Ibitoye, Ayodeji Olusegun ORCID: https://orcid.org/0000-0002-5631-8507, Makuochi, Samuel Nkwo and Orji, Rita (2025) Rethinking responsible AI from ethical pillars to sociotechnical practice. AI and Ethics, 5. pp. 6207-6223. ISSN 2730-5961 (Online) (doi:10.1007/s43681-025-00809-2)

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Abstract

The growing demand for Responsible AI has crystallised around normative principles: fairness, transparency, accountability, privacy, safety, and value alignment, yet their implementation often reveals profound conceptual and operational instability. This research employs a constructively critical approach to examine the structural tensions underlying these pillars and argues that prevailing frameworks treat responsibility as a static compliance exercise, detached from the sociotechnical realities of AI systems. Drawing on traditions in process ethics, participatory design, and adaptive governance, the study develops a reframed understanding of Responsible AI as a dynamic, negotiated, and context-sensitive process. It advances a composite theoretical model and a layered ecosystem framework that redistributes responsibility across design, deployment, governance, and public deliberation. Through this reframing, the work offers both a critique of the dominant paradigm and a practical roadmap for interdisciplinary engagement, ethical responsiveness, and institutional reflexivity. The contribution is twofold: a conceptual synthesis that challenges the assumptions of checklist ethics, and an applied methodology with implications for AI researchers, developers, policymakers, and civil society actors working to navigate the ethical complexity of real-world AI design, deployment and use.

Item Type:	Article
Uncontrolled Keywords:	Responsible AI, AI ethics, sociotechnical systems, adaptive governance, process ethics, participatory design
Subjects:	B Philosophy. Psychology. Religion > BJ Ethics Q Science > Q Science (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS)
Last Modified:	05 Jan 2026 11:58
URI:	https://gala.gre.ac.uk/id/eprint/52023

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