ABSTRACT Enterprise bargaining provides an innovative way for addressing concerns about workplace surveillance in the absence of legislative reform. This article examines how workplace surveillance is being addressed in registered enterprise agreements in Australia, and discusses the implications of those findings for the regulation of workplace surveillance. This article provides the results of the first detailed, industry-by-industry analysis of the nature and frequency of workplace surveillance clauses in Australian enterprise agreements. This article also proposes a typology for classifying the basic structure of the clauses encountered and describes the common features of each clause type. The findings provide insights on the extent to which unions are seeking to address workplace surveillance in enterprise bargaining in the Australian context. Our study is important for understanding the extent to which enterprise bargaining is providing an effective bulwark against increased workplace surveillance.

Through systematic literature synthesis (2000–2024) integrating Foucault’s disciplinary power theory, Nissenbaum’s contextual integrity framework, and job design theory, this paper develops the Autonomy-Surveillance Conceptual Framework to explain differential psychological impacts of digital workplace surveillance. The embrace of remote work has increased surveillance practices among organizations as an increased need to ensure employee productivity in remote settings appears, along with a drive to ensure data security and streamline workflows. Many employees perceive such practices as a breach of privacy, signifying employer distrust. The framework predicts that surveillance creates varying degrees of contextual integrity violation based on job autonomy: high-autonomy knowledge workers experience severe violations through trust erosion, procedural injustice, and temporal autonomy loss, while low-autonomy workers evaluate surveillance primarily through fairness criteria. This paper addresses a critical gap in existing research, which has focused on low-autonomy roles. By examining which roles are most impacted by digital surveillance, this paper seeks to highlight transparency and autonomy-sensitive policies to maximize the associated benefits of digital surveillance, while calling attention to employee well-being, trust, and organizational performance.

This analysis examines the escalating trend of digital workplace surveillance, arguing that such practices are not tools for operational efficiency but symptoms of a profound crisis of corporate insecurity. Using the late 2025 implementation of aggressive 'bossware' at a major IT services firm as a central case study, the text dissects how granular metrics, such as 300-second inactivity thresholds, reveal a management philosophy that prioritises visible motion over the invisible labour of cognitive work. This approach is situated within a broader ecosystem of surveillance, from the gig economy's invasive monitoring to the algorithmic management of physical labour, demonstrating a sector-wide regression towards outdated control mechanisms. Leveraging psychological frameworks like Self-Determination Theory, the document demonstrates that excessive monitoring shatters the psychological contract between employer and employee, destroying autonomy, competence, and relatedness. This, in turn, fosters a culture of 'performative productivity', incentivising countermeasures like 'mouse jiggling' while suppressing the deep work and creative risk-taking essential for innovation. The central hypothesis posits that this low-trust environment imposes a significant 'surveillance tax'-comprising software costs, management overhead, and high employee turnover-which creates a self-reinforcing 'insecurity loop' of declining performance and increased control. By contrasting this model with high-trust organisations that focus on outcomes rather than inputs, the analysis quantifies the financial dividend of trust, evidenced by superior revenue per employee, lower attrition rates, and enhanced organisational resilience. Ultimately, the text concludes that the path of surveillance, driven by leadership insecurity, is economically unsustainable and a strategic roadmap to obsolescence in an innovation-driven economy.

The challenges associated with ethical lapses in public service delivery are increasingly becoming evident in Kenya and globally. The enforcement of ethical standards within public service is, therefore, a critical issue that significantly impacts the effectiveness and efficiency of government operations and service delivery. Ethical breaches not only undermine public trust but also hinder the overall development and well-being of a country. This study aimed to determine the effect of the enforcement of ethical standards on public service delivery by Bomet County Government in Kenya. The study objectives were to examine the effects of compliance with laws, regular monitoring of employees, and the implementation of ethics training programs on public service delivery in Bomet County, Kenya. Institutional Theory and Agency Theory guided the research. A descriptive research design was adopted. The research targeted 165 employees. The research used a statistical technique to determine the sample size of 120 respondents. A stratified sampling technique was used to pick the study respondents. Both qualitative and quantitative data were collected and analysed. Descriptive and inferential statistics were utilised to analyse the quantitative data, while thematic analysis was used for qualitative data. The findings revealed that compliance with laws, regular monitoring and implementation of ethics training programs among employees had a positive and statistically significant effect on public service delivery as indicated by a p-value of 0.002, 0.002 and 0.004, respectively. The study concluded that compliance with laws promotes transparency and accountability among employees. Regular monitoring of employees enhances adherence to standards and prompt correction of deviation, while implementation of ethics training programs positively influences service quality by fostering ethical behaviour and professionalism among staff. The study recommended that the government should strengthen and enforce national-level ethical frameworks and codes of conduct across all public institutions. This includes harmonising anti-corruption policies, establishing a centralised ethical oversight unit, and conducting regular monitoring and audits to ensure adherence to public service values.

The political body has long stood at the center of debates on sovereignty, discipline, and biopolitics. In the digital era, algorithmic governance extends these dynamics by continuously classifying, monitoring, and regulating human life. This article examines how state and corporate systems—China’s Social Credit System (SCS), India’s Aadhaar, U.S. predictive policing, and Amazon’s workplace surveillance—deploy legitimizing discourses of trust, modernization, efficiency, and integrity to normalize surveillance. Using Critical Discourse Analysis (CDA), the study demonstrates how these narratives translate into behavioral mechanisms of compliance, avoidance, and resistance, revealing governance as both a structural imposition and a lived practice negotiated by individuals. The comparative perspective highlights that, while China’s SCS represents the most integrated model of algorithmic governance, parallel strategies of legitimization are evident across democratic and corporate contexts. To conceptualize this convergence, the paper introduces the notion of the algorithmically mediated political body , which captures how disciplinary and biopolitical logics are inscribed onto everyday practices through digital infrastructures. By synthesizing Foucauldian biopolitics with Zuboff’s surveillance capitalism, the study offers a theoretical contribution, showing how algorithmic dispositifs merge population‐level regulation with the commodification of behavioral data. The findings underscore that algorithmic governance is not confined to authoritarian regimes but constitutes a global pattern with profound implications for autonomy, inclusion, and resistance in the digital age. While the study includes a comparative discussion of Aadhaar, predictive policing, and Amazon’s workplace surveillance, primary data collection and discourse analysis were conducted solely for China’s SCS, with other cases examined through secondary academic and policy sources.

This study aims to propose a model for detecting the likelihood of fraud and financial crimes using forensic accounting tools. The required data were collected through semi-structured interviews with 15 expert forensic accountants using the snowball sampling method. An Interpretive Structural Modeling (ISM) approach was employed to develop a proposed model. According to the ISM analysis, the exploratory model includes 19 factors. The results revealed that forensic accounting tools include the following components: data analysis, accounting standards, auditing standards, financial ratio analysis, Benford's analysis, and cloud-based tools. Legal forensic accounting tools comprised components such as criminal and penal law, criminology, legal monitoring of individuals’ accounts, interviewing and interrogation, forensic analysis, and legal documentation. Other forensic accounting tools encompassed information technology, employee monitoring tools, and fraud psychology. Ultimately, accounting tools, legal tools, and other forensic accounting instruments contribute to reducing the incidence of fraud and financial crimes. This model provides a systematic framework for combating financial fraud by creating overlap among accounting, legal, and technological domains. The findings emphasize that integrating analytical tools (e.g., Benford's analysis) with advanced technologies (such as cloud systems) and legal mechanisms significantly enhances the accuracy and speed of fraud detection. Additionally, considering psychological and monitoring factors alongside legal requirements facilitates the design of more effective preventive policies. This model can serve as a foundation for developing forensic accounting standards and strengthening regulatory frameworks within organizations.

The article presents an organizational and functional model of psychological support for personnel of a motor transport enterprise operating under wartime conditions. The relevance of this study is determined by the high level of psycho-emotional stress faced by employees in the transport sector, which performs critical tasks such as cargo transportation, population evacuation, and delivery of humanitarian aid. In conditions of constant threat, prolonged air-raid alerts, disruption of social connections, and loss of colleagues or relatives on the frontline, employees are exposed to increased risks of professional burnout, stress-related maladaptation, and reduced work efficiency. The study aims to substantiate and present an organizational and functional model of psychological support for personnel of motor transport enterprises under wartime conditions, which ensures resilience, prevention of emotional burnout, maintenance of work efficiency, and continuity of operations. The proposed model consists of seven interrelated functional blocks: Organizational-Managerial, Integrated Crisis, Diagnostic-Analytical, Psycho-Educational, Individual, Group, and Digital. Each block performs specific functions, including centralized management, monitoring of employees’ psycho-emotional state, conducting trainings and informational activities, providing individual counseling, strengthening peer support, and facilitating digital communication and rapid response. The implementation of the system is structured as a phased process: Preparatory, Training and Information, Pilot Implementation, Analysis and Adjustment, Scaling, Institutionalization, and Sustainable Operation. This approach ensures adaptability to the enterprise’s operational conditions, minimizes psycho-emotional risks, enhances personnel management, and maintains productivity under high-stress circumstances. The proposed model is systemic, flexible, cost-effective, and applicable to other enterprises in the transport sector operating in turbulent or crisis environments. Further research may focus on evaluating its effectiveness, the impact on employees’ mental health, organizational performance outcomes, and integration of modern digital tools for monitoring and early intervention. The study contributes to the theoretical and practical understanding of occupational psychological support in high-risk contexts, providing a foundation for long-term workforce resilience and sustainable enterprise functioning under wartime conditions.

The Legal Boundary and Regulation of Intelligent Workplace Surveillance

This study examines knowledge workers’ perspectives on privacy implications and surveillant functionalities of group-based communicative AI in the context of work. The objective is to connect the ongoing examination of communicative AI in the workplace to research on privacy and employee surveillance, and to use the framework of privacy as contextual integrity as a theoretical lens through which some of the user perspectives on communicative AI tools are analyzed. Building on 33 qualitative interviews with Finnish knowledge workers, who were presented with scenarios of communicative AI functioning as a ‘team member’ in a work-related chat group, we find that knowledge workers recognize several privacy-related risks in using group-based communicative AI at work, and commonly use surveillant reasoning and logics to make sense of the suggested technology and its privacy implications. We present three distinct approaches knowledge workers had toward privacy in this setting: the detached, the compartmentalized, and the affective. Our findings suggest a wider need to consider communicative AI’s agency and role as an actor contributing to increasing privacy concerns. We highlight how, due to its human-like nature, data-reliant functionalities, and potential capabilities when operating in a group setting, the technology introduces negative affective responses and novel concerns related to privacy and employee surveillance. Specifically, privacy concerns relating to communicative AI expand beyond mere data protection issues to include concerns of how the technology is used by management, how the technology itself interacts within the organization, and how it will develop in the future.

As artificial intelligence transforms work through automation, a "wellbeing paradox" may emerge if its social and psychological impacts are not consciously managed. This practitioner-focused research brief explores the tensions between AI's productivity gains and potential threats to human thriving. Through a review of recent studies at the intersection of technology, jobs and wellbeing, it identifies challenges like job insecurity, social isolation, technostress, employee surveillance and over-reliance on algorithms that could undermine individuals' sense of purpose, autonomy, relationships and overall wellbeing. Meanwhile, AI provides an opportunity to cultivate resilience for workers through career support, meaningful reskilling, internal mobility and social connection in the workplace. The brief also outlines strategies for organizations to optimize human-AI collaboration through transparency, explainability and prioritizing augmentation over automation. It concludes with a "digital ergonomics" framework of boundary-setting, mindfulness, presence and wellbeing nudges to proactively design technology that enhances rather than depletes human capacities and fulfillment.

Abstract Artificial intelligence is revolutionising industry, significantly improving work efficiency. However, the development of AI continues to generate new ethical challenges. An international legal framework has already been developed to ensure the ethical and safe development of AI. However, it seems that new threats and ethical dilemmas continue to arise as AI develops further. This study aims to explain some of the benefits and threats of using AI in industry and to encourage reflection on the need to intensify work in this area in view of the further development of AI. Several selected ways of using AI in industry are presented, such as the implementation of cobots, algorithmic management, employee monitoring, the implementation of sustainable development ideas, and the use of generative artificial intelligence. Some of the existing legal frameworks for the safety and ethics of artificial intelligence are also described. The work is theoretical in nature and is based on a critical analysis of the literature on the subject. The reflections presented reveal a lack of consideration of the dangers associated with the responsibility involved in entrusting machines with autonomy and decision-making.

From humans to algorithms: A sociotechnical framework of workplace surveillance

Microchip implants have significantly broadened their application beyond their initial use in animal tracking and are increasingly being utilized in humans for a variety of purposes. These implants are not only employed in medical treatments and performance enhancement but are also used for tracking, surveillance, contactless payments, and access control. Although the adoption of microchip implants is observed in specific sectors and countries, researchers continue to explore their broader adoption and integration. While this technology offers several conveniences, it simultaneously raises concerns about security, privacy, and the potential for data misuse. This study aims to provide a structured framework by systematically analyzing the use of microchip implants in humans and their implications for businesses. A descriptive analysis was conducted on 28 articles identified through searches in the WOS and Scopus databases, resulting in the identification of six key themes and 24 categories. The findings reveal that microchip implants have a wide range of applications, yet their social acceptance is hindered by unresolved ethical and legal challenges. While these implants offer businesses advantages in terms of efficiency and speed, issues such as employee surveillance and the unauthorized collection of personal data remain significant concerns.

Dwi Putra Tile Craftsman (PG. Dwi Putra) is a manufacturing industry in Klaten, Central Java, which produces three types of press tiles, namely mantili tiles, ordinary tiles, and kerpus. Recording the results of employees' work today is carried out manually, which often leads to inaccuracies in the data and hinders the calculation of salaries. Solving this problem requires a website-based employee monitoring system that can record, monitor, and report work results in real-time, and speed up salary calculations. This system aims to efficiently record employee work results, monitor productivity in real-time, provide accurate and structured work reports, automate the salary calculation process, and provide integrated and easily accessible data access. This system is built by using the Laravel Framework by implementing a Waterfall approach, and MySQL as a database. System testing is carried out with a Black Box approach and System Usability Scale (SUS). The results of the application of the Black Box method indicate that all system functions operate according to the expectations set by the researcher, resulting in a validity rate of 100%. The trial with SUS resulted in a grade of 82.5, which indicates that the system is functioning very well and has met the eligibility criteria.

BackgroundWithin radiology departments, computed tomography (CT) has been identified as presenting a higher risk of infection compared to other imaging modalities. CT scanning often deploys contrast injectors to administer iodine contrast intravenously, which poses infection risks for patients and staff. The aim of this study was to explore the variations in practice and the enablers and barriers to infection prevention and control (IPC) practices in the CT suite in Australia.MethodsSemi-structured focus group discussions (FGD) were conducted over three sessions with thirteen registered radiographers, who had expressed interest in participating in FGDs after completing a survey on IPC knowledge and practice. The FGDs ran for one hour and questions focused on workplace surveillance, IPC education, risks associated with different components of contrast injectors, and variations between staff. FGDs were transcribed verbatim and coded using thematic analysis to identify key themes and concepts.ResultsThree key themes arose from the focus group discussions: ‘Communication and Education in Radiology’, ‘Safety in CT’, and ‘Injection Technology’. Participants described general IPC modules, most of which did not relate to the CT environment. In hospital settings, IPC policies were often considered broad, and participants described having no written policies relating to IPC and the CT contrast injector. IPC safety was impacted by other staff members, particularly staff from other departments who assist with connecting the CT injector but were often not familiar with CT equipment. CT injectors have connection points that must remain sterile and poor adherence to IPC practices will increase the risk of infections. The number of connection points are less in multi-use injectors compared to single-use injectors, hence, there was a perceived advantage with multi-use injectors. However, single-use injectors were used for infectious patients if available for easier cleaning.ConclusionThe lack of CT-specific IPC training and policies led to variations in practice between staff in the CT suite. Training and resources focused on radiology settings and scenarios are needed and would benefit both radiology staff and other wards that require radiology services.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12913-025-13728-z.

International organizations play an important role in framing the debate about how new technologies transform global labour markets. Merging insights from the recent scholarship on technology and society with academic debates on global social policy, we look at policy reports from international organizations to see how they discuss the debate for middle-income countries. We focus on these countries because they are very much affected by technological change, but often less discussed. Contrasting the reports against discussions of academics and policy experts, we find that the overall tone of these reports tends to be more positive than underlying sources, even if there are discernible multiple differences between organizations. We also find that frames about cash transfers are much more present than discussions about labour standards or the regulation of technology, and important aspects such as workplace surveillance are almost absent. Our findings imply that most international organizations exhibit a conditional solutionist mindset – ‘technological change is good, if . . . ’– thereby excluding important dimensions of the debate. This casts a shadow on how policy responses towards technological disruption in these countries will look like.

The engagement of artificial intelligence (AI) has been presented as one of relentless and uniform progress reshaping management practices and employee relations across the globe. Or so the narrative goes. This paper argues that the adoption of AI-driven management and surveillance tools is not a culturally neutral phenomenon but contains differences as understood whether in an Eastern or Western context. Through a synthesis of existing literature, this analysis examines this divide by focusing on algorithmic management and workplace surveillance. Western contexts, prioritizing individual autonomy, tend to view algorithmic surveillance with precaution, framing it as an infringement on rights. Many Eastern contexts that emphasize collective harmony and national goals would demonstrate a higher degree of acceptance of these tools as instruments for efficiency and social order. This dichotomy is examined further through an analysis of China's Corporate Social Credit System as an apotheosis of the state-driven, collectivist model. The paper then provides a comparative analysis of worker pushback, and how responses to algorithmic control are themselves culturally coded. The paper concludes that a one-size-fits-all approach to the deployment of workplace AI is untenable, and discusses a few implications for multinational corporations, global AI ethics, and the future of labor rights.

This article explores the ethical dimensions of cloud-based human resources technologies in aviation, examining the intersection of digital transformation with the unique challenges of a safety-critical industry. It analyzes how these technologies reshape employee monitoring, performance evaluation, and psychological assessment while creating new power dynamics between organizations and aviation professionals. Through examination of case studies, including mental wellness tools and performance review systems, the article develops a framework for human-centered design that balances automation with meaningful oversight, transparency, and employee participation. It proposes governance mechanisms that address regulatory complexities across international jurisdictions while establishing stakeholder engagement models, accountability structures, and grievance platforms. The article concludes by articulating a vision for socially responsible implementation that harnesses technological capabilities while preserving the professional judgment, psychological well-being, and human dignity essential to aviation safety and operational excellence.

BackgroundZirconium (Zr) compounds have increasingly been used as alternatives to traditional toxic metals in industrial processes, yet comprehensive exposure and biomonitoring data are scarce. This study aimed to assess occupational exposure to zirconium and co-metals (cobalt, nickel, arsenic) in Taiwanese manufacturing industries through integrated environmental and biological monitoring.MethodsA cross-sectional investigation was conducted in eight metal surface treatment plants, with biomonitoring conducted among ten exposed workers. Personal and area air sampling were analyzed for zirconium and co-metals using inductively coupled plasma–optical emission spectrometry (ICP-OES); urine and blood samples were analyzed for internal exposure biomarkers (urinary zirconium, urinary/blood cobalt, urinary nickel, blood arsenic) by inductively coupled plasma–mass spectrometry (ICP-MS). Pulmonary effects were assessed using spirometry.ResultsAirborne Zr concentrations varied substantially by process, with the highest levels observed in shelling and slurry mixing operations (up to 22.55 µg/m³). Urinary Zr was undetectable in all participants (< 0.2 µg/L), consistent with limited systemic absorption. In contrast, co-metals were consistently detected: cobalt and nickel were elevated in workers handling ceramic pigments and surface finishing tasks. Regression analyses indicated inverse associations between cobalt and hemoglobin, nickel and oxidative/inflammatory markers (8-OHdG, CRP), and positive associations between nickel and IgM, and arsenic and IgM. Spirometry indices remained within clinical reference ranges but tended to be lower among high-exposure workers.ConclusionsThis study provides the first integrated dataset of zirconium and co-metal exposure in Taiwanese industry, showing measurable airborne Zr but undetectable urinary Zr under current conditions. Co-metals (cobalt, nickel, arsenic) demonstrated significant associations with hematologic, oxidative, and immunologic markers, underscoring the complexity of mixed-metal exposures. These findings support ongoing workplace surveillance and further research on health implications of zirconium and co-metal co-exposures.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12995-025-00483-4.

ABSTRACT In the shift towards human-centred manufacturing, our two-year longitudinal study investigates the real-world impact of deploying Cognitive Assistants (CAs) in factories. The CAs were designed to facilitate knowledge sharing among factory operators. Our investigation focussed on smartphone-based voice assistants and LLM-powered chatbots, examining their usability and utility in a real-world factory setting. Based on the qualitative feedback we collected during the deployments of CAs at the factories, we conducted a thematic analysis to investigate the perceptions, challenges, and overall impact on workflow and knowledge sharing. Our results indicate that while CAs have the potential to significantly improve efficiency through knowledge sharing and quicker resolution of production issues, they also introduce concerns around workplace surveillance, the types of knowledge that can be shared, and shortcomings compared to human-to-human knowledge sharing. Additionally, our findings stress the importance of addressing privacy, knowledge contribution burdens, and tensions between factory operators and their managers.