هوش مصنوعی در آموزش علوم پزشکی: تقابل اقتدار علمی و شکاف نسلی

Research Center for Social Determinant of Health, Medical Education development center, Jahrom University of Medical Sciences, Jahrom,Iran
Advances in artificial intelligence have sparked paradigm shifts in medical education, presenting both transformative opportunities and complex challenges. AI-driven tools—such as adaptive learning systems, sophisticated clinical simulators, and advanced data analytics—hold immense potential to enhance educational quality by improving diagnostic precision, minimizing medical errors, and fostering equity in learning. Despite these benefits, integrating AI into medical curricula comes with significant hurdles, including digital disparities, ethical concerns surrounding data privacy, growing reliance on technology, and evolving faculty roles.
A key challenge lies in redefining traditional academic authority, transitioning instructors from mere knowledge providers to facilitators of dynamic learning experiences. Additionally, the generational divide in digital adoption between educators and students complicates the effective implementation of AI-driven methodologies. To bridge these gaps, it is crucial to establish faculty development initiatives, implement ethics-based regulatory frameworks, and promote blended learning models.
The future of medical education hinges on achieving a balanced integration of human expertise and digital innovation. Strengthening data literacy and nurturing critical thinking skills will be essential alongside technological advancements. Success in this transition demands interdisciplinary collaboration and a reevaluation of conventional educational structures. This study explores AI’s role in the classroom and its long-term impact on medical education, analyzing key challenges—including shifts in academic authority and the generational digital divide—to provide insights for educators and policymakers navigating this evolving landscape.