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Algorithmic management and collective bargaining

Author

Listed:
  • Valerio De Stefano

    (York University, Toronto, Ontario, Canada)

  • Simon Taes

    (Institute for Labour Law of the KU Leuven, Belgium)

Abstract

This article addresses the challenges raised by the introduction of algorithmic management and artificial intelligence in the world of work, focusing on the risks that new managerial technologies present for fundamental rights and principles, such as non-discrimination, freedom of association and the right to privacy. The article argues that collective bargaining is the most suitable regulatory instrument for responding to these challenges, and that current EU legislative initiatives do not adequately recognise the role of collective bargaining in this area. It also maps current initiatives undertaken by national trade union movements in Europe to govern algorithmic management.

Suggested Citation

  • Valerio De Stefano & Simon Taes, 2023. "Algorithmic management and collective bargaining," Transfer: European Review of Labour and Research, , vol. 29(1), pages 21-36, February.
    • Handle: RePEc:sae:treure:v:29:y:2023:i:1:p:21-36
    DOI: 10.1177/10242589221141055
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    References listed on IDEAS

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    1. Virginia Doellgast & Ines Wagner & Sean O’Brady, 2023. "Negotiating limits on algorithmic management in digitalised services: cases from Germany and Norway," Transfer: European Review of Labour and Research, , vol. 29(1), pages 105-120, February.
    2. Philippa Collins & Joe Atkinson, 2023. "Worker voice and algorithmic management in post-Brexit Britain," Transfer: European Review of Labour and Research, , vol. 29(1), pages 37-52, February.
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    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.

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