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Behind the headline number: Why not to rely on Frey and Osborne’s predictions of potential job loss from automation

Author

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  • Michael Coelli

    (Department of Economics, The University of Melbourne)

  • Jeff Borland

    (Department of Economics, The University of Melbourne)

Abstract

We review a highly influential study that estimated potential job loss from advances in Artificial Intelligence and robotics: Frey and Osborne (FO) (2013, 2017) concluded that 47 per cent of jobs in the United States were at ‘high risk’ of automation in the next 10 to 20 years. First, we investigate FO’s methodology for estimating job loss. Several major problems and limitations are revealed; especially associated with the subjective designation of occupations as fully automatable. Second, we examine whether FO’s predictions can explain occupation-level changes in employment in the United States from 2013 to 2018. Compared to standard approaches which classify jobs based on their intensity in routine tasks, FO’s predictions do not ‘add value’ for forecasting the impact of technology on employment.

Suggested Citation

  • Michael Coelli & Jeff Borland, 2019. "Behind the headline number: Why not to rely on Frey and Osborne’s predictions of potential job loss from automation," Melbourne Institute Working Paper Series wp2019n10, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    • Handle: RePEc:iae:iaewps:wp2019n10
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    References listed on IDEAS

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    Cited by:

    1. Foster-McGregor, Neil & Nomaler, Önder & Verspagen, Bart, 2021. "Job Automation Risk, Economic Structure and Trade: a European Perspective," Research Policy, Elsevier, vol. 50(7).
    2. Turja, Tuuli & Särkikoski, Tuomo & Koistinen, Pertti & Krutova, Oxana & Melin, Harri, 2024. "Job well robotized! – Maintaining task diversity and well-being in managing technological changes," European Management Journal, Elsevier, vol. 42(1), pages 67-75.
    3. Heluo, Yuxi & Fabel, Oliver, 2024. "Job computerization, occupational employment and wages: A comparative study of the United States, Germany, and Japan," Technological Forecasting and Social Change, Elsevier, vol. 209(C).
    4. Jeff Borland & Michael Coelli, 2023. "The Australian labour market and IT-enabled technological change," Melbourne Institute Working Paper Series wp2023n01, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    5. Melián-González, Santiago & Bulchand-Gidumal, Jacques, 2025. "A framework for research on the automation of work," Technological Forecasting and Social Change, Elsevier, vol. 215(C).
    6. Långstedt, Johnny & Spohr, Jonas & Hellström, Magnus, 2023. "Are our values becoming more fit for artificial intelligence society? A longitudinal study of occupational values and occupational susceptibility to technological substitution," Technology in Society, Elsevier, vol. 72(C).

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    JEL classification:

    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • 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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