IDEAS home Printed from https://ideas.repec.org/a/sae/treure/v29y2023i1p71-86.html
   My bibliography  Save this article

Governing the work-related risks of AI: implications for the German government and trade unions

Author

Listed:
  • Anke Hassel

    (Hertie School, Berlin’s University of Governance, Germany)

  • Didem Özkiziltan

    (University of Parma, Italy)

Abstract

This article discusses the risks that artificial intelligence (AI) poses for work. It classifies risks into two types, direct and indirect. Direct risks are AI-induced forms of discrimination, surveillance and information asymmetries at work. Indirect risks are enhanced workplace automation and the increasing ‘fissurisation’ of work. Direct and indirect risks are illustrated using the example of the transport and logistics sector. We discuss policy responses to both types of risk in the context of the German economy and argue that the policy solutions need to differ according to the type of risk. Direct risks can be addressed by European and national regulation against discrimination, surveillance and information asymmetries. As for indirect risks, the first step is to monitor the risks so as to gain an understanding of sector-specific transformations and establish relevant expertise and competence. This way of addressing AI-induced risks at work will help to improve the prospects of decent work, fair remuneration and adequate social protection for all.

Suggested Citation

  • Anke Hassel & Didem Özkiziltan, 2023. "Governing the work-related risks of AI: implications for the German government and trade unions," Transfer: European Review of Labour and Research, , vol. 29(1), pages 71-86, February.
  • Handle: RePEc:sae:treure:v:29:y:2023:i:1:p:71-86
    DOI: 10.1177/10242589221147228
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/10242589221147228
    Download Restriction: no

    File URL: https://libkey.io/10.1177/10242589221147228?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The Skill Content of Recent Technological Change: An Empirical Exploration," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(4), pages 1279-1333.
    2. Ajay Agrawal & Joshua S. Gans & Avi Goldfarb, 2019. "Artificial Intelligence: The Ambiguous Labor Market Impact of Automating Prediction," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 31-50, Spring.
    3. Oscar Molina & Florian Butollo & Csaba Makó & Alejandro Godino & Ursula Holtgrewe & Anna Illsoe & Sander Junte & Trine Pernille Larsen & Miklós Illésy & Jószef Pap & Philip Wotschack, 2023. "It takes two to code: a comparative analysis of collective bargaining and artificial intelligence," Transfer: European Review of Labour and Research, , vol. 29(1), pages 87-104, February.
    4. K. Sabeel Rahman & Kathleen Thelen, 2019. "The Rise of the Platform Business Model and the Transformation of Twenty-First-Century Capitalism," Politics & Society, , vol. 47(2), pages 177-204, June.
    5. Ljubica Nedelkoska & Glenda Quintini, 2018. "Automation, skills use and training," OECD Social, Employment and Migration Working Papers 202, OECD Publishing.
    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. Valerio De Stefano & Virginia Doellgast, 2023. "Introduction to the Transfer special issue. Regulating AI at work: labour relations, automation, and algorithmic management," Transfer: European Review of Labour and Research, , vol. 29(1), pages 9-20, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bürgisser, Reto, 2023. "Policy Responses to Technological Change in the Workplace," SocArXiv kwxn2, Center for Open Science.
    2. Jasmine Mondolo, 2022. "The composite link between technological change and employment: A survey of the literature," Journal of Economic Surveys, Wiley Blackwell, vol. 36(4), pages 1027-1068, September.
    3. Lütkenhorst, Wilfried, 2018. "Creating wealth without labour? Emerging contours of a new techno-economic landscape," IDOS Discussion Papers 11/2018, German Institute of Development and Sustainability (IDOS).
    4. Goos, Maarten & Rademakers, Emilie & Röttger, Ronja, 2021. "Routine-Biased technical change: Individual-Level evidence from a plant closure," Research Policy, Elsevier, vol. 50(7).
    5. Montobbio, Fabio & Staccioli, Jacopo & Virgillito, Maria Enrica & Vivarelli, Marco, 2022. "Robots and the origin of their labour-saving impact," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    6. Kaltenberg, Mary & Foster-McGregor, Neil, 2020. "The impact of automation on inequality across Europe," MERIT Working Papers 2020-009, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    7. Xie, Mengmeng & Ding, Lin & Xia, Yan & Guo, Jianfeng & Pan, Jiaofeng & Wang, Huijuan, 2021. "Does artificial intelligence affect the pattern of skill demand? Evidence from Chinese manufacturing firms," Economic Modelling, Elsevier, vol. 96(C), pages 295-309.
    8. Hensvik, Lena & Skans, Oskar Nordström, 2023. "The skill-specific impact of past and projected occupational decline," Labour Economics, Elsevier, vol. 81(C).
    9. Nii-Aponsah, Hubert, 2022. "Automation exposure and implications in advanced and developing countries across gender, age, and skills," MERIT Working Papers 2022-021, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    10. Enrique Fernandez-Macias & Martina Bisello, 2020. "A Taxonomy of Tasks for Assessing the Impact of New Technologies on Work," JRC Working Papers on Labour, Education and Technology 2020-04, Joint Research Centre.
    11. Tania Babina & Anastassia Fedyk & Alex X. He & James Hodson, 2023. "Firm Investments in Artificial Intelligence Technologies and Changes in Workforce Composition," NBER Chapters, in: Technology, Productivity, and Economic Growth, National Bureau of Economic Research, Inc.
    12. Barbieri, Laura & Mussida, Chiara & Piva, Mariacristina & Vivarelli, Marco, 2019. "Testing the employment and skill impact of new technologies: A survey and some methodological issues," MERIT Working Papers 2019-032, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    13. Ehlert, Martin, 2020. "No Future, No Training? Explaining Cross-national Variation in the Effect of Job Tasks On Training Participation [Keine Zukunft, keine Weiterbildung? Zur Erklärung von Länderunterschieden im Effekt," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 72(S1), pages 483-510.
    14. Wen Zhang & Kee-Hung Lai & Qiguo Gong, 2024. "The future of the labor force: higher cognition and more skills," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-9, December.
    15. Leonardo Bonilla-Mejía & Luz A. Florez & Didier Hermida & Francisco Lasso & Leonardo Fabio Morales & Juan Jose Ospina & José Pulido, 2023. "Is the COVID-19 Pandemic Fast-Tracking Automation in Developing Countries? Evidence from Colombia," Journal of Human Capital, University of Chicago Press, vol. 17(4), pages 593-616.
    16. Kinga Hat & Gernot Stoeglehner, 2020. "Spatial Dimension of the Employment Market Exposition to Digitalisation—The Case of Austria," Sustainability, MDPI, vol. 12(5), pages 1-29, March.
    17. Nikolova, Milena & Cnossen, Femke & Nikolaev, Boris, 2024. "Robots, meaning, and self-determination," Research Policy, Elsevier, vol. 53(5).
    18. Montobbio, F. & Staccioli, J. & Virgillito, M.E. & Vivarelli, Marco, 2022. "The empirics of technology, employment and occupations," MERIT Working Papers 2022-037, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    19. Ljubica Nedelkoska & Frank Neffke, 2019. "Skill Mismatch and Skill Transferability: Review of Concepts and Measurements," Papers in Evolutionary Economic Geography (PEEG) 1921, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Jun 2019.
    20. Egana-delSol, Pablo & Bustelo, Monserrat & Ripani, Laura & Soler, Nicolas & Viollaz, Mariana, 2022. "Automation in Latin America: Are Women at Higher Risk of Losing Their Jobs?," Technological Forecasting and Social Change, Elsevier, vol. 175(C).

    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:sae:treure:v:29:y:2023:i:1:p:71-86. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.