Artificial Intelligence and Patient-Centered Decision-Making
By Jens Christian Bjerring, Jacob Busch. 2020
212 citations recorded by the source corpus.
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.
Subfields: Health Informatics, Public Health, Environmental and Occupational Health, Safety Research
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Citations in the corpus
- Ethical Implementation of Artificial Intelligence to Select Embryos in In Vitro Fertilization (2021, background): “inability of the clinician and the patient to understand the model’s decision [35].”