New Global CARE-AI Framework Sets Standard for Responsible AI in Health Education and Care
The framework includes 10 principles and a toolkit to help medical schools, residency programs, and health systems govern AI use.
5 Articles
5 Articles
When physicians and AI work together, who is accountable? How to lay out medical liability
Nature, Published online: 28 July 2026; doi:10.1038/d41586-026-02315-9A staging system based on how big a role AI has in patient care can help to identify who is responsible in cases in which care fails.
New global CARE-AI framework sets standard for responsible AI in health education and care
An international team of researchers, clinicians, educators, ethicists and patient partners has developed and validated the Health CARE-AI (Contextual, Accountable, Responsible, and Equitable Artificial Intelligence) Framework. Published in JMIR Medical Education, the study provides a consensus-backed roadmap for the responsible integration of AI across the health care learning and practice continuum.
Hyperpersonalization, driven by artificial intelligence (AI), has altered the way companies relate to customers in electronic commerce, including in the medical product segment. Unlike traditional customization, based on static data such as name and location, the dynamic model uses behavior and context information to anticipate demands and guide recommendations. The expectation for this type of treatment already predominates among consumers: a M…
Key Takeaways on AI Healthcare Risk Responsibility
Table of ContentsHow This Technology Is Impacting Patients and CliniciansWhy Clinicians Must Still “Know Their Patients”A Targeted Approach to Implementation Within AI Healthcare Risk ResponsibilityPreserving Learning Opportunities Amid AutomationAI Scribes and Consent Considerations Within This FrameworkThe Role of the National Commission Into AI RegulationMedical Device Compliance and AI Healthcare Risk Responsibility for ProvidersWhy Risk Map…
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