AI THREATENS TO PREVENT MEDICAL TRAINEES FROM LEARNING CLINICAL JUDGMENT

The concern extends beyond deskilling—the loss of abilities already acquired. Medical students, residents, and fellows using AI diagnostic and decision-making tools before establishing their own judgment may never develop the foundational skills required to practice medicine safely. Unlike experienced doctors who risk losing previously developed expertise, trainees face a different challenge: building clinical competency depends on deliberate practice, pattern recognition, and learning from cases over time. If AI handles diagnostic reasoning and decision-making early in training, students miss critical developmental stages. The healthcare field increasingly recognizes this gap. Training programs must balance AI integration with preserving hands-on learning and independent problem-solving. Without intervention, new generations of physicians could depend entirely on algorithmic guidance, unable to function when systems fail or when cases fall outside AI training parameters. Experts argue that AI should enhance, not replace, early clinical training.