From humans to algorithms: A sociotechnical framework of workplace surveillance

The increasing integration of digital technologies into organizational frameworks has amplified the prevalence of surveillance practices across various sectors. This study investigates the nature and extent of digital surveillance practices in Punjab, with a particular focus on how organizations monitor employee activities and data. Drawing from qualitative interviews and quantitative surveys conducted across public and private institutions, the research explores the tools, purposes, and perceived intrusiveness of digital monitoring. The findings reveal a growing reliance on surveillance technologies such as biometric systems, internet usage tracking, CCTV, GPS-enabled devices, and productivity monitoring software. While organizations justify these measures as necessary for security, efficiency, and policy compliance, employees often express concerns regarding privacy, autonomy, and ethical boundaries. The study highlights the need for balanced surveillance policies that protect organizational interests while upholding employee rights and fostering trust. The paper concludes with recommendations for developing transparent digital surveillance frameworks guided by legal, ethical, and human resource considerations. The research aims to understand the tools used, the rationale behind their deployment, and their perceived impact on employee privacy and workplace culture. A mixed-method research design was adopted, combining quantitative surveys distributed among 250 employees across diverse organizations with in-depth qualitative interviews conducted. The data was analyzed using descriptive statistics and thematic coding to uncover trends, patterns, and subjective perceptions regarding digital monitoring. The findings indicate a growing reliance on surveillance technologies such as CCTV, biometric attendance systems, internet usage tracking, email monitoring, and GPS-enabled field tracking. While organizations largely justify these practices on grounds of security, productivity, and compliance, employees often report concerns related to privacy invasion, stress, and reduced trust. The study concludes by advocating for transparent, policy-driven surveillance frameworks that balance organizational needs with ethical standards and employee rights.

This chapter describes the conflict between employers' legitimate rights and employees' right to privacy and data protection as a result of the shift in workplace surveillance from a non-digital to a technologically advanced one. Section 1 describes the transition from non-digital workplace surveillance to an Internet-centred one, where “smart” devices are in a dominant position. Section 2 focuses on the legal framework (supranational and national legislation and case law) of workplace surveillance. In section 3, one case study regarding wearable technology and the law is carried out to prove that national and European legislation are not adequate to deal with all issues and ambiguities arising from the use of novel surveillance technology at work. The chapter concludes by noting that the adoption of sector specific legislation for employees' protection is necessary, but it would be incomplete without a general framework adopting modern instruments of data protection.

This chapter describes the conflict between employers' legitimate rights and employees' right to privacy and data protection as a result of the shift in workplace surveillance from a non-digital to a technologically advanced one. Section 1 describes the transition from non-digital workplace surveillance to an Internet-centred one, where “smart” devices are in a dominant position. Section 2 focuses on the legal framework (supranational and national legislation and case law) of workplace surveillance. In section 3, one case study regarding wearable technology and the law is carried out to prove that national and European legislation are not adequate to deal with all issues and ambiguities arising from the use of novel surveillance technology at work. The chapter concludes by noting that the adoption of sector specific legislation for employees' protection is necessary, but it would be incomplete without a general framework adopting modern instruments of data protection.

This chapter describes the conflict between employers' legitimate rights and employees' right to privacy and data protection as a result of the shift in workplace surveillance from a non-digital to a technologically advanced one. Section 1 describes the transition from non-digital workplace surveillance to an Internet-centred one, where “smart” devices are in a dominant position. Section 2 focuses on the legal framework (supranational and national legislation and case law) of workplace surveillance. In section 3, one case study regarding wearable technology and the law is carried out to prove that national and European legislation are not adequate to deal with all issues and ambiguities arising from the use of novel surveillance technology at work. The chapter concludes by noting that the adoption of sector specific legislation for employees' protection is necessary, but it would be incomplete without a general framework adopting modern instruments of data protection.

A smart and scalable system is required to schedule various machine learning applications to control pandemics like COVID‐19 using computing infrastructure provided by cloud and fog computing. This paper proposes a framework that considers the use case of smart office surveillance to monitor workplaces for detecting possible violations of COVID effectively. The proposed framework uses deep neural networks, fog computing and cloud computing to develop a scalable and time‐sensitive infrastructure that can detect two major violations: wearing a mask and maintaining a minimum distance of 6 feet between employees in the office environment. The proposed framework is developed with the vision to integrate multiple machine learning applications and handle the computing infrastructures for pandemic applications. The proposed framework can be used by application developers for the rapid development of new applications based on the requirements and do not worry about scheduling. The proposed framework is tested for two independent applications and performed better than the traditional cloud environment in terms of latency and response time. The work done in this paper tries to bridge the gap between machine learning applications and their computing infrastructure for COVID‐19.

Current sophisticated technologies in the workplace offer inexpensive and user-friendly devices and the means to control ‘on-the-job’ behaviour. This promises high profitability, productivity and liability alleviation. Yet, it also gives rise to a socio-ethical crisis of incessant surveillance that often overrules its anticipated benefits and motives of control and care. The dilemma is twofold: First, scholarly studies undertaken on this issue from a principally administrative and legal point of view tend to lack a moral framework and so prove unable to offer an integral understanding. Second, a majority of scholars tend to focus exclusively on individual rights, such as privacy, even at the risk of overlooking its social impact and consequences. This paper thus aims to unravel these forgotten moral and social concerns. It analyses the surveillance frameworks and the arguments for and against it; scrutinises critically the technological devices most often implemented in the workplace; examines both its individual effects (privacy) and social effects (categorising); and proposes an ethics of workplace surveillance in a framework of trust and transparency. It argues, in all these ways, for an alteration or modification of traditional organisational behaviour within a new frame of reference, situated within and going beyond questions of moral duty, principles and legal compliance.