Principles for Responsible AI in Health Professions Education, Research, and Care: Health CARE-AI (Contextual, Accountable, Responsible, and Equitable Artificial Intelligence) Framework Delphi Consensus Study

Lyn K Sonnenberg   ^{1, 2 *} , BSc, MSc, MEd, EMBA, MD ;   David Wiljer   ^{1, 3, 4 *} , BA, MA, PhD ;   Muhammad Mamdani   ^{5, 6} , MA, MPH, PhD ;   Victor Do   ^{1, 2} , MSc, MD ;   Brandon Tang   ^{1, 7} , MD ;   Babar Haroon   ⁸ , MEd, MD ;   Bizav Jaffer   ^{1, 9} , BSc ;   Jerry Maniate   ^{1, 9 *} , MEd, EMBA, MD

¹ Equity in Health Systems (EqHS) Lab, Bruyère Health Research Institute, Ottawa, ON, Canada

² Department of Pediatrics, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB, Canada

³ Education Technology Innovation, Digital, University Health Network, Toronto, ON, Canada

⁴ Department of Psychiatry, University of Toronto, Toronto, ON, Canada

⁵ Department of Laboratory Medicine and Pathology, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada

⁶ Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada

⁷ Department of Medicine, University of Toronto, Toronto, ON, Canada

⁸ Department of Critical Care, Faculty of Medicine, Dalhousie University, Halifax, NS, Canada

⁹ Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada

*these authors contributed equally