How Should Clinical Ethics Evolve to Ensure Moral Use of AI?
Artificial intelligence is reshaping clinical decision-making in ways that challenge assumptions about patient-centered care, moral responsibility, and professional judgment. Encoding Bioethics: AI in Clinical Decision-Making, by Charles Binkley and Tyler Loftus, begins where ethical reflection on t...
| 主要作者: | |
|---|---|
| 格式: | 電子 Review |
| 語言: | English |
| Check availability: | HBZ Gateway |
| Interlibrary Loan: | Interlibrary Loan for the Fachinformationsdienste (Specialized Information Services in Germany) |
| 出版: |
2026
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| In: |
The Hastings Center report
Year: 2026, 卷: 56, 發布: 1, Pages: 47-49 |
| Further subjects: | B
書評
B algorithmic decision-making B Bioethics B artificial intelligence in health care B clinical ethics B implementation science |
| 在線閱讀: |
Presumably Free Access Volltext (lizenzpflichtig) Volltext (lizenzpflichtig) |
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| 520 | |a Artificial intelligence is reshaping clinical decision-making in ways that challenge assumptions about patient-centered care, moral responsibility, and professional judgment. Encoding Bioethics: AI in Clinical Decision-Making, by Charles Binkley and Tyler Loftus, begins where ethical reflection on this topic should begin—in the trenches of clinical care. Together with the National Academy of Medicine's publication An Artificial Intelligence Code of Conduct for Health and Medicine: Essential Guidance for Aligned Action, which came out after the book, Encoding Bioethics goes a long way toward offering physicians, patients, developers, and health-system leaders actionable guidance. Through explanation, probing questions, and case studies, Binkley and Loftus illuminate the ethical difficulties posed by opacity, bias, and shifting clinical roles. Yet their analysis stops short of identifying the governance tools and operational structures that are essential for achieving patient-centered, morally responsible AI that strengthens clinical judgment. This review essay argues that bridging ethics and practice requires attention to psychological safety, organizational dynamics, and implementation science to ensure that AI supports—not supplants—ethical care. | ||
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