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  1. Opening the Door: Rethinking “Difficult Conversations” about Living and Dying with Dementia.Mara Buchbinder & Nancy Berlinger - 2024 - Hastings Center Report 54 (S1):22-28.
    This essay looks closely at metaphors and other figures of speech that often feature in how Americans talk about dementia, becoming part of cultural narratives: shared stories that convey ideas and values, and also worries and fears. It uses approaches from literary studies to analyze how cultural narratives about dementia may surface in conversations with family members or health care professionals. This essay also draws on research on a notable social effect of legalizing medical aid in dying: patients may find (...)
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  • What Counts as “Clinical Data” in Machine Learning Healthcare Applications?Joshua August Skorburg - 2020 - American Journal of Bioethics 20 (11):27-30.
    Peer commentary on Char, Abràmoff & Feudtner (2020) target article: "Identifying Ethical Considerations for Machine Learning Healthcare Applications" .
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  • Using Artificial Intelligence in Patient Care—Some Considerations for Doctors and Medical Regulators.Kanny Ooi - 2024 - Asian Bioethics Review 16 (3):483-499.
    This paper discusses the key role medical regulators have in setting standards for doctors who use artificial intelligence (AI) in patient care. Given their mandate to protect public health and safety, it is incumbent on regulators to guide the profession on emerging and vexed areas of practice such as AI. However, formulating effective and robust guidance in a novel field is challenging particularly as regulators are navigating unfamiliar territory. As such, regulators themselves will need to understand what AI is and (...)
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  • Identifying Ethical Considerations for Machine Learning Healthcare Applications.Danton S. Char, Michael D. Abràmoff & Chris Feudtner - 2020 - American Journal of Bioethics 20 (11):7-17.
    Along with potential benefits to healthcare delivery, machine learning healthcare applications raise a number of ethical concerns. Ethical evaluations of ML-HCAs will need to structure th...
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  • Deep Ethical Learning: Taking the Interplay of Human and Artificial Intelligence Seriously.Anita Ho - 2019 - Hastings Center Report 49 (1):36-39.
    From predicting medical conditions to administering health behavior interventions, artificial intelligence technologies are being developed to enhance patient care and outcomes. However, as Mélanie Terrasse and coauthors caution in an article in this issue of the Hastings Center Report, an overreliance on virtual technologies may depersonalize medical interactions and erode therapeutic relationships. The increasing expectation that patients will be actively engaged in their own care, regardless of the patients’ desire, technological literacy, and economic means, may also violate patients’ autonomy 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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  • Primer on an ethics of AI-based decision support systems in the clinic.Matthias Braun, Patrik Hummel, Susanne Beck & Peter Dabrock - 2021 - Journal of Medical Ethics 47 (12):3-3.
    Making good decisions in extremely complex and difficult processes and situations has always been both a key task as well as a challenge in the clinic and has led to a large amount of clinical, legal and ethical routines, protocols and reflections in order to guarantee fair, participatory and up-to-date pathways for clinical decision-making. Nevertheless, the complexity of processes and physical phenomena, time as well as economic constraints and not least further endeavours as well as achievements in medicine and healthcare (...)
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  • Addressing the “Wicked” Problems in Machine Learning Applications – Time for Bioethical Agility.Junaid Nabi - 2020 - American Journal of Bioethics 20 (11):25-27.
    “I think we should be very careful about artificial intelligence. If I had to guess at what our biggest existential threat is, it’s probably that.” Elon Musk AeroAstro Centennial Symposium Massachu...
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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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  • Designing Regulatory Frameworks for Machine Learning Systems in Medicine—Time for Balance and Practicality.Junaid Nabi & Tawheed Makhdoomi - 2024 - American Journal of Bioethics 24 (10):91-93.
    Volume 24, Issue 10, October 2024, Page 91-93.
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