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  1. “Just do your job”: technology, bureaucracy, and the eclipse of conscience in contemporary medicine.Jacob A. Blythe & Farr A. Curlin - 2018 - Theoretical Medicine and Bioethics 39 (6):431-452.
    Market metaphors have come to dominate discourse on medical practice. In this essay, we revisit Peter Berger and colleagues’ analysis of modernization in their book The Homeless Mind and place that analysis in conversation with Max Weber’s 1917 lecture “Science as a Vocation” to argue that the rise of market metaphors betokens the carry-over to medical practice of various features from the institutions of technological production and bureaucratic administration. We refer to this carry-over as the product presumption. The product presumption (...)
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  • Of Slide Rules and Stethoscopes: AI and the Future of Doctoring.Robert D. Truog - 2019 - Hastings Center Report 49 (5):3-3.
    Historically, the practice of medicine has been a physically intimate endeavor. Physicians have used their hands to palpate and reveal the secrets hidden within the body. Smelling the breath for the ketosis of diabetes or tasting the skin for the saltiness of cystic fibrosis were among the physician's essential practices. Today, perhaps the most defining characteristic of a brilliant clinician is the ability to synthesize many images—from electrocardiograms, ultrasounds, CT scans, and so forth—into a coherent picture that can guide our (...)
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  • Clinical applications of machine learning algorithms: beyond the black box.David S. Watson, Jenny Krutzinna, Ian N. Bruce, Christopher E. M. Griffiths, Iain B. McInnes, Michael R. Barnes & Luciano Floridi - 2019 - British Medical Journal 364:I886.
    Machine learning algorithms may radically improve our ability to diagnose and treat disease. For moral, legal, and scientific reasons, it is essential that doctors and patients be able to understand and explain the predictions of these models. Scalable, customisable, and ethical solutions can be achieved by working together with relevant stakeholders, including patients, data scientists, and policy makers.
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