ArticleFrontiers in sociology2026
Algorithmic governance at work: a legal-sociological and policy analysis of AI regulation, institutional power and labor rights.
Article in Frontiers in sociology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Objectives: Artificial Intelligence (AI) has transformed and revolutionized the technological and informational space of the 21st century. AI has also reconfigured the way of relating and interacting with the information system, the work environment, the occupational structure, and the societal space. Within the framework of this study, the general objective aims to analyze and evaluate employee rights in the context of organizational change, technological innovation-driven algorithmic governance generated by automation and intelligent systems. The specific objective of the research focuses on reskilling under AI rules, AI civil liability for workers' rights regime, ethical use of algorithmic governance at the workplace, and social and behavioral outcomes. Methods and methodology: The current research uses legal-organizational analysis (LOA), combining systematic literature review with legal and exploratory-descriptive study of the AI phenomenon in order to identify the current state of regulation in the field. This method is complemented by comparative legal analysis of different regulatory systems at a global level, as well as good practices in the workplace and case studies of representative examples of AI regulation in the workplace to identify how automation is transforming the occupational space and employment relationships. Results and discussions: The legal-organizational analysis highlights the legal developments in Europe, the Americas, and the Asia-Pacific, identifying the diverse dimensions of the regulatory architectural structure for AI technology across six interrelated pillars. The results indicate that AI regulation across Europe, the Americas, and the Asia-Pacific is increasingly intersecting around human rights and personal data protection, risk-based governance, and accountability mechanisms, particularly in the employment environment. Legal frameworks emphasize transparency, non-discrimination, and the need for human oversight in AI-powered workplace decisions. Conclusion: The conclusions highlight that across Europe, the Americas and the Asia-Pacific, AI regulation is increasingly organized around six dimensions: protection of human rights and data privacy in the workplace; governance frameworks addressing reskilling, job transformation and adaptation to AI-driven work models; risk-based oversight of AI systems; AI civil liability regimes affecting employee rights and HR practices; promotion of ethical AI to foster trust and mitigate bias; and strengthened monitoring, accountability and non-discrimination mechanisms.
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