The Ethics of Reviewing AI Studies by Research Ethics Committees (Recs) in Low and Medium Income Countries (LMICs)

The recent breakthroughs in medical technology and Artificial Intelligence (AI) in healthcare have had an important impact on disease diagnosis, patient management and treatment outcomes across the globe. Settings with limited resources are likely to benefit from efficiencies that come with AI in health research, making AI health technologies very appealing for most low and middle income countries (LMICs) because they facilitate access to services.  

However, due to the relatively new nature of AI health technologies in LMICs, it is not clear whether regulatory authorities, such as research ethics committees (RECs), in these settings have adequate capacity to provide research oversight to these studies, and to determine the appropriate proportion of benefits and risks to participants. Oversight of AI health research require relevant competencies by local RECs, however, it is likely that the rapid advances in AI are beyond the capacity of most RECs in LMICs to adequately determine ethical issues in such studies.  

Zambia, like other LMICs, has seen an increase in AI studies, however there is no indication that RECs in the country have the required capacity to review these studies, ensure protection of research participants and to ensure that both the benefits and risks of such studies are within acceptable standards. The lack of standardized AI related regulations makes it impossible for RECs to uniformly determine the social value, scientific validity and favorable risk-benefit ratio of AI studies, effectively making these studies unethical. This may create inequities in access to these health technologies which may erode the benefits associated with AI health technologies.  

To ensure equitable and ethical access to AI in health research, we propose a study to assess the knowledge, attitudes and current practices of Zambian health research regulators, such as the Zambia Health Research Authority and the existing RECs. This will provide insights on the gaps and capacity building needs to ensure that benefits from AI research are equitable and ethical.