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  1. Explainability, Public Reason, and Medical Artificial Intelligence.Michael Da Silva - 2023 - Ethical Theory and Moral Practice 26 (5):743-762.
    The contention that medical artificial intelligence (AI) should be ‘explainable’ is widespread in contemporary philosophy and in legal and best practice documents. Yet critics argue that ‘explainability’ is not a stable concept; non-explainable AI is often more accurate; mechanisms intended to improve explainability do not improve understanding and introduce new epistemic concerns; and explainability requirements are ad hoc where human medical decision-making is often opaque. A recent ‘political response’ to these issues contends that AI used in high-stakes scenarios, including medical (...)
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  • Philosophy of science at sea: Clarifying the interpretability of machine learning.Claus Beisbart & Tim Räz - 2022 - Philosophy Compass 17 (6):e12830.
    Philosophy Compass, Volume 17, Issue 6, June 2022.
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  • “Just” accuracy? Procedural fairness demands explainability in AI‑based medical resource allocation.Jon Rueda, Janet Delgado Rodríguez, Iris Parra Jounou, Joaquín Hortal-Carmona, Txetxu Ausín & David Rodríguez-Arias - 2022 - AI and Society:1-12.
    The increasing application of artificial intelligence (AI) to healthcare raises both hope and ethical concerns. Some advanced machine learning methods provide accurate clinical predictions at the expense of a significant lack of explainability. Alex John London has defended that accuracy is a more important value than explainability in AI medicine. In this article, we locate the trade-off between accurate performance and explainable algorithms in the context of distributive justice. We acknowledge that accuracy is cardinal from outcome-oriented justice because it helps (...)
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  • On the Ethical and Epistemological Utility of Explicable AI in Medicine.Christian Herzog - 2022 - Philosophy and Technology 35 (2):1-31.
    In this article, I will argue in favor of both the ethical and epistemological utility of explanations in artificial intelligence -based medical technology. I will build on the notion of “explicability” due to Floridi, which considers both the intelligibility and accountability of AI systems to be important for truly delivering AI-powered services that strengthen autonomy, beneficence, and fairness. I maintain that explicable algorithms do, in fact, strengthen these ethical principles in medicine, e.g., in terms of direct patient–physician contact, as well (...)
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  • The virtues of interpretable medical artificial intelligence.Joshua Hatherley, Robert Sparrow & Mark Howard - forthcoming - Cambridge Quarterly of Healthcare Ethics:1-10.
    Artificial intelligence (AI) systems have demonstrated impressive performance across a variety of clinical tasks. However, notoriously, sometimes these systems are 'black boxes'. The initial response in the literature was a demand for 'explainable AI'. However, recently, several authors have suggested that making AI more explainable or 'interpretable' is likely to be at the cost of the accuracy of these systems and that prioritising interpretability in medical AI may constitute a 'lethal prejudice'. In this paper, we defend the value of interpretability (...)
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