Guidance for ethics review of Artificial Intelligence-related research: A scoping review

Mr Yves Saint James Aquino1

1University Of Wollongong, Wollongong, Australia

Biography:

Dr Yves Saint James Aquino (he/him) is a physician and philosopher with expertise in theoretical and applied ethics, empirical bioethics, and philosophy of medicine. His program of research currently focuses on the ethical, legal and social implications of artificial intelligence applications in healthcare. Yves is a research fellow at UOW's Australian Centre for Health Engagement, Evidence and Values (ACHEEV), and a member of Wiser Healthcare, a multi-institutional collaboration conducting research that will reduce overdiagnosis and overtreatment in Australia and around the world. He is one of the editors-in-chief of Research Ethics (Sage Publications)

Abstract:

A fundamental gap in research infrastructure worldwide is the absence of clear and shared framework to guide the ethical evaluation and oversight of artificial intelligence (AI) research across industries, such as healthcare. Ethics committees frequently face challenges in evaluating research on emerging technologies (e.g. gene editing, synthetic biology). Such new technologies raise questions around whether new approaches to research governance and ethics review are needed, or whether existing approaches are sufficient. This question also applies to AI. A systematic search of peer-reviewed and grey literature was conducted to map the literature on research ethics review of AI research, to identify whether there are gaps in research ethics governance infrastructures that are problematic for review of AI-related research, and identify tools to address any such gaps. We will present our analysis of documents under three themes: 1) whether AI research is exceptional; 2) whether ethics review requires an exceptional approach; and 3) strategies to address gaps in ethics review/governance of AI research. We found that authors take positions on a spectrum, ranging from non-exceptionalist (arguing that no change is needed) in one extreme, to exceptionalist (arguing for a new system or approach) in another. In the middle are approaches that propose a range of new tools or skills that can be integrated into existing frameworks. We suggest ways forward for ethical review of research involving AI.

 

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