IDEAS home Printed from https://ideas.repec.org/p/zbw/glodps/71.html
   My bibliography  Save this paper

Who Are Afraid of Losing Their Jobs to Artificial Intelligence and Robots? Evidence from a Survey

Author

Listed:
  • Morikawa, Masayuki

Abstract

This study, using original survey data of 10,000 individuals, analyzes the possible impacts of artificial intelligence (AI) and robotics on employment. The first interest of this study is to ascertain, from the viewpoint of workers, what types of worker characteristics are associated with the perception of risk of jobs being replaced by the development of AI and robotics. The second interest is to identify, from the viewpoint of consumers, what types of services are likely to be replaced by AI and robotics. The results suggest that malleable/adaptable high skills acquired through higher education, particularly in science and engineering, are complementary with new technologies such as AI and robotics. At the same time, occupation-specific skills acquired by attending professional schools or holding occupational licenses, particularly those related to human-intensive services, are less likely to be replaced by AI and robotics.

Suggested Citation

  • Morikawa, Masayuki, 2017. "Who Are Afraid of Losing Their Jobs to Artificial Intelligence and Robots? Evidence from a Survey," GLO Discussion Paper Series 71, Global Labor Organization (GLO).
  • Handle: RePEc:zbw:glodps:71
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/158005/1/GLO_DP_0071.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Winters, John V., 2014. "STEM graduates, human capital externalities, and wages in the U.S," Regional Science and Urban Economics, Elsevier, vol. 48(C), pages 190-198.
    2. Alan B. Krueger, 1993. "How Computers Have Changed the Wage Structure: Evidence from Microdata, 1984–1989," The Quarterly Journal of Economics, Oxford University Press, vol. 108(1), pages 33-60.
    3. Eric A. Hanushek & Guido Schwerdt & Ludger Woessmann & Lei Zhang, 2017. "General Education, Vocational Education, and Labor-Market Outcomes over the Lifecycle," Journal of Human Resources, University of Wisconsin Press, vol. 52(1), pages 48-87.
    4. Van Reenen, John, 2011. "Wage inequality, technology and trade: 21st century evidence," Labour Economics, Elsevier, vol. 18(6), pages 730-741.
    5. Timothy F. Bresnahan & Erik Brynjolfsson & Lorin M. Hitt, 2002. "Information Technology, Workplace Organization, and the Demand for Skilled Labor: Firm-Level Evidence," The Quarterly Journal of Economics, Oxford University Press, vol. 117(1), pages 339-376.
    6. Maarten Goos & Alan Manning, 2007. "Lousy and Lovely Jobs: The Rising Polarization of Work in Britain," The Review of Economics and Statistics, MIT Press, vol. 89(1), pages 118-133, February.
    7. Lechevalier, Sébastien & Nishimura, Junichi & Storz, Cornelia, 2014. "Diversity in patterns of industry evolution: How an intrapreneurial regime contributed to the emergence of the service robot industry," Research Policy, Elsevier, vol. 43(10), pages 1716-1729.
    8. Dirk Krueger & Krishna B. Kumar, 2004. "Skill-Specific rather than General Education: A Reason for US--Europe Growth Differences?," Journal of Economic Growth, Springer, vol. 9(2), pages 167-207, June.
    9. 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.
    10. David H. Autor, 2015. "Why Are There Still So Many Jobs? The History and Future of Workplace Automation," Journal of Economic Perspectives, American Economic Association, vol. 29(3), pages 3-30, Summer.
    11. Maarten Goos & Alan Manning & Anna Salomons, 2014. "Explaining Job Polarization: Routine-Biased Technological Change and Offshoring," American Economic Review, American Economic Association, vol. 104(8), pages 2509-2526, August.
    12. Benjamin David, 2017. "Computer technology and probable job destructions in Japan: An evaluation," Post-Print hal-01549790, HAL.
    13. Giorgio Brunello & Lorenzo Rocco, 2017. "The Labor Market Effects of Academic and Vocational Education over the Life Cycle: Evidence Based on a British Cohort," Journal of Human Capital, University of Chicago Press, vol. 11(1), pages 106-166.
    14. Giovanni Peri & Kevin Shih & Chad Sparber, 2016. "STEM Workers, H-1B Visas, and Productivity in US Cities," World Scientific Book Chapters, in: The Economics of International Migration, chapter 9, pages 277-307, World Scientific Publishing Co. Pte. Ltd..
    15. Joel Mokyr & Chris Vickers & Nicolas L. Ziebarth, 2015. "The History of Technological Anxiety and the Future of Economic Growth: Is This Time Different?," Journal of Economic Perspectives, American Economic Association, vol. 29(3), pages 31-50, Summer.
    16. David, Benjamin, 2017. "Computer technology and probable job destructions in Japan: An evaluation," Journal of the Japanese and International Economies, Elsevier, vol. 43(C), pages 77-87.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. HAMAGUCHI Nobuaki & KONDO Keisuke, 2018. "Regional Employment and Artificial Intelligence in Japan," Discussion papers 18032, Research Institute of Economy, Trade and Industry (RIETI).

    More about this item

    Keywords

    artificial intelligence; robotics; skill; household production;

    JEL classification:

    • 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
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis

    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:zbw:glodps:71. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (ZBW - Leibniz Information Centre for Economics). General contact details of provider: http://edirc.repec.org/data/glaboea.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.