Watching the worker – How Workplace surveillance and Algorithmic Management undermine Productivity and Employee Privacy

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Authors: Subiksha Merin
Cited by: 0

Abstract

This article examines the growing use of workplace surveillance and algorithmic management systems and their implications for employee privacy, fairness, and productivity. It argues that continuous digital monitoring-through tools such as biometric tracking, keystroke logging, and AI-driven performance evaluation-does not enhance productivity as commonly assumed but instead generates stress, erodes trust, and incentivizes superficial performance metrics. The article further critiques algorithmic management for its opacity, bias, and inability to account for the contextual realities of human labour, which can lead to discriminatory outcomes and unchallengeable workplace decisions. Drawing comparative insights from the European Union's regulatory approach under the EU AI Act, the article highlights the need for stronger legal safeguards, transparency obligations, and meaningful human oversight in employment-related automated systems. It concludes that sustainable productivity and lawful workplace governance require re-centering human judgment, accountability, and employee privacy in increasingly data-driven workplaces.

Fields of Study & Subjects

Legal and Labor Studies Ethics and Social Impacts of AI Digitalization Law and Regulation

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
9 March 2026
Language
EN