Algorithmic Subordination as a Novel Criterion for Determining Employee Status in the Context of Atypical Forms of Employment

This article advances the thesis that algorithmic subordination should operate as a legally cognisable indicator of employment status within European labour law. Building upon the Court of Justice’s autonomous concept of the “worker” and the Union legislature’s recent intervention in Directive (EU) 2024/2831 of 23 October 2024 on improving working conditions in platform work (OJ L 2024/2831, hereinafter referred to as: “the Directive”), the argument proceeds in three steps. First, it reconstructs subordination as a functional criterion that can be revealed through digital control measures, in particular the allocation of tasks, monitoring, price setting, evaluation and deactivation effected by algorithms. Secondly, it examines how this control reconfigures both sides of the personal work relation, by sharpening tests for employee status and by pressing toward a re‑specification of the employer concept, including scenarios of joint or indirect employer responsibility. Thirdly, it draws on Member State practice, notably Spain and Italy, to show how rebuttable presumptions, transparency obligations and data‑protection enforcement can be linedup to evidence and to constrain algorithmic power in the workplace. The article concludes that algorithmic subordination, when bounded by appropriate procedural and substantive safeguards, warrants recognition as a criterion for classifying work performed in atypical arrangements as employment. It recommends legislative and judicial techniques to ensure the effective implementation of Directive (EU) 2024/2831, while preserving the distinction between genuine self‑employment and employment.

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Publication Details

Journal
Studia z Zakresu Prawa Pracy i Polityki Społecznej
Published
2026-02-26
DOI
https://doi.org/10.4467/25444654spp.26.002.23178
Primary Topic
Digital Economy and Work Transformation
Type
article
Field-Weighted Citation Impact
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article

Algorithmic Subordination as a Novel Criterion for Determining Employee Status in the Context of Atypical Forms of Employment

Monika Tomaszewska
Studia z Zakresu Prawa Pracy i Polityki Społecznej
Digital Economy and Work Transformation
article

Algorithmic Subordination as a Novel Criterion for Determining Employee Status in the Context of Atypical Forms of Employment

Monika Tomaszewska
article en

Abstract

This article advances the thesis that algorithmic subordination should operate as a legally cognisable indicator of employment status within European labour law. Building upon the Court of Justice’s autonomous concept of the “worker” and the Union legislature’s recent intervention in Directive (EU) 2024/2831 of 23 October 2024 on improving working conditions in platform work (OJ L 2024/2831, hereinafter referred to as: “the Directive”), the argument proceeds in three steps. First, it reconstructs subordination as a functional criterion that can be revealed through digital control measures, in particular the allocation of tasks, monitoring, price setting, evaluation and deactivation effected by algorithms. Secondly, it examines how this control reconfigures both sides of the personal work relation, by sharpening tests for employee status and by pressing toward a re‑specification of the employer concept, including scenarios of joint or indirect employer responsibility. Thirdly, it draws on Member State practice, notably Spain and Italy, to show how rebuttable presumptions, transparency obligations and data‑protection enforcement can be linedup to evidence and to constrain algorithmic power in the workplace. The article concludes that algorithmic subordination, when bounded by appropriate procedural and substantive safeguards, warrants recognition as a criterion for classifying work performed in atypical arrangements as employment. It recommends legislative and judicial techniques to ensure the effective implementation of Directive (EU) 2024/2831, while preserving the distinction between genuine self‑employment and employment.

Studia z Zakresu Prawa Pracy i Polityki SpołecznejVol. 33(1)
University of Gdańsk (PL)
Decent work and economic growth
Openalex Percentile: Top 47%
Digital Economy and Work Transformation
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