Periodic Reporting for period 2 - iManage (Rethinking Employment Law for a world of Algorithmic Management)
Reporting period: 2022-10-01 to 2024-03-31
Amidst important debates about the gig economy and the automation of jobs, employment law has paid scant attention to the rise of algorithmic management: the increasingly pervasive reliance on monitoring technology and sophisticated algorithms to measure, control, and sanction workers. This poses a fundamental threat to the legal regulation of our labour markets. Automated management allows the exercise of hitherto impossibly granular employer control. At the same time, however, the absence of clear decisions and traditional management structures appears to disperse responsibility ‘into the cloud’.
How can employment law respond to a world in which automation has not replaced workers—but their bosses?
iMANAGE develops the first systematic account of the challenges and potential of algorithmic management, examines its implications for legal regulation, and develops concrete solutions to avoid harmful path-dependencies: our recently published Blueprint for Regulating Algorithmic management offers concrete solutions in legal and broader economic regulation to ensure both innovation facilitation and the protection of fundamental rights and decent working standards.
How can employment law respond to a world in which automation has not replaced workers—but their bosses?
iMANAGE develops the first systematic account of the challenges and potential of algorithmic management, examines its implications for legal regulation, and develops concrete solutions to avoid harmful path-dependencies: our recently published Blueprint for Regulating Algorithmic management offers concrete solutions in legal and broader economic regulation to ensure both innovation facilitation and the protection of fundamental rights and decent working standards.
The central effort of the team thus far has been in WP1, focusing on identifying the key challenges for algorithmic management - and developing responses to them. This has resulted in a blueprint for regulation, suggesting eight specific strategies to tackle the regulatory gaps identified (increased privacy harms, and the demise of managerial agency). In order to explore these conclusions, and international comparative conference was organised in the early summer of 2022, followed by a comparative workshop exploring the draft blueprint with policy makers from the United States (EEOC) and Europe (including MEPs and representatives of the European Commission).
WP2 and WP3 have focused on algorithmic discrimination and data protection, respectively, focusing on the implications of the results of WP1 in specific regulatory domains and across the laws of different Member States. Progress on WP4 has involved work with key stakeholders from the public sector (domestically and internationally), as well as the social partners.
WP2 and WP3 have focused on algorithmic discrimination and data protection, respectively, focusing on the implications of the results of WP1 in specific regulatory domains and across the laws of different Member States. Progress on WP4 has involved work with key stakeholders from the public sector (domestically and internationally), as well as the social partners.
WP1: state-of-the-art debates in law have mostly been focused on detecting and discussing the problems arising from algorithmic management. iManage' regulatory blueprint takes a significant step beyond these diagnoses, presenting concrete solutions which are already influencing policy-making in the EU (see e.g. ongoing discussions of Chapter III of the proposed Platform Work Directive).
WP2: the existing literature has argued near-exclusively that indirect discrimination is the most appropriate lens through which algorithmic discrimination should be analysed. "Directly Discriminatory Algorithms' (MLR 2023) is the first paper to argue that this focus is unduly narrow, and that the law on direct discrimination could apply to at least some algorithmic practices instead.
WP3: whilst Art 88 GDPR has long offered Member States the possibility to lay down more specific provisions in the context of employment, there has been no comprehensive study of its implementation across the Member States, as now performed (and published) by PDR Dr Halefom Abraha.
WP2: the existing literature has argued near-exclusively that indirect discrimination is the most appropriate lens through which algorithmic discrimination should be analysed. "Directly Discriminatory Algorithms' (MLR 2023) is the first paper to argue that this focus is unduly narrow, and that the law on direct discrimination could apply to at least some algorithmic practices instead.
WP3: whilst Art 88 GDPR has long offered Member States the possibility to lay down more specific provisions in the context of employment, there has been no comprehensive study of its implementation across the Member States, as now performed (and published) by PDR Dr Halefom Abraha.