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Trust in Medicine

In Judith Simon (ed.), The Routledge Handbook of Trust and Philosophy (2020)

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  1. Undisclosed probing into decision-making capacity: a dilemma in secondary care.Sandip Talukdar - 2021 - BMC Medical Ethics 22 (1):1-14.
    BackgroundThe assessment of patients’ decision-making capacity is ubiquitous in contemporary healthcare. This paper examines the ethics of undisclosed probing of capacity by psychiatrists. The discussion will refer to the law in England and Wales, though the highlighted issues are likely to be relevant in similar jurisdictions.Main textDecision-making capacity is a private attribute, and patients may not necessarily be aware that one of their personal abilities is being explored. Routine exploration of capacity has not historically been a part of psychiatric examination, (...)
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  • Justice and empowerment through digital health: ethical challenges and opportunities.Philip J. Nickel, Iris Loosman, Lily Frank & Anna Vinnikova - 2023 - Digital Society 2.
    The proposition that digital innovations can put people in charge of their health has been accompanied by prolific talk of empowerment. In this paper we consider ethical challenges and opportunities of trying to achieve justice and empowerment using digital health initiatives. The language of empowerment can misleadingly suggest that by using technology, people can control their health and take responsibility for health outcomes to a greater degree than is realistic or fair. Also, digital health empowerment often primarily reaches people who (...)
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  • Consequences of unexplainable machine learning for the notions of a trusted doctor and patient autonomy.Michal Klincewicz & Lily Frank - 2020 - Proceedings of the 2nd EXplainable AI in Law Workshop (XAILA 2019) Co-Located with 32nd International Conference on Legal Knowledge and Information Systems (JURIX 2019).
    This paper provides an analysis of the way in which two foundational principles of medical ethics–the trusted doctor and patient autonomy–can be undermined by the use of machine learning (ML) algorithms and addresses its legal significance. This paper can be a guide to both health care providers and other stakeholders about how to anticipate and in some cases mitigate ethical conflicts caused by the use of ML in healthcare. It can also be read as a road map as to what (...)
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