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About our research

The rapid development of artificial intelligence (AI) is considered one of the most transformative forces of our time. This burgeoning use of AI also impacts the medical world, particularly in the case of image-based medicine . So far the technical possibilities of digitalization and AI in medicine have been at the fore of academic debate. Yet understanding and guidance for the responsible development and use of such technologies is urgently required. We believe that now is the right time to scrutinize the process of digitalization and the desired role for AI in image-based medicine, as AI is currently being implemented but not yet “carved in stone”.

“Responsible Artificial Intelligence in clinical DecisIOn-making” is a 4-year long, NWO-funded research project aiming to investigate the question: How should AI be responsibly integrated and used in image-based medicine? To answer this, we will first chart and refine the conceptual terrain of AI-augmented medical decision-making.  Subsequently, we will gather an empirical understanding of two central case studies in image-based medicine, the field of pathology and radiology by means of interviews with relevant stakeholders and an ethnographic film to stimulate the discussion on AI in medicine with patients and the broader public. The outcomes of these investigations will form the basis for a theoretical and empirically informed normative framework for the responsible development and use of AI in image-based medicine. 

This research project is a collaboration between the University Medical Centre Utrecht, Maastricht University, and Radboud University Medical Centre. Researchers involved are Annelien Bredenoord (professor ethics of biomedical innovation), Jojanneke Drogt (PhD candidate), Karin Jongsma (associate professor of bioethics), Flora Lysen (assistant professor in cultural analysis of science and media), Megan Milota (assistant professor in medical humanities), Shoko Vos (pathologist) and Sally Wyatt (professor of digital cultures). The varying disciplinary backgrounds of the RAIDIO team members  allow us to study the issue of AI-augmented medical decision-making with an  interdisciplinary approach. We will also use this research project as an opportunity for joint reflection on the way interdisciplinary collaboration can support normative guidance.

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