Generative artificial intelligence and the epistemology of medical learning: from cognitive augmentation to epistemic dependency
TL;DR
It is proposed that the relationship between GAI and medical learning is best understood as a continuum that extends from cognitive augmentation to epistemic dependency, and algorithmic systems may expand opportunities for learning and reasoning while simultaneously altering the intellectual dispositions through which critical evaluation, uncertainty management, and independent judgment are cultivated.
Abstract
Generative artificial intelligence (GAI) is rapidly transforming medical education by expanding access to information, enabling personalized learning, and improving measurable educational outcomes. Systematic reviews, meta-analyses, and experimental studies consistently report gains in learner satisfaction, communication abilities, practical skills, and short-term academic performance following GAI-assisted educational interventions. Yet these benefits have largely been evaluated through performance-centered metrics, while the cognitive and epistemological implications of algorithmically mediated learning remain insufficiently examined. This Perspective explores how GAI may be reconfiguring the conditions under which medical knowledge is acquired, interpreted, and integrated. Drawing on medical epistemology, philosophy of science, educational theory, and evidence-based medicine, we argue that the educational significance of GAI extends beyond efficiency and information accessibility. By increasingly participating in explanatory, interpretive, and inferential activities, generative systems are redistributing forms of cognitive work that have traditionally contributed to the development of autonomous clinical judgment. We propose that the relationship between GAI and medical learning is best understood as a continuum that extends from cognitive augmentation to epistemic dependency. Along this continuum, algorithmic systems may expand opportunities for learning and reasoning while simultaneously altering the intellectual dispositions through which critical evaluation, uncertainty management, and independent judgment are cultivated. The principal challenge for contemporary medical education is therefore not whether future physicians will learn alongside intelligent systems, but how educational environments can harness the benefits of AI-mediated learning while sustaining the cognitive capacities that underpin responsible clinical reasoning. Cultivating epistemological resilience may become a central objective of medical education in the age of GAI.