How AI is changing the training of doctors

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Artificial Intelligence (AI) is rapidly transforming medicine, creating new possibilities in diagnosis, therapeutic decision-making, and patient care. However, it also raises a fundamental question: how should doctors be trained when more and more cognitive functions can be supported by intelligent computing systems?

In an article published on October 14, 2026, in the scientific journal JAMA, Jesse Burk-Rafel and Robert Wachter argue that the integration of AI into clinical practice necessitates a substantial revision of the traditional model of medical education.

For over a century, the education of doctors has relied on the acquisition of extensive scientific knowledge and the development of clinical experience. However, the ability of AI to analyze information and suggest diagnostic or therapeutic approaches creates the risk that young doctors may bypass the reasoning process through which independent clinical assessment develops.

The risk of dependence on AI and the importance of clinical assessment

This phenomenon is described as “never-skilling”, meaning the inability to develop essential skills due to reliance on technology. The authors propose a new educational strategy based on three axes: enhancing skills that become more important in the age of AI, cultivating new capabilities and carefully limiting educational requirements that become less necessary. Direct clinical examination continues to hold a central position. Physical examination, observation, and communication with the patient provide information that may be missing from the electronic medical record or may not be recognized by an algorithm. Equally important is therapeutic reasoning, that is, the ability to transform a diagnosis into a personalized treatment plan, taking into account the severity of the disease, the patient’s specific needs and preferences.

The development of the ability for critical oversight of AI reasoning gains particular importance. This refers to the doctor’s ability to independently evaluate the diagnostic and therapeutic recommendations produced by AI systems, to identify possible inaccuracies, and to decide when to accept them, modify them, or seek additional clinical data. The doctor of the future must not only know how to use AI. They must possess the scientific knowledge and independent clinical judgment required to recognize its limitations and potential errors and to intervene when necessary.

How should doctors be educated in the age of AI

This process requires two essential skills: calibrated trust, that is, the doctor’s ability to adjust their degree of trust in Artificial Intelligence based on the tool, the clinical application, and the seriousness of the possible consequences, and metacognition, that is, the ability to recognize, evaluate, and readjust their own thinking and decision-making processes. In this way, the aim is to limit both the uncritical acceptance of algorithmic suggestions and the unjustified rejection of the possibilities offered by technology. At the same time, it is proposed to target the reduction of encyclopedic memorization, without undermining the fundamental knowledge of physiology, pathophysiology, and pharmacology. The knowledge required for emergency clinical decisions must remain immediately available, while other information can be sought with the help of technology.

The reform of medical education requires continuous practice both with and without AI, case simulations with embedded errors, and new assessment methods that will distinguish the personal contribution of the trainee from that of the algorithm. The central message of the publication is that AI does not replace medical judgment, but makes its cultivation even more important. The challenge is not merely to train doctors who effectively use technology but to cultivate scientists who maintain autonomy, critical thinking, and the ability to make responsible, personalized decisions, always focusing on the human aspect.

An article written by ERTNews, initially published on 23 October 2026, 13:20 (CEST)