ArticleBMC medical ethics2025
Strengthening ethics review of the development of artificial intelligence (AI) systems in health research: a guide for research ethics committees in Uganda.
Article in BMC medical ethics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- AI literacy and ethical attitudes toward AI in medical students: evidence from a structural model.BMC medical education · 2026Article
- Exploring the operational challenges of navigating ethical oversight in the era of artificial intelligence: a qualitative study of health research ethics committees in Tanzania.BMC medical ethics · 2026Article
- Research Ethics Committees (RECs) perspectives on large language models and AI ethics review: a South African case.BMC medical ethics · 2026Article
- Ethics in AI Research: Emerging Governance Challenges for Institutional Review Boards in Health Systems.Journal of multidisciplinary healthcare · 2026Article
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Authors and funding
4 authors.
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Abstract
introductionThe ability of artificial intelligence (AI) to analyze data in real-time and improve patients' diagnosis has led to a rapid growth of AI- health research in Uganda. Yet, there are no national guidelines on how to conduct AI-research in an ethical manner. Recent studies have reported that ethics committees lack resources, expertise and training to appropriately address the risks that may arise from AI health research. This study aimed to develop a guide for ethical review of the development of AI systems in health research in Uganda.
methodsThis study employed an exploratory qualitative approach between March - October 2024, involving 35 stakeholders in two public universities in Uganda. In-depth interviews were conducted with twelve members of ethics committees who had ever reviewed AI- protocols, six bioethicists, eight health researchers and nine members of AI-development teams. A thematic approach was used to interpret the results.
resultsSix themes emerged from this data including promoting social value and equity; ensuring participants and end-user autonomy and safety; addressing data acquisition, access and sharing gaps; ensuring responsible data use and data minimization; promoting responsible AI and fostering collaborative partnerships. Respondents opined that AI holds promise for improving health research. However, its successful implementation demands ethical considerations to minimize harm to participants and end-users.
conclusionOverall, respondents felt that developing a guide for ethics review of AI-research may minimize potential harms that could arise from using AI tools in research. We recommend training of ethics committees on key ethical considerations for development of responsible AI tools.
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Registered trials
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