- Reflections on Putting AI Ethics into Practice: How Three AI Ethics Approaches Conceptualize Theory and Practice.Hannah Bleher & Matthias Braun - 2023 - Science and Engineering Ethics 29 (3):1-21.details
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Levels of explicability for medical artificial intelligence: What do we normatively need and what can we technically reach?Frank Ursin, Felix Lindner, Timo Ropinski, Sabine Salloch & Cristian Timmermann - 2023 - Ethik in der Medizin 35 (2):173-199.details
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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.details
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The Future Ethics of Artificial Intelligence in Medicine: Making Sense of Collaborative Models.Torbjørn Gundersen & Kristine Bærøe - 2022 - Science and Engineering Ethics 28 (2):1-16.details
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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.details
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Towards a pragmatist dealing with algorithmic bias in medical machine learning.Georg Starke, Eva De Clercq & Bernice S. Elger - 2021 - Medicine, Health Care and Philosophy 24 (3):341-349.details
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It is Time for Bioethicists to Enter the Arena of Machine Learning Ethics.Michaela Hardt & Marshall H. Chin - 2020 - American Journal of Bioethics 20 (11):18-20.details
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Structural Disparities in Data Science: A Prolegomenon for the Future of Machine Learning.Niranjan S. Karnik, Majid Afshar, Matthew M. Churpek & Marcella Nunez-Smith - 2020 - American Journal of Bioethics 20 (11):35-37.details
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Respect and Trustworthiness in the Patient-Provider-Machine Relationship: Applying a Relational Lens to Machine Learning Healthcare Applications.Stephanie A. Kraft - 2020 - American Journal of Bioethics 20 (11):51-53.details
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Addressing the “Wicked” Problems in Machine Learning Applications – Time for Bioethical Agility.Junaid Nabi - 2020 - American Journal of Bioethics 20 (11):25-27.details
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An Evaluation of the Pipeline Framework for Ethical Considerations in Machine Learning Healthcare Applications: The Case of Prediction from Functional Neuroimaging Data.Dawson J. Overton - 2020 - American Journal of Bioethics 20 (11):56-58.details
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What Counts as “Clinical Data” in Machine Learning Healthcare Applications?Joshua August Skorburg - 2020 - American Journal of Bioethics 20 (11):27-30.details
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Is the Algorithm Good in a Bad World, or Has It Learned to be Bad? The Ethical Challenges of “Locked” Versus “Continuously Learning” and “Autonomous” Versus “Assistive” AI Tools in Healthcare.Alaa Youssef, Michael Abramoff & Danton Char - 2023 - American Journal of Bioethics 23 (5):43-45.details
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Challenges of Local Ethics Review in a Global Healthcare AI Market.Danton Char - 2022 - American Journal of Bioethics 22 (5):39-41.details
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Deepening the Normative Evaluation of Machine Learning Healthcare Application by Complementing Ethical Considerations with Regulatory Governance.Calvin Wai-Loon Ho - 2020 - American Journal of Bioethics 20 (11):43-45.details
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The ethics of machine learning-based clinical decision support: an analysis through the lens of professionalisation theory.Sabine Salloch & Nils B. Heyen - 2021 - BMC Medical Ethics 22 (1):1-9.details
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Where Bioethics Meets Machine Ethics.Anna C. F. Lewis - 2020 - American Journal of Bioethics 20 (11):22-24.details
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Important Design Questions for Algorithmic Ethics Consultation.Danton Char - 2022 - American Journal of Bioethics 22 (7):38-40.details
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Randomised controlled trials in medical AI: ethical considerations.Thomas Grote - 2022 - Journal of Medical Ethics 48 (11):899-906.details
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Machine Learning Healthcare Applications (ML-HCAs) Are No Stand-Alone Systems but Part of an Ecosystem – A Broader Ethical and Health Technology Assessment Approach is Needed.Helene Gerhards, Karsten Weber, Uta Bittner & Heiner Fangerau - 2020 - American Journal of Bioethics 20 (11):46-48.details
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Scoping Review Shows the Dynamics and Complexities Inherent to the Notion of “Responsibility” in Artificial Intelligence within the Healthcare Context.Sarah Bouhouita-Guermech & Hazar Haidar - forthcoming - Asian Bioethics Review:1-30.details
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Accountability in the Machine Learning Pipeline: The Critical Role of Research Ethics Oversight.Melissa D. McCradden, James A. Anderson & Randi Zlotnik Shaul - 2020 - American Journal of Bioethics 20 (11):40-42.details
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Machine Learning in Healthcare: Exceptional Technologies Require Exceptional Ethics.Kristine Bærøe, Maarten Jansen & Angeliki Kerasidou - 2020 - American Journal of Bioethics 20 (11):48-51.details
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Embedded Ethics Could Help Implement the Pipeline Model Framework for Machine Learning Healthcare Applications.Amelia Fiske, Daniel Tigard, Ruth Müller, Sami Haddadin, Alena Buyx & Stuart McLennan - 2020 - American Journal of Bioethics 20 (11):32-35.details
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What’s in the Box?: Uncertain Accountability of Machine Learning Applications in Healthcare.Ma'N. Zawati & Michael Lang - 2020 - American Journal of Bioethics 20 (11):37-40.details
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An Ethical Framework to Nowhere.Eric S. Swirsky, Carol Gu & Andrew D. Boyd - 2020 - American Journal of Bioethics 20 (11):30-32.details
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Keeping the Patient at the Center of Machine Learning in Healthcare.Jess Findley, Andrew Woods, Christopher Robertson & Marv Slepian - 2020 - American Journal of Bioethics 20 (11):54-56.details
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AI Ethics Is Not a Panacea.Stuart McLennan, Meredith M. Lee, Amelia Fiske & Leo Anthony Celi - 2020 - American Journal of Bioethics 20 (11):20-22.details
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