ArticleJournal of the American Medical Informatics Association : JAMIA2021
Public vs physician views of liability for artificial intelligence in health care.
Article in Journal of the American Medical Informatics Association : JAMIA, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
29 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Opportunities and challenges of artificial intelligence in public health: a systematic review on technological efficacy, ethical dilemmas, and governance pathways.Frontiers in public health · 2025Pooled it
- Artificial Intelligence (AI) and Healthcare Capabilities: A Systematic Review and Research Directions.F1000Research · 2025Pooled it
- Artificial Intelligence and the Ethical Foundations of Cardiothoracic Surgery: Evidence, Accountability, and the Limits of Delegated Judgment.Medical sciences (Basel, Switzerland) · 2026Review
- Primary Care Doctors' Perspectives and Experiences With a Chest X-Ray AI Triage Program: Qualitative Study.Journal of medical Internet research · 2026Article
- From Assistance to Autonomy: Acceptability of Progressive Artificial Intelligence Integration in Facial Reconstructive Surgery-Protocol for Within-Subjects Vignette Experiment Among Romanian Adults.Healthcare (Basel, Switzerland) · 2026Article
- From Algorithm to Policy: A Bibliometric Analysis of Implementation Science and Governance Frameworks in AI Healthcare Research (2016-2026).Healthcare (Basel, Switzerland) · 2026Review
- Beyond Algorithmic Oversight: Internal Morality of Medicine and Meaningful Human Control in AI-Assisted Care.Healthcare (Basel, Switzerland) · 2026Article
- Attitudes Towards the Use of Artificial Intelligence in Healthcare: A Conjoint Analysis Survey in Singapore.Asian bioethics review · 2026Article
- The Application of artificial intelligence in periprosthetic joint infection.Journal of advanced research · 2026Review
- Large Language Models in Surgery: Promise, Pitfalls, and Practical Use.Journal of abdominal wall surgery : JAWS · 2026Review
- Article
- The application and challenges of ChatGPT in laboratory medicine.Advances in laboratory medicine · 2025Review
- A quantitative study of pathologists' perceptions towards artificial intelligence-assisted diagnostic system.PLOS digital health · 2025Article
- Improving AI-Based Clinical Decision Support Systems and Their Integration Into Care From the Perspective of Experts: Interview Study Among Different Stakeholders.JMIR medical informatics · 2025Article
- Article
- Problems and Barriers Related to the Use of AI-Based Clinical Decision Support Systems: Interview Study.Journal of medical Internet research · 2025Article
- Physicians' attitudes and acceptance towards artificial intelligence in medical care: a qualitative study in Germany.Frontiers in digital health · 2025Article
- Perceptions and attitudes toward artificial intelligence among frontline physicians and physicians' assistants in Kansas: a cross-sectional survey.JAMIA open · 2024Article
- Analysis of public perceptions on the use of artificial intelligence in genomic medicine.Human genomics · 2024Article
- Laboratory Preparation for Digital Medicine in Healthcare 4.0: An Investigation Into the Awareness and Applications of Big Data and Artificial Intelligence.Annals of laboratory medicine · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
The growing use of artificial intelligence (AI) in health care has raised questions about who should be held liable for medical errors that result from care delivered jointly by physicians and algorithms. In this survey study comparing views of physicians and the U.S. public, we find that the public is significantly more likely to believe that physicians should be held responsible when an error occurs during care delivered with medical AI, though the majority of both physicians and the public hold this view (66.0% vs 57.3%; P = .020). Physicians are more likely than the public to believe that vendors (43.8% vs 32.9%; P = .004) and healthcare organizations should be liable for AI-related medical errors (29.2% vs 22.6%; P = .05). Views of medical liability did not differ by clinical specialty. Among the general public, younger people are more likely to hold nearly all parties liable.
Indexed as
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.