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  1. The ethical canary: narrow reflective equilibrium as a source of moral justification in healthcare priority-setting.Victoria Charlton & Michael J. DiStefano - forthcoming - Journal of Medical Ethics.
    Healthcare priority-setting institutions have good reason to want to demonstrate that their decisions are morally justified—and those who contribute to and use the health service have good reason to hope for the same. However, finding a moral basis on which to evaluate healthcare priority-setting is difficult. Substantive approaches are vulnerable to reasonable disagreement about the appropriate grounds for allocating resources, while procedural approaches may be indeterminate and insufficient to ensure a just distribution. In this paper, we set out a complementary, (...)
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  • An empirical ethics study of the coherence of NICE technology appraisal policy and its implications for moral justification.Victoria Charlton & Michael DiStefano - 2024 - BMC Medical Ethics 25 (1):1-22.
    Background As the UK’s main healthcare priority-setter, the National Institute for Health and Care Excellence (NICE) has good reason to want to demonstrate that its decisions are morally justified. In doing so, it has tended to rely on the moral plausibility of its principle of cost-effectiveness and the assertion that it has adopted a fair procedure. But neither approach provides wholly satisfactory grounds for morally defending NICE’s decisions. In this study we adopt a complementary approach, based on the proposition that (...)
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  • Democratizing Algorithmic Fairness.Pak-Hang Wong - 2020 - Philosophy and Technology 33 (2):225-244.
    Algorithms can now identify patterns and correlations in the (big) datasets, and predict outcomes based on those identified patterns and correlations with the use of machine learning techniques and big data, decisions can then be made by algorithms themselves in accordance with the predicted outcomes. Yet, algorithms can inherit questionable values from the datasets and acquire biases in the course of (machine) learning, and automated algorithmic decision-making makes it more difficult for people to see algorithms as biased. While researchers have (...)
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  • Publish or be damned: Individual Funding Requests and the publicity condition.Monique Jonas, Anne Kolbe & Briar Warin - 2014 - Journal of Medical Ethics 40 (12):827-831.
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  • Hammer or Measuring Tape? Artificial Intelligence and Justice in Healthcare.Jan-Hendrik Heinrichs - forthcoming - Cambridge Quarterly of Healthcare Ethics:1-12.
    Artificial intelligence (AI) is a powerful tool for several healthcare tasks. AI tools are suited to optimize predictive models in medicine. Ethical debates about AI’s extension of the predictive power of medical models suggest a need to adapt core principles of medical ethics. This article demonstrates that a popular interpretation of the principle of justice in healthcare needs amendment given the effect of AI on decision-making. The procedural approach to justice, exemplified with Norman Daniels and James Sabin’saccountability for reasonablenessconception, needs (...)
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  • Accountability for reasonableness: the relevance, or not, of exceptionality in resource allocation.Amy Ford - 2015 - Medicine, Health Care and Philosophy 18 (2):217-227.
    Accountability for Reasonableness has gained international acceptance as a framework to assist with resource allocation within healthcare. Despite this, one of the four conditions, the relevance condition, has not been widely adopted. In this paper I will start by examining the relevance condition, and the constraints placed on it by Daniels and Sabin. Following this, I review the theoretical limitations of the condition identified to date, by prominent critics such as Rid, Friedman, Lauridsen and Lippert—Rasmussen. Finally, I respond to Daniels (...)
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