Understanding AI adoption in medical education: Insights from students and faculty members in Indonesian medical schools

Background: Artificial Intelligence (AI) implementation in medical education has changed the learning process, with new forms of diagnosis, treatment planning, and patient care. Biases in AI adoption among Indonesian medical schools’ students and teachers, however, are still to be explained. This article seeks to determine the level of knowledge, attitude, and behavior of the medical students and faculty members towards the adoption of AI in medical education. Materials and Methods: Analytical observational design with a cross-sectional design is utilized in this study. Questionnaires were used to collect data from medical students and medical lecturers of several Indonesian medical schools. Consecutive and purposive sampling methods were used to determine the sample. Statistical analysis involved using the Spearman correlation test to examine the correlation between AI adoption, knowledge, attitudes, and behavior. Results: Among the students, 62.3% had good knowledge about AI, while 52.6% fell in the neutral attitude range and 64% of them showed a moderate behavior in implementing AI. The faculty members, however, were found to be divided in terms of their extent of knowledge, among which 34.7% fell into the good knowledge range, 71.4% showed a positive attitude, and 46.9% illustrated low interaction in implementing AI. The correlation test did not show any meaningful relationship between behavior and knowledge in either group (students: P =0.582; staff: P =0.593). There was, however, a weak but significant relationship between attitude and behavior in the staff ( P = 0.018; r = 0.239). Conclusion: Though both students and teachers have an idea about the possibilities of AI in medical education, they are still far from adopting AI-based tools at their behavioral level.