Governing Clinical AI for Sustainable Healthcare in Nigeria: Patient Safety, Distributed Accountability and Lifecycle Regulation
This presentation examined how Nigeria can govern clinically consequential AI systems—those influencing diagnosis, triage, prognosis, treatment, monitoring or resource allocation—without sacrificing patient safety, rights or sustainable health-system development. It argued that existing legal silos in data protection, medical-device regulation, negligence and procurement are necessary but insufficient when used separately. The paper proposed a Sustainable Clinical AI Governance Framework built on three rules: lifecycle safety; distributed accountability according to control and capability; and sustainability proportionality. Seven operational pillars translate these principles into practice, covering risk classification, data and equity, safety and human factors, explainability and contestability, accountability and remedy, monitoring and change control, and sustainable procurement. It concluded with a practical Nigerian roadmap centred on coordinated regulation, clinical-AI standards, a national register, incident learning, shared technical capacity and staged deployment.
- Status
- Presented in 2026
- Presenter
- Dr Abba Amsami Elgujja, PhD, LLM, BL, LLB
- Location
- Ahmadu Bello University, Zaria, Nigeria
- Focus
- Clinical AI, patient safety, accountability and sustainable healthcare