Olawade, David ORCID: https://orcid.org/0000-0003-0188-9836, Clement David-Olawade, Aanuoluwapo, Aderinto, Nicholas and Wada, Ojima Z. (2026) Ethical oversight of Artificial Intelligence in Nigerian Healthcare: A qualitative analysis of ethics committee members’ perspectives on integration and regulation. International Journal of Medical Informatics, 206. p. 106140.

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Abstract

Background
The adoption of artificial intelligence (AI) in healthcare has the potential to improve diagnostic accuracy, streamline processes, and address resource shortages, particularly in low- and middle-income countries (LMICs) like Nigeria. However, challenges related to knowledge, ethics, and regulation hinder its implementation.
Aim
This study aimed to explore ethics committee members’ perspectives on AI integration in healthcare across public teaching hospitals in southwest Nigeria, examining their knowledge, perceived benefits, challenges, and regulatory considerations surrounding AI adoption in healthcare settings.
Methods
A qualitative study design was used, involving semi-structured interviews with 10 ethics committee members from five public teaching hospitals across southwest Nigeria. Thematic analysis was conducted using NVivo software to identify key themes regarding knowledge, benefits, challenges, risks, and regulatory needs associated with AI in healthcare.
Results
Participants acknowledged AI’s potential to improve efficiency and accuracy in healthcare. However, they expressed concerns about limited knowledge and training, financial barriers, and data privacy issues. Ethical concerns included potential AI errors and overreliance on technology. Participants highlighted the need for comprehensive regulatory frameworks and emphasized a collaborative approach to AI regulation, involving multiple stakeholders. Trust in AI was found to be contingent upon demonstrated accuracy and reliability.
Conclusions
While participants recognized the benefits of AI in addressing healthcare challenges, significant knowledge gaps, ethical concerns, and regulatory deficiencies present barriers to AI’s successful implementation. Addressing these challenges through training, investment, and multi-stakeholder regulatory efforts could facilitate the responsible and effective integration of AI into Nigeria’s healthcare sector.

Item Type:	Article
Status:	Published
DOI:	10.1016/j.ijmedinf.2025.106140
School/Department:	London Campus
URI:	https://ray.yorksj.ac.uk/id/eprint/13207

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