Table 3.

The curricular concepts and topics of relevance to family physicians.

Main curricular topic		Subtopics
Overview of AIa and data science in family medicine
	Providing an overview of AI definitions and concepts including machine learning as well as topics related to data science (eg, mathematics and statistics) and clinical epidemiology for family medicine.	Review of AI (definitions and concepts) as it relates to family medicine Introduction to AI and fundamentals of data science in family medicine Strength and limitations of AI-based tools
Ethics, legal, and social considerations
	Understanding the ethical, legal, and social concerns of AI as it impacts family medicine clinical practice.	Ethics, patient rights, data security, and confidentiality Liabilities and regulatory and policy considerations Equity, diversity, and inclusion of AI
Application of AI in family medicine
	Understanding how to choose and engage with AI-based tools in clinical settings and workflows with the ability to understand, interpret, and apply results of AI systems in clinical practice.	Clinical practice management and operation Preventative care and risk profiling (eg, mental health and chronic disease) Patient self-management Physician decision support Physician wellness and resilience Social determinants of health
Appraisal of family medicine AI-based tools
	Assessing and reviewing AI-based tools to ensure safe and effective integration and use in clinical practice.	Identification of potential AI adverse effects and potential solutions Quality improvement

^aAI: artificial intelligence.