CARE-AI Framework guides responsible health AI
10/20/2026
Artificial intelligence is rapidly becoming part of everyday life, including the way health professionals learn, conduct research, and deliver care. From helping analyze medical information to supporting clinical decision-making, AI offers exciting possibilities. But as these tools become more common, an important question remains: how can we ensure AI is used in ways that are ethical, trustworthy, and fair?
A team of researchers and health professionals has developed a practical answer through the CARE-AI Framework (Contextual, Accountable, Responsible, and Equitable Artificial Intelligence). Created to help guide the responsible use of AI across health professions, education, research, and clinical care, the framework goes beyond broad ethical values and provides actionable principles that support professional accountability and equity in real-world settings.
“The CARE-AI Framework isn’t so much about AI as it is about people,” said Dr. Lyn Sonnenberg, Investigator with Bruyère Health Research Institute and Director of Strategy and Innovation at the Equity in Health Systems Lab. “Use of AI is shaped by the interconnected actions of patients, care partners, clinicians, educators, and more. That’s why patient partners were included from the onset, to ensure those we care for are centred at all stages of the framework.”
The framework is organized into four domains: values, competence, accountability, and structural equity. Together, they balance a shared responsibility by individuals and institutions to contribute to the safe and equitable use of AI.
CARE-AI is complemented by an implementation guide that offers context specific guidance across education, research, clinical, and administrative environments.
How can clinical environments leverage efficiency and accuracy, while countering risks such as biased outputs, opaque decision pathways, and privacy breaches? How can researchers leverage large-scale data sets and enhance analysis, while preventing biased data and protecting how health information is collected, stored, and processed?
“AI is no longer an emerging tool in health care, it’s already being used in clinical decisions, research, and education,” said Dr. Jerry Maniate, Investigator at Bruyère Health Research Institute and Founder of the Equity in Health System Lab. “Our implementation guide is focused on very clear, tangible examples that people can apply directly to their work at different stages of AI adoption.”
CARE-AI is unique because of its emphasis on people. The framework is grounded in the belief that technology should enhance human expertise, not replace it, and encourages ongoing AI literacy so that health professionals understand both the opportunities and limitations of these technologies.
As AI continues to reshape health care, frameworks like CARE-AI are a reminder that responsible innovation is not only about what technology can do, but how people choose to use it. By centring accountability, critical thinking, transparency, and equity, CARE-AI offers a roadmap for ensuring that AI strengthens health care while keeping patients, learners, and communities at the heart of every decision.
This research was funded in part by the Government of Canada under the Future Skills Centre program for the project named Fostering Equity and Inclusion in Healthcare by Accelerating Responsible Use of Artificial Intelligence.