Mind the gap: exploring the emergence of AI in medical research.

As Artificial Intelligence (AI) is implemented everywhere, it is also emerging in the sphere of medical scientific research. An interesting context, indeed, for ethics is not only highly present, but also highly regulated by strong legal mechanisms, moral frameworks and independent ethics review committees (ERC’s). These key oversight bodies of medical scientific research on human subjects are unique places where the implementation of AI is ethically assessed, and ERC-members are hereby at the forefront of the implementation of this new, emerging and disruptive technology. What do members of the ERC view to be the risks of AI and data-intensive research? How do they respond to these risks? Are there risks of AI and data-intensive research that committee members signal, but are not able to address? In short, what are the gaps between the tradition of research ethics, that mostly focuses on protecting the individual participant, and the newly upcoming field of AI ethics, in which concerns of social justice, bias and discrimination and the dependency of Big Tech are raised? In discussing the results of my empirical study into how ERC-members experience the ethics assessment of AI and data-intensive medical research, we will explore three gaps; (1) despite the hype on AI, there is a low frequency of AI and data-intensive research, (2) societal risks fall outside the scope of assessment of ERC’s, and (3) ERC-members struggle with the assessment of AI and data-intensive research, referring to existing moral and legal frameworks in their response to these challenges. In an attempt to bridge the gap between research ethics and AI ethics, this presentation will conclude with recommendations for how ERC’s can best deal with the (new) challenges that come with AI and data-intensive research.