Philosophy and Technology:1-23 (forthcoming)

Authors
Jacob Busch
University of Aarhus
Abstract
Advanced AI systems are rapidly making their way into medical research and practice, and, arguably, it is only a matter of time before they will surpass human practitioners in terms of accuracy, reliability, and knowledge. If this is true, practitioners will have a prima facie epistemic and professional obligation to align their medical verdicts with those of advanced AI systems. However, in light of their complexity, these AI systems will often function as black boxes: ​the details of their contents, calculations, and procedures cannot be meaningfully understood by human practitioners. ​When AI systems reach this level of complexity, we can also speak of black-box medicine. In this paper, we want to argue that black-box medicine conflicts with core ideals of patient-centered medicine. In particular, we claim, ​black-box medicine is not conducive for supporting informed decision making based on shared information, shared deliberation, and shared mind between practitioner and patient.
Keywords Black-box medicine  Patient-centered medicine  Artificial intelligence and medicine  Medical decision making
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DOI 10.1007/s13347-019-00391-6
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References found in this work BETA

On the Proper Treatment of Connectionism.Paul Smolensky - 1988 - Behavioral and Brain Sciences 11 (1):1-23.

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Citations of this work BETA

Limits of Trust in Medical AI.Joshua James Hatherley - 2020 - Journal of Medical Ethics 46 (7):478-481.

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