Humans and machines: Moving towards a more symbiotic approach to learning clinical reasoning |
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| Authors: | Ralph Pinnock Jenny McDonald Darren Ritchie Steven J Durning |
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| Institution: | 1. Educational Unit, Dunedin School of Medicine, Otago University, Dunedin, New Zealand;2. ralph.pinnock@otago.ac.nz;4. Centre for Learning &5. Research in Higher Education (CLeaR), University of Auckland, Auckland, New Zealand;6. Dunedin School of Medicine, Otago University, Dunedin, New Zealand;7. Professor of Medicine and Pathology and Director Graduate Programs in Health Professions Education, Uniformed Services University of the Health Sciences, Bethesda, MD, USA;8. Medicine and Pathology, Uniformed Services University of the Health Sciences, Bethesda, MD, USA |
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| Abstract: | AbstractArtificial intelligence is a growing phenomenon that is driving major changes to how we deliver healthcare. One of its most significant and challenging contributions is likely to be in diagnosis. Artificial intelligence is challenging the physician’s exclusive role in diagnosis and in some areas, its diagnostic accuracy exceeds that of humans. We argue that we urgently need to consider how we will incorporate AI into our teaching of clinical reasoning in the undergraduate curriculum; students need to successfully navigate the benefits and potential issues of new and developing approaches to AI in clinical diagnosis. We offer a pedagogical framework for this challenging change to our curriculum. |
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