Table 2.

Recommended artificial intelligence (AI) ethics teaching content.

MAIN TEACHING RECOMMENDATION	DETAILED AI ETHICS TEACHING CONTENT RECOMMENDATIONS	PUBLICATIONS
Ethical challenges and issuesa	General ethical problems and challenges (not specified) [43,46,48,50] Informed consent, bias, safety, transparency, patient privacy, and allocation [47,49] Quality assurance, trust, patient values, confidentially, justice, human rights, accountability, over-diagnosis and over-treatment, automation bias, skill erosion, explainability, and information overload [49] Incorrect, absent, or abusive use of AI in medicine [49] Patient-physician relationship [22,42,45]	[22,42,43,45,46,47,48,49,50]
Data protectiona	Cyber-security risks [49] Risks for patient data due to the use of AI [22,44,45,47] AI-related data collection, storage, and analysis [51]	[22,44,45,47,49,51]
Liabilitya	Liability in case of mistakes due to programming or construction flaws, lack of proper documentation, and user guidance [49] Ethical implications of liability in the clinical context (not specified) [42,44,45,46]	[22,44,45,46,49]
Ethical values and principlesa	The potential impact of AI on the principles of medical ethics by Beauchamp and Childress (beneficence, justice, autonomy, and non-maleficence) [22,36,42,44,45,49] Fairness, transparency, and responsibility analogous to beneficence, justice, autonomy, and non-maleficence [22] Empathy as the cornerstone of teaching AI ethics [23]	[22,23,42,44,45,47,49]

^aassociated with the use of AI in medicine.