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  1. Algorithms for Ethical Decision-Making in the Clinic: A Proof of Concept.Lukas J. Meier, Alice Hein, Klaus Diepold & Alena Buyx - 2022 - American Journal of Bioethics 22 (7):4-20.
    Machine intelligence already helps medical staff with a number of tasks. Ethical decision-making, however, has not been handed over to computers. In this proof-of-concept study, we show how an algorithm based on Beauchamp and Childress’ prima-facie principles could be employed to advise on a range of moral dilemma situations that occur in medical institutions. We explain why we chose fuzzy cognitive maps to set up the advisory system and how we utilized machine learning to train it. We report on the (...)
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  • Ethical artificial intelligence framework for a good AI society: principles, opportunities and perils.Pradeep Paraman & Sanmugam Anamalah - forthcoming - AI and Society:1-17.
    The justification and rationality of this paper is to present some fundamental principles, theories, and concepts that we believe moulds the nucleus of a good artificial intelligence society. The morally accepted significance and utilitarian concerns that stems from the inception and realisation of an AI’s structural foundation are displayed in this study. This paper scrutinises the structural foundation, fundamentals, and cardinal righteous remonstrations, as well as the gaps in mechanisms towards novel prospects and perils in determining resilient fundamentals, accountability, and (...)
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  • Karl Jaspers and Artificial Neural Nets: On the Relation of Explaining and Understanding Artificial Intelligence in Medicine.Christopher Poppe & Georg Starke - 2022 - Ethics and Information Technology 24 (3).
    Assistive systems based on Artificial Intelligence are bound to reshape decision-making in all areas of society. One of the most intricate challenges arising from their implementation in high-stakes environments such as medicine concerns their frequently unsatisfying levels of explainability, especially in the guise of the so-called black-box problem: highly successful models based on deep learning seem to be inherently opaque, resisting comprehensive explanations. This may explain why some scholars claim that research should focus on rendering AI systems understandable, rather than (...)
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  • Research on the Clinical Translation of Health Care Machine Learning: Ethicists Experiences on Lessons Learned.Jennifer Blumenthal-Barby, Benjamin Lang, Natalie Dorfman, Holland Kaplan, William B. Hooper & Kristin Kostick-Quenet - 2022 - American Journal of Bioethics 22 (5):1-3.
    The application of machine learning in health care holds great promise for improving care. Indeed, our own team is collaborating with experts in machine learning and statistical modeling to bu...
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  • When Doctors and AI Interact: on Human Responsibility for Artificial Risks.Mario Verdicchio & Andrea Perin - 2022 - Philosophy and Technology 35 (1):1-28.
    A discussion concerning whether to conceive Artificial Intelligence systems as responsible moral entities, also known as “artificial moral agents”, has been going on for some time. In this regard, we argue that the notion of “moral agency” is to be attributed only to humans based on their autonomy and sentience, which AI systems lack. We analyze human responsibility in the presence of AI systems in terms of meaningful control and due diligence and argue against fully automated systems in medicine. With (...)
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  • Responsibility, Second Opinions and Peer-Disagreement: Ethical and Epistemological Challenges of Using AI in Clinical Diagnostic Contexts.Hendrik Kempt & Saskia K. Nagel - 2022 - Journal of Medical Ethics 48 (4):222-229.
    In this paper, we first classify different types of second opinions and evaluate the ethical and epistemological implications of providing those in a clinical context. Second, we discuss the issue of how artificial intelligent could replace the human cognitive labour of providing such second opinion and find that several AI reach the levels of accuracy and efficiency needed to clarify their use an urgent ethical issue. Third, we outline the normative conditions of how AI may be used as second opinion (...)
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  • “I’m afraid I can’t let you do that, Doctor”: meaningful disagreements with AI in medical contexts.Hendrik Kempt, Jan-Christoph Heilinger & Saskia K. Nagel - forthcoming - AI and Society:1-8.
    This paper explores the role and resolution of disagreements between physicians and their diagnostic AI-based decision support systems. With an ever-growing number of applications for these independently operating diagnostic tools, it becomes less and less clear what a physician ought to do in case their diagnosis is in faultless conflict with the results of the DSS. The consequences of such uncertainty can ultimately lead to effects detrimental to the intended purpose of such machines, e.g. by shifting the burden of proof (...)
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  • Four Responsibility Gaps with Artificial Intelligence: Why They Matter and How to Address Them.Filippo Santoni de Sio & Giulio Mecacci - 2021 - Philosophy and Technology 34 (4):1057-1084.
    The notion of “responsibility gap” with artificial intelligence was originally introduced in the philosophical debate to indicate the concern that “learning automata” may make more difficult or impossible to attribute moral culpability to persons for untoward events. Building on literature in moral and legal philosophy, and ethics of technology, the paper proposes a broader and more comprehensive analysis of the responsibility gap. The responsibility gap, it is argued, is not one problem but a set of at least four interconnected problems (...)
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  • Teasing Out Artificial Intelligence in Medicine: An Ethical Critique of Artificial Intelligence and Machine Learning in Medicine.Mark Henderson Arnold - 2021 - Journal of Bioethical Inquiry 18 (1):121-139.
    The rapid adoption and implementation of artificial intelligence in medicine creates an ontologically distinct situation from prior care models. There are both potential advantages and disadvantages with such technology in advancing the interests of patients, with resultant ontological and epistemic concerns for physicians and patients relating to the instatiation of AI as a dependent, semi- or fully-autonomous agent in the encounter. The concept of libertarian paternalism potentially exercised by AI has created challenges to conventional assessments of patient and physician autonomy. (...)
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  • 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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