Ansattprofil

Guy Davidov

Professor

Institutt for rettsvitenskap og styring

Bilde av Guy Davidov

Biografi

Guy Davidov is Professor in Law at the Department of Law and Governance. He was the founder and first Chair of the Labour Law Research Network (2011-2015), and Editor-in-Chief of the International Journal of Comparative Labour Law and Industrial Relations (2015-2020). His book A Purposive Approach to Labour Law was published by Oxford University Press in 2016. He has also co-edited Boundaries and Frontiers of Labour Law (with Langille, 2006), The Idea of Labour Law (with Langille, 2011), and the Oxford Handbook of the Law of Work (with Langille and Lester, 2024). His articles appeared in the Oxford Journal of Legal Studies, Modern Law Review, University of Toronto Law Journal, Law & Social Inquiry, McGill Law Journal, as well as multiple times in the top work law journals, including the Industrial Law Journal, Comparative Labour Law & Policy Journal, Berkeley Journal of Employment & Labor Law and more. His work has been cited with approval by the Supreme Courts in four countries: the UK (in the important Uber case), Canada, Israel and Jamaica.

Ekspertområder

Publikasjoner

Davidov, Guy (2024)

Using AI to Mitigate the Employee Misclassification Problem

Modern law review, 88(2) , s. 267-299. Doi: https://doi.org/10.1111/1468-2230.12919

Misclassification of employees as independent contractors is widespread. This article aims to make two contributions. My first goal is to sharpen the explanation of why misclassifications persist; I argue that three well‐known problems – the indeterminacy of employee status tests, the barriers to self‐enforcement, and the inequality of bargaining power – together combine to give employers de facto power to set the default legal status. Putting the burden on the worker to initiate legal proceedings and challenge their classification as an independent contractor is the ultimate reason for persistent misclassifications. The second and main contribution is to propose a solution that relies on new AI capabilities. Thanks to technological advancements it is now possible to require employers to seek pre‐authorisation before engaging with someone as an independent contractor. The authorisation would be granted (or refused) by a state‐run automated system, based on an AI prediction about the law. Both parties would still be able to bring the case before a court of law; but the power to set the default legal status would be taken away from employers. The article considers the difficulties with relying on AI predictions, and argues that those difficulties can be addressed, proposing a model that can be justified.

Akademisk grad
År Akademisk institusjon Grad
2002 University of Toronto Doctor of Laws
1998 University of Toronto Master of Laws
1996 Tel Aviv University Bachelor of Laws