The aim of this study is to analyse the challenges posed by artificial intelligence based worker management (AIWM) systems in relation to psychosocial risks and the role of worker participation structures in identifying, assessing, preventing and mitigating psychosocial risks arising from AIWM. AIWM is 'an umbrella term that refers to a worker management system that gathers data, often in real time, on the workspace, workers, the tasks they do, and the (digital) tools they use for their work, which is then fed into an AI-based model that makes automated or semi-automated decisions or provides information for decision-makers on worker management-related questions' (EU-OSHA, 2022: p.5). In recent years, the increasing reliance on AIWM within workplaces has sparked significant discussion concerning its impact on workers' occupational safety and health (OSH). On the one hand, AIWM can be used to prevent and mitigate some risks, and to assist managers and health and safety representatives in detecting and managing psychosocial risks at work. On the other hand, AIWM has often led to heightened surveillance, decreased job control, unpredictable work patterns and a perceived lack of fairness. The study has shown that AIWM can have both positive and negative psychosocial implications. Research exploring the detrimental psychosocial effects of AIWM shows that AIWM systems may intensify surveillance and erode workers' autonomy, which in turn leads to high stress levels. AIWM systems can also increase work intensity and the speed of work and lead to unpredictability in work schedules. Moreover, AIWM technologies that are used to monitor and evaluate performance can create performance pressure and are also associated with high stress levels among workers, particularly when they perceive the metrics and processes to be unfair. However, research also shows that psychosocial risks related to AIWM vary according to the type of company or the sector. In this regard, further research is needed to better identify specific sectoral risks associated with AIWM systems, particularly beyond the digital platform sector and in SMEs.
