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  1.  89
    On the Ethics of Algorithmic Decision-Making in Healthcare.Thomas Grote & Philipp Berens - 2020 - Journal of Medical Ethics 46 (3):205-211.
    In recent years, a plethora of high-profile scientific publications has been reporting about machine learning algorithms outperforming clinicians in medical diagnosis or treatment recommendations. This has spiked interest in deploying relevant algorithms with the aim of enhancing decision-making in healthcare. In this paper, we argue that instead of straightforwardly enhancing the decision-making capabilities of clinicians and healthcare institutions, deploying machines learning algorithms entails trade-offs at the epistemic and the normative level. Whereas involving machine learning might improve the accuracy of medical (...)
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  2. On Algorithmic Fairness in Medical Practice.Thomas Grote & Geoff Keeling - 2022 - Cambridge Quarterly of Healthcare Ethics 31 (1):83-94.
    The application of machine-learning technologies to medical practice promises to enhance the capabilities of healthcare professionals in the assessment, diagnosis, and treatment, of medical conditions. However, there is growing concern that algorithmic bias may perpetuate or exacerbate existing health inequalities. Hence, it matters that we make precise the different respects in which algorithmic bias can arise in medicine, and also make clear the normative relevance of these different kinds of algorithmic bias for broader questions about justice and fairness in healthcare. (...)
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  3.  3
    Randomized Controlled Trials in Medical AI.Konstantin Genin & Thomas Grote - 2021 - Philosophy of Medicine 2 (1).
    Various publications claim that medical AI systems perform as well, or better, than clinical experts. However, there have been very few controlled trials and the quality of existing studies has been called into question. There is growing concern that existing studies overestimate the clinical benefits of AI systems. This has led to calls for more, and higher-quality, randomized controlled trials of medical AI systems. While this a welcome development, AI RCTs raise novel methodological challenges that have seen little discussion. We (...)
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  4.  12
    Randomised Controlled Trials in Medical AI: Ethical Considerations.Thomas Grote - forthcoming - Journal of Medical Ethics:medethics-2020-107166.
    In recent years, there has been a surge of high-profile publications on applications of artificial intelligence systems for medical diagnosis and prognosis. While AI provides various opportunities for medical practice, there is an emerging consensus that the existing studies show considerable deficits and are unable to establish the clinical benefit of AI systems. Hence, the view that the clinical benefit of AI systems needs to be studied in clinical trials—particularly randomised controlled trials —is gaining ground. However, an issue that has (...)
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  5.  7
    Can Robots Do Epidemiology? Machine Learning, Causal Inference, and Predicting the Outcomes of Public Health Interventions.Alex Broadbent & Thomas Grote - 2022 - Philosophy and Technology 35 (1):1-22.
    This paper argues that machine learning and epidemiology are on collision course over causation. The discipline of epidemiology lays great emphasis on causation, while ML research does not. Some epidemiologists have proposed imposing what amounts to a causal constraint on ML in epidemiology, requiring it either to engage in causal inference or restrict itself to mere projection. We whittle down the issues to the question of whether causal knowledge is necessary for underwriting predictions about the outcomes of public health interventions. (...)
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  6.  27
    Trustworthy Medical AI Systems Need to Know When They Don’T Know.Thomas Grote - 2021 - Journal of Medical Ethics 47 (5):337-338.
    There is much to learn from Durán and Jongsma’s paper.1 One particularly important insight concerns the relationship between epistemology and ethics in medical artificial intelligence. In clinical environments, the task of AI systems is to provide risk estimates or diagnostic decisions, which then need to be weighed by physicians. Hence, while the implementation of AI systems might give rise to ethical issues—for example, overtreatment, defensive medicine or paternalism2—the issue that lies at the heart is an epistemic problem: how can physicians (...)
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  7.  43
    Review of Elijah Milgram: The Great Endarkenment – Philosophy for an Age of Hyperspecialization: Oxford/New York: OUP, 2015. ISBN: 978019-932602-0. £41.99. [REVIEW]Thomas Grote - 2016 - Ethical Theory and Moral Practice 19 (4):1047-1048.
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  8.  4
    How Competitors Become Collaborators—Bridging the Gap(s) Between Machine Learning Algorithms and Clinicians.Thomas Grote & Philipp Berens - 2022 - Wiley: Bioethics 36 (2):134-142.
    Bioethics, Volume 36, Issue 2, Page 134-142, February 2022.
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  9.  21
    Berit Brogaard: On Romantic Love: Simple Truths About a Complex Emotion, Oxford University Press, 2015. 288 Pages Hardcover $ 21.95 ISBN: 9780199370733. [REVIEW]Thomas Grote - 2016 - Ethical Theory and Moral Practice 19 (1):281-283.
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  10.  14
    James F. Keenan , University Ethics: How Universities Can Build and Benefit From a Culture of Ethics: London/New York: Rowman & Littlefield. ISBN: 978-1-4422-2372-1; £23, 95.Thomas Grote - 2016 - Ethical Theory and Moral Practice 19 (5):1329-1330.
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