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Mirror, Mirror on the Wall: Which Jobs Will AI Replace After All?: A New Index of Occupational Exposure

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  • Benítez, Miguel
  • Parrado, Eric

Abstract

This paper introduces the AI Generated Index of Occupational Exposure (GENOE), a novel measure quantifying the potential impact of artificial intelligence on occupations and their associated tasks. Our methodology employs synthetic AI surveys, leveraging large language models to conduct expert-like assessments. This approach allows for a more comprehensive evaluation of job replacement likelihood, minimizing human bias and reducing assumptions about the mechanisms through which AI innovations could replace job tasks and skills. The index not only considers task automation, but also contextual factors such as social and ethical considerations and regulatory constraints that may affect the likelihood of replacement. Our findings indicate that the average likelihood of job replacement is estimated at 0.28 in the next year, increasing to 0.38 and 0.44 over the next five and ten years, respectively. To validate our methodology, we successfully replicate other measures of occupational exposure that rely on human expert assessments, substituting these with AI-based evaluations. The GENOE index provides valuable insights for policymakers, employers, and workers, offering a data-driven foundation for strategic workforce planning and adaptation in the face of rapid technological change.

Suggested Citation

  • Benítez, Miguel & Parrado, Eric, 2024. "Mirror, Mirror on the Wall: Which Jobs Will AI Replace After All?: A New Index of Occupational Exposure," IDB Publications (Working Papers) 13696, Inter-American Development Bank.
  • Handle: RePEc:idb:brikps:13696
    DOI: http://dx.doi.org/10.18235/0013125
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    References listed on IDEAS

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    1. Daron Acemoglu & Pascual Restrepo, 2022. "Tasks, Automation, and the Rise in U.S. Wage Inequality," Econometrica, Econometric Society, vol. 90(5), pages 1973-2016, September.
    2. Daron Acemoglu & David Autor & Jonathon Hazell & Pascual Restrepo, 2022. "Artificial Intelligence and Jobs: Evidence from Online Vacancies," Journal of Labor Economics, University of Chicago Press, vol. 40(S1), pages 293-340.
    3. David H. Autor & David Dorn, 2013. "The Growth of Low-Skill Service Jobs and the Polarization of the US Labor Market," American Economic Review, American Economic Association, vol. 103(5), pages 1553-1597, August.
    4. 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.
    5. Fossen, Frank M. & Sorgner, Alina, 2021. "Digitalization of work and entry into entrepreneurship," Journal of Business Research, Elsevier, vol. 125(C), pages 548-563.
    6. David H. Autor & Lawrence F. Katz & Melissa S. Kearney, 2006. "The Polarization of the U.S. Labor Market," American Economic Review, American Economic Association, vol. 96(2), pages 189-194, May.
    7. Edward Felten & Manav Raj & Robert Seamans, 2021. "Occupational, industry, and geographic exposure to artificial intelligence: A novel dataset and its potential uses," Strategic Management Journal, Wiley Blackwell, vol. 42(12), pages 2195-2217, December.
    8. Erik Brynjolfsson & Tom Mitchell & Daniel Rock, 2018. "What Can Machines Learn, and What Does It Mean for Occupations and the Economy?," AEA Papers and Proceedings, American Economic Association, vol. 108, pages 43-47, May.
    9. Acemoglu, Daron & Autor, David, 2011. "Skills, Tasks and Technologies: Implications for Employment and Earnings," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 12, pages 1043-1171, Elsevier.
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    Cited by:

    1. Egana-delSol, Pablo & Bravo-Ortega, Claudio, 2025. "Artificial Intelligence and Labor Market Transformations in Latin America," IZA Discussion Papers 17746, Institute of Labor Economics (IZA).

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    More about this item

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • 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
    • 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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