The Need for Artificial Intelligence Regulation in Colleges of Health Sciences and Technology in Edo State

Artificial Intelligence (AI) is increasingly influencing healthcare education, research, and administrative decision-making, including within tertiary health institutions in developing contexts. In Edo State College of Health Sciences and Technology, AI-driven tools have the potential to enhance medical training, diagnostics, health data management, and institutional efficiency. However, the adoption of AI within health sciences education and practice also introduces ethical, legal, and professional risks, such as data privacy violations, algorithmic bias in clinical decision support, lack of transparency, and challenges to accountability. This article argues that institution-specific and context-aware AI regulation is essential for Edo State College of Health Sciences and Technology to ensure that AI use aligns with professional healthcare standards, patient safety, and public trust. Drawing on academic literature on AI governance, healthcare ethics, and regulatory theory, the article demonstrates that tailored, risk-based regulatory frameworks can support innovation while safeguarding ethical practice. The article contributes to institutional policy discussions by providing a scholarly justification for AI regulation within health sciences and technology education.

Artificial Intelligence, AI Regulation, Institutional Governance

1. Floridi, L., Cowls, J., Beltrametti, M., et al. (2018). AI4People—An ethical framework for a good AI society. Minds and Machines, 28(4), 689–707. https://doi.org/10.1007/s11023-018-9482-5 [Google Scholar] [Crossref]

2. Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence, 1(9), 389–399. https://doi.org/10.1038/s42256-019-0088-2 [Google Scholar] [Crossref]

3. Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016). The ethics of algorithms: Mapping the debate. Big Data & Society, 3(2), 1–21. https://doi.org/10.1177/2053951716679679 [Google Scholar] [Crossref]

4. OECD. (2019). Artificial intelligence in society. OECD Publishing. https://doi.org/10.1787/eedfee77-en [Google Scholar] [Crossref]

5. Stilgoe, J., Owen, R., & Macnaghten, P. (2013). Developing a framework for responsible innovation. Research Policy, 42(9), 1568–1580. https://doi.org/10.1016/j.respol.2013.05.008 [Google Scholar] [Crossref]

6. Veale, M., & Borgesius, F. Z. (2021). Demystifying the draft EU Artificial Intelligence Act. Computer Law Review International, 22(4), 97–112. https://doi.org/10.9785/cri-2021-220402 [Google Scholar] [Crossref]

7. Topol, E. (2019). High-performance medicine: The convergence of human and artificial intelligence. Nature Medicine, 25(1), 44–56. https://doi.org/10.1038/s41591-018-0300-7 [Google Scholar] [Crossref]

8. World Health Organization. (2021). Ethics and governance of artificial intelligence for health. WHO Press. [Google Scholar] [Crossref]

9. National Information Technology Development Agency (NITDA). (2023). National Artificial Intelligence Strategy for Nigeria. Abuja. [Google Scholar] [Crossref]

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