Collins, P. and Atkinson, J. orcid.org/0000-0001-5207-2231 (2023) Worker voice and algorithmic management in post-Brexit Britain. Transfer: European Review of Labour and Research, 29 (1). pp. 37-52. ISSN 1024-2589
Abstract
In this article, we consider the legal frameworks that enable workers to influence the deployment of new workplace technologies in the United Kingdom and the future of worker voice and algorithmic management in a post-Brexit Britain. The article demonstrates how the legal mechanisms that facilitate voice at work, primarily collective bargaining via trade unions, can be leveraged to influence employers’ choices regarding algorithmic management. However, it also identifies both familiar and novel challenges regarding using these routes to ‘negotiate the algorithm’. The article then outlines major regulatory proposals emerging from the EU that would establish greater co-determination in this context and assesses their relevance to the UK labour market. It concludes by considering whether specific regulatory measures are necessary in the UK context to enhance the exercise of worker voice regarding the deployment of algorithmic management and close the widening gap between the position of UK and EU workers.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2023. This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
Keywords: | Labour law; employment rights; worker voice; UK; artificial intelligence; algorithmic management; trade unions; collective bargaining |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > School of Law (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 25 Nov 2022 13:34 |
Last Modified: | 19 Apr 2023 13:48 |
Status: | Published |
Publisher: | SAGE Publications |
Refereed: | Yes |
Identification Number: | 10.1177/10242589221143068 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:193775 |