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  1. (1 other version)Creating a large language model of a philosopher.Eric Schwitzgebel, David Schwitzgebel & Anna Strasser - 2023 - Mind and Language 39 (2):237-259.
    Can large language models produce expert‐quality philosophical texts? To investigate this, we fine‐tuned GPT‐3 with the works of philosopher Daniel Dennett. To evaluate the model, we asked the real Dennett 10 philosophical questions and then posed the same questions to the language model, collecting four responses for each question without cherry‐picking. Experts on Dennett's work succeeded at distinguishing the Dennett‐generated and machine‐generated answers above chance but substantially short of our expectations. Philosophy blog readers performed similarly to the experts, while ordinary (...)
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  • How to Use AI Ethically for Ethical Decision-Making.Joanna Demaree-Cotton, Brian D. Earp & Julian Savulescu - 2022 - American Journal of Bioethics 22 (7):1-3.
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  • The Artificial Moral Advisor. The “Ideal Observer” Meets Artificial Intelligence.Alberto Giubilini & Julian Savulescu - 2018 - Philosophy and Technology 31 (2):169-188.
    We describe a form of moral artificial intelligence that could be used to improve human moral decision-making. We call it the “artificial moral advisor”. The AMA would implement a quasi-relativistic version of the “ideal observer” famously described by Roderick Firth. We describe similarities and differences between the AMA and Firth’s ideal observer. Like Firth’s ideal observer, the AMA is disinterested, dispassionate, and consistent in its judgments. Unlike Firth’s observer, the AMA is non-absolutist, because it would take into account the human (...)
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  • Use of a Patient Preference Predictor to Help Make Medical Decisions for Incapacitated Patients.A. Rid & D. Wendler - 2014 - Journal of Medicine and Philosophy 39 (2):104-129.
    The standard approach to treatment decision making for incapacitated patients often fails to provide treatment consistent with the patient’s preferences and values and places significant stress on surrogate decision makers. These shortcomings provide compelling reason to search for methods to improve current practice. Shared decision making between surrogates and clinicians has important advantages, but it does not provide a way to determine patients’ treatment preferences. Hence, shared decision making leaves families with the stressful challenge of identifying the patient’s preferred treatment (...)
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  • Ethics of generative AI.Hazem Zohny, John McMillan & Mike King - 2023 - Journal of Medical Ethics 49 (2):79-80.
    Artificial intelligence (AI) and its introduction into clinical pathways presents an array of ethical issues that are being discussed in the JME. 1–7 The development of AI technologies that can produce text that will pass plagiarism detectors 8 and are capable of appearing to be written by a human author 9 present new issues for medical ethics. One set of worries concerns authorship and whether it will now be possible to know that an author or student in fact produced submitted (...)
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  • Health Research Priority Setting: State Obligations and the Human Right to Science.Sebastian Porsdam Mann & Maximillian M. Schmid - 2018 - American Journal of Bioethics 18 (11):33-35.
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  • Neuroreductionism about sex and love.Brian D. Earp & Julian Savulescu - unknown
    "Neuroreductionism" is the tendency to reduce complex mental phenomena to brain states, confusing correlation for physical causation. In this paper, we illustrate the dangers of this popular neuro-fallacy, by looking at an example drawn from the media: a story about "hypoactive sexual desire disorder" in women. We discuss the role of folk dualism in perpetuating such a confusion, and draw some conclusions about the role of "brain scans" in our understanding of romantic love.
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  • Blockchain, consent and prosent for medical research.Sebastian Porsdam Mann, Julian Savulescu, Philippe Ravaud & Mehdi Benchoufi - 2021 - Journal of Medical Ethics 47 (4):244-250.
    Recent advances in medical and information technologies, the availability of new types of medical data, the requirement of increasing numbers of study participants, as well as difficulties in recruitment and retention, all present serious problems for traditional models of specific and informed consent to medical research. However, these advances also enable novel ways to securely share and analyse data. This paper introduces one of these advances—blockchain technologies—and argues that they can be used to share medical data in a secure and (...)
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