Implementation of a Novel Case-Based Session for Medical Students Focused on Artificial Intelligence Ethics

Area of Science:

• Medical Education
• Bioethics
• Artificial Intelligence in Healthcare

Background:

• Artificial intelligence (AI) integration in healthcare necessitates physicians understanding its ethical foundations for just patient care.
• Medical professionals require foundational knowledge of AI ethics to effectively utilize AI in clinical settings.

Purpose of the Study:

• To design and evaluate a novel ethics session for preclerkship medical students focused on the ethical principles of AI in medicine.
• To assess students' self-reported understanding of AI ethics concepts post-session.

Main Methods:

• A case-based, small-group ethics session was developed for preclerkship medical students.
• Interdisciplinary bioethics faculty facilitated the session, followed by a retrospective pre-post survey with Likert scale and open-ended questions.

Main Results:

• Out of 170 attendees, 94 students (55% response rate) completed the survey.
• Students reported a significantly stronger understanding of ethical issues surrounding AI in medicine post-session.
• Qualitative analysis revealed students valued peer and facilitator discussions on AI ethics.

Conclusions:

• The case-based session was highly valued by students and recommended for future curricula.
• The session demonstrated a self-reported improvement in understanding core AI ethics concepts.
• This approach effectively integrates key AI ethics domains (bias, privacy, autonomy, harm) into medical education.