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  1. Should the use of adaptive machine learning systems in medicine be classified as research?Robert Sparrow, Joshua Hatherley, Justin Oakley & Chris Bain - 2024 - American Journal of Bioethics 24 (10):58-69.
    A novel advantage of the use of machine learning (ML) systems in medicine is their potential to continue learning from new data after implementation in clinical practice. To date, considerations of the ethical questions raised by the design and use of adaptive machine learning systems in medicine have, for the most part, been confined to discussion of the so-called “update problem,” which concerns how regulators should approach systems whose performance and parameters continue to change even after they have received regulatory (...)
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  • Below the Surface of Clinical Ethics.J. Clint Parker - 2023 - Journal of Medicine and Philosophy 48 (1):1-11.
    Often lurking below the surface of many clinical ethical issues are questions regarding background metaphysical, epistemological, meta-ethical, and political beliefs. In this issue, authors critically examine the effects of background beliefs on conscientious objection, explore ethical issues through the lenses of particular theoretical approaches like pragmatism and intersectional theory, rigorously explore the basic concepts at play within the patient safety movement, offer new theoretical approaches to old problems involving decision making for patients with dementia, explicate and explore the problems and (...)
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  • Scoping Review Shows the Dynamics and Complexities Inherent to the Notion of “Responsibility” in Artificial Intelligence within the Healthcare Context.Sarah Bouhouita-Guermech & Hazar Haidar - 2024 - Asian Bioethics Review 16 (3):315-344.
    The increasing integration of artificial intelligence (AI) in healthcare presents a host of ethical, legal, social, and political challenges involving various stakeholders. These challenges prompt various studies proposing frameworks and guidelines to tackle these issues, emphasizing distinct phases of AI development, deployment, and oversight. As a result, the notion of responsible AI has become widespread, incorporating ethical principles such as transparency, fairness, responsibility, and privacy. This paper explores the existing literature on AI use in healthcare to examine how it addresses, (...)
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  • The impact of digital health technologies on moral responsibility: a scoping review.E. Meier, T. Rigter, M. P. Schijven, M. van den Hoven & M. A. R. Bak - forthcoming - Medicine, Health Care and Philosophy:1-15.
    Recent publications on digital health technologies highlight the importance of ‘responsible’ use. References to the concept of responsibility are, however, frequently made without providing clear definitions of responsibility, thus leaving room for ambiguities. Addressing these uncertainties is critical since they might lead to misunderstandings, impacting the quality and safety of healthcare delivery. Therefore, this study investigates how responsibility is interpreted in the context of using digital health technologies, including artificial intelligence (AI), telemonitoring, wearables and mobile apps. We conducted a scoping (...)
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  • Bioethical Boundaries, Critiques of Current Paradigms, and the Importance of Transparency.J. Clint Parker - 2022 - Journal of Medicine and Philosophy 47 (1):1-17.
    This issue of The Journal of Medicine and Philosophy is dedicated to topics in clinical ethics with essays addressing clinician participation in state sponsored execution, duties to decrease ecological footprints in medicine, the concept of caring and its relationship to conscientious refusal, the dilemmas involved in dual use research, a philosophical and practical critique of principlism, conundrums that arise when applying surrogate decision-making models to patients with moderate intellectual disabilities, the phenomenology of chronic disease, and ethical concerns surrounding the use (...)
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