords

    artificial intelligence; employment opportunity; working conditions; women workers; access to information technology; impact evaluation;
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