ArticleThe Milbank quarterly2021
Artificial Intelligence and Liability in Medicine: Balancing Safety and Innovation.
Article in The Milbank quarterly, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
63 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Patient Concerns Regarding Artificial Intelligence Applications in Health Care: Systematic Review and Meta-Synthesis Based on Social Ecological Theory.Journal of medical Internet research · 2026Pooled it
- AI Trustworthiness in the Perioperative Period for Patients with Serious Illness: Scoping Narrative Review.JMIR perioperative medicine · 2026Article
- Clinicians' Attitudes and Perceptions on the Adoption of AI in Mental Health Care: Scoping Review.Journal of medical Internet research · 2026Article
- Generative artificial intelligence in forensic medicine: a pilot study on AI-simulated medico-legal reports in healthcare liability cases.International journal of legal medicine · 2026Article
- Agentic Loafing: An AI Decision Delegation Risk.Risk analysis : an official publication of the Society for Risk Analysis · 2026Article
- Risk and liability in the deployment of AI systems for surgery: a SAGES white paper.Surgical endoscopy · 2026Review
- Defining the artificial intelligence knowledge gap in surgery: experience and perspectives from surgical resident and postgraduate.Updates in surgery · 2026Article
- Article
- Clinician in the loop: a flawed solution for AI oversight.BMJ (Clinical research ed.) · 2026Article
- Integrating Generative AI Into Patient-Centered Clinical Decision Support: Viewpoint on Research and Practice Considerations.Journal of medical Internet research · 2026Article
- Advanced immunotherapy across diseases and the role of artificial intelligence: A review.Biomolecules & biomedicine · 2026Review
- Artificial intelligence in dementia care: challenges, controversies, and policy implications.Frontiers in dementia · 2026Article
- Navigating ethical, regulatory, and implementation barriers to AI in healthcare: pathways toward inclusive digital health in low-resource settings-a scoping review.Frontiers in digital health · 2026Review
- Legal and ethical reflections on the use of artificial intelligence in the diagnosis and treatment of cancer: who assumes responsibility?Frontiers in artificial intelligence · 2026Article
- The unintended negative consequences of artificial intelligence use for psychologists.Frontiers in psychology · 2026Article
- Toward a National Health Digital and Data Architecture: Laying the Foundation for Digital Transformation: Commission on Investment Imperatives for a Healthy Nation.NAM perspectives · 2026Review
- The Evolving Role of AI in Simulation-Based Medical Education: A Narrative Review.Advances in medical education and practice · 2026Review
- FromFrontiers in digital health · 2026Article
- Empowering photodynamic therapy with artificial intelligence: current trends and future directions.Frontiers in oncology · 2026Review
- Using generative artificial intelligence in clinical practice: a narrative review and proposed agenda for implementation.The Medical journal of Australia · 2025Review
3 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Policy Points With increasing integration of artificial intelligence and machine learning in medicine, there are concerns that algorithm inaccuracy could lead to patient injury and medical liability. While prior work has focused on medical malpractice, the artificial intelligence ecosystem consists of multiple stakeholders beyond clinicians. Current liability frameworks are inadequate to encourage both safe clinical implementation and disruptive innovation of artificial intelligence. Several policy options could ensure a more balanced liability system, including altering the standard of care, insurance, indemnification, special/no-fault adjudication systems, and regulation. Such liability frameworks could facilitate safe and expedient implementation of artificial intelligence and machine learning in clinical care.
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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.