From humans to algorithms: A sociotechnical framework of workplace surveillance

Kayas, OG, Ong, CE and Belal, HM (2025) From humans to algorithms: A sociotechnical framework of workplace surveillance. Digital Business, 5 (2). ISSN 2666-9544

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Abstract

Workplace surveillance is a sociotechnical practice shaped by both human actors and digital technology. Although existing surveillance frameworks acknowledge the role that social context plays in shaping the outcomes of surveillance, they overlook the impact organisational culture, leadership, management, and employees have on shaping its characteristics. Current frameworks also underplay the influence of digital technology and fail to account for the impact modern digital technologies, such as artificial intelligence algorithms, have on shaping the characteristics of surveillance. Through an inductive approach that synthesises and integrates surveillance concepts and theories, this paper identifies and develops the characteristics of surveillance (i.e., purpose, observer, target, direction, transparency, and intrusiveness) as well as the specific social and technological elements shaping each characteristic. By integrating these dimensions, this paper produces an innovative sociotechnical framework that provides academics and practitioners with a detailed understanding of the various types of surveillance engendered in different organisational settings. This paper also sheds light on how the social and technological elements interact to shape the characteristics of surveillance, the negative outcomes and ethical challenges arising from each characteristic, and approaches to mitigating these negative effects. In addition, practical recommendations are offered to guide organisations with the responsible implementation of surveillance through a participatory process aligned with organisational policies and legal and regulatory requirements. These practical recommendations can also help organisations reduce resistance, improve trust between employers and employees, mitigate negative outcomes, avoid ethical concerns, and increase acceptance of surveillance.

Item Type:	Article
Uncontrolled Keywords:	46 Information and Computing Sciences; 35 Commerce, Management, Tourism and Services; 3507 Strategy, Management and Organisational Behaviour; 8.3 Policy, ethics, and research governance; 8.1 Organisation and delivery of services
Subjects:	H Social Sciences > HF Commerce > HF5001 Business
Divisions:	Liverpool Business School
Publisher:	Elsevier
Date of acceptance:	6 April 2025
Date of first compliant Open Access:	2 May 2025
Date Deposited:	02 May 2025 09:04
Last Modified:	02 May 2025 10:45
DOI or ID number:	10.1016/j.digbus.2025.100120
URI:	https://researchonline.ljmu.ac.uk/id/eprint/26199

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