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Artificial Intelligence and Workers' Well-Being

Author

Listed:
  • Giuntella, Osea

    (University of Pittsburgh)

  • König, Johannes

    (DIW Berlin)

  • Stella, Luca

    (University of Milan)

Abstract

This study explores the relationship between artificial intelligence (AI) and workers' well-being and mental health using longitudinal survey data from Germany (2000-2020). We construct a measure of individual exposure to AI technology based on the occupation in which workers in our sample were first employed and explore an event study design and a difference-in-differences approach to compare AI-exposed and non-exposed workers. Before AI became widely available, there is no evidence of differential pre-trends in workers' well-being and concerns about their economic futures. Since 2015, however, with the increasing adoption of AI in firms across Germany, we find that AI-exposed workers have become less satisfied with their life and job and more concerned about job security and their personal economic situation. However, we find no evidence of a significant impact of AI on workers' mental health, anxiety, or depression.

Suggested Citation

  • Giuntella, Osea & König, Johannes & Stella, Luca, 2023. "Artificial Intelligence and Workers' Well-Being," IZA Discussion Papers 16485, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp16485
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    References listed on IDEAS

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    1. Gihleb, Rania & Giuntella, Osea & Stella, Luca & Wang, Tianyi, 2022. "Industrial robots, Workers’ safety, and health," Labour Economics, Elsevier, vol. 78(C).
    2. O'Brien, Rourke & Bair, Elizabeth F. & Venkataramani, Atheendar S., 2022. "Death by Robots? Automation and Working-Age Mortality in the United States," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 59(2), pages 607-628.
    3. Sarah Bankins & Paul Formosa & Yannick Griep & Deborah Richards, 2022. "AI Decision Making with Dignity? Contrasting Workers’ Justice Perceptions of Human and AI Decision Making in a Human Resource Management Context," Information Systems Frontiers, Springer, vol. 24(3), pages 857-875, June.
    4. Sybrand Brekelmans & Georgios Petropoulos, 2020. "Occupational change, artificial intelligence and the geography of EU labour markets," Working Papers 37146, Bruegel.
    5. Massimo Anelli & Osea Giuntella & Luca Stella, 2024. "Robots, Marriageable Men, Family, and Fertility," Journal of Human Resources, University of Wisconsin Press, vol. 59(2), pages 443-469.
    6. Ajay K. Agrawal & Joshua S. Gans & Avi Goldfarb, 2023. "The Turing Transformation: Artificial Intelligence, Intelligence Augmentation, and Skill Premiums," NBER Working Papers 31767, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Grimm, Felix, 2024. "Digital Technologies, Job Quality and Employer-provided Training," VfS Annual Conference 2024 (Berlin): Upcoming Labor Market Challenges 302402, Verein für Socialpolitik / German Economic Association.

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    More about this item

    Keywords

    artificial intelligence; future of work; well-being; mental health;
    All these keywords.

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • J28 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Safety; Job Satisfaction; Related Public Policy
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General

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