Polycentric AI Governance: A Multi-Stakeholder Approach to Distributed Responsibility and Ethical Technology Management - Lim, Enoch Chi Ngai; Lim, Chi Eung Danforn (International Journal of Advanced AI Applications, 2025)
The swift evolution of artificial intelligence (AI) technologies has created unprecedented complexities in attributing responsibility within multifaceted technological systems concerning who is accountable for harm caused by AI technologies. This review analyses the chronological development of AI governance frameworks from 2018 to 2024 with special attention to newly emerging frameworks of distributed responsibility whereby developers, users, and regulators are legally bound under hybrid deontological-consequentialist governance systems. Through comprehensive analysis of policies, regulatory frameworks, case studies, and recent policy shifts, this paper argues that the inadequacy of the ‘single-point accountability’ model is increasingly becoming a defining feature of modern AI systems. This analysis illustrates an unparalleled global shift toward governance frameworks with distributed responsibility inspired by the EU AI Act 2024, UNESCO’s AI Ethics Recommendation 2021, and national governance frameworks emerging from Malaysia, Singapore, Australia, and Denmark. Applying stakeholder theory, duty of care, and Floridi’s information ethics, this review responds to the chief criticisms of distributed responsibility, such as concerns over diluted accountability and complexity of implementation. This narrative review advances the scholarly discourse on contemporary AI ethics by proposing a comprehensive policy framework that implements distributed responsibility through tiered-responsibility strategies, mandatory algorithmic impact assessments, and internationally coordinated oversight mechanisms. These findings offer balanced and practically implementable solutions to the competing desires of accountability and innovation within a networked technological landscape.