The Reverse Native-Speaker Problem: Teaching Physiology to a Generation Fluent in Tools We Are Still Learning

Generative artificial intelligence (AI) is reshaping physiology education, but the central challenge is epistemic, not technological. Learners are often more fluent with AI tools than their instructors, yet less fluent in the physiology those tools describe: a pattern this Perspective terms the reverse native-speaker problem. AI-generated explanations of physiological mechanisms are rarely overtly wrong. An interpretive framework proposed by means of this perspective states that explanations that appear plausible step by step may become become inconsistent when organ systems are considered together. It is therefore argued that the educator role is shifting from transmitting information to certifying coherence and proposes a classroom exercise, the error-hunt, for identifying seeded, systems-level inconsistencies in AI-generated explanations.