Evaluation of a Problem-Based Learning Program's Effect on Artificial Intelligence Ethics Among Japanese Medical...

Area of Science:

• Medical Education
• Artificial Intelligence Ethics
• Health Informatics

Background:

• Medical school curricula lag in integrating artificial intelligence (AI) education.
• Medical students show a gap between positive AI perceptions and actual competencies, particularly in legal and ethical understanding.
• Existing AI education challenges include addressing regulatory and ethical complexities in clinical practice.

Purpose of the Study:

• To evaluate an educational program's effectiveness in enhancing medical students' understanding of legal and ethical AI issues.
• To assess the program's impact on knowledge acquisition and the qualitative shift in students' ethical reasoning.
• To determine the contribution of lecture and problem-based learning (PBL) components.

Main Methods:

• A mixed-methods, single-group pretest-posttest design with 118 fourth-year medical students.
• A 1-day intervention including a lecture and PBL session on a clinical AI case.
• Quantitative analysis via MCQ and qualitative analysis using descriptive essays and text mining.

Main Results:

• Significant improvement in objective knowledge scores post-intervention (P<.001).
• Qualitative analysis revealed a transformation from fragmented to integrated thinking networks regarding AI ethics.
• Students increased their use of professional and ethical terminology, such as 'bias' and 'personal information.'

Conclusions:

• PBL-based education effectively improved medical students' AI ethics knowledge and reasoning.
• The program fostered a shift from abstract to concrete, clinically relevant ethical thinking.
• PBL demonstrates potential as a key pedagogical method for AI ethics in medical education.