Harnessing Data and Learning Analytics in the Era of AI: Reflections from Medical Education

Artificial intelligence (AI) and learning analytics are transforming medical education by enabling personalized learning, data-informed assessment, and curriculum planning. However, educational use of these tools also carries ethical implications related to privacy, bias, and the epistemic value of data. This commentary proposes that AI and analytics be approached not only as technical solutions but as sociotechnical systems that influence how medical schools conceptualize learning, assessment, and equity. Drawing on recent literature and lived educational experience, we argue for theory-driven, ethically grounded implementations that protect learners, promote transparency, and foster human-centered professional formation.