The Debate on the Ethics of AI in Health Care: a Reconstruction and Critical Review
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AI can offer computational assistance for complex clinical decisions such as CPR and DNAR status that aligns with patient preferences while mitigating human biases under stress and time pressure.
“In scenarios like cardio-pulmonary resuscitation and determining Do Not Attempt to Resuscitate (DNAR) status, AI can offer computational assistance that aligns with patient preferences while mitigating human biases in decision-making under stress and time pressure [4][5][6].”
From Balancing Privacy and Progress: A Review of Privacy Challenges, Systemic Oversight, and Patient Perceptions in AI-Driven Healthcare (2024) · cites this paper as [4]
AI systems have shown proficiency in structuring vast medical data, identifying clinical patterns, and validating medical hypotheses.
“For instance, AI systems have shown remarkable proficiency in structuring vast medical data, identifying clinical patterns, and validating medical hypotheses.”
From Balancing Privacy and Progress: A Review of Privacy Challenges, Systemic Oversight, and Patient Perceptions in AI-Driven Healthcare (2024) · cites this paper as [4]
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Self-citation
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ARTIFICIAL INTELLIGENCE IN PRIMARY CARE - THREAT OR SUPPORT FOR THE GENERAL PRACTITIONER?
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- Authors
- Morley, J., Machado, C., Burr, C., Cowls, J., Taddeo, M., & Floridi, L.
- Affiliations
- University of Oxford (GB)
- Corresponding author
- Morley, Jessica
- Venue
- SSRN Electronic Journal
- Publisher
- Elsevier BV
- Published
- 2019
- ISSN
- 1556-5068 (ISSN-L)
- OpenAlex
- W3003851578
- Cited by
- 66
- References
- 158
- Citations by year
- 2026: 3 · 2025: 11 · 2024: 11 · 2023: 4 · 2022: 19 · 2021: 10 · 2020: 8
- Type
- posted content
- Language
- en
- Open access
- green
- doi.org
- Locations
- SSRN Electronic Journal (publishedVersion)
- PhilPapers (PhilPapers Foundation) (submittedVersion)
- Funders
- Engineering and Physical Sciences Research Council (EP/N023013/1)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Ethics and bioethics in healthcare
- Keywords
- artificial intelligence in healthcare, machine learning, AI ethics, ethical frameworks, regulatory framework, legal framework, AI governance, healthcare automation, epistemic ethics, normative ethics, social ethics, healthcare policy
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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