Sociedad Española de Educación Médica

This is so true! #MedEd does not give enough value to the work of educators because there is no clear system to measure this work economically. In laboratory studies, almost everything has a cost, but in medical education, teaching, curriculum preparation, assessment and similar works are usually not calculated. Because of this, the time and effort of clinician-educators become invisible, and many educators continue these works in their personal time. The authors says institutions should create a system to measure and recognize educational work, and this work should also be connected with compensation and promotion.

State of clinical AI in 2026 has been published: AI is getting better at medicine faster than medicine is getting ready for AI. AI in healthcare improved a lot, but good benchmark results do not mean it is ready for real clinical use. Some models can match or even outperform doctors in certain diagnostic tasks. But they still have problems with uncertainty, unusual cases and understanding when they are wrong. Also, real-world evidence is still limited compared to how fast these tools are being adopted. Another important point is human-AI collaboration. Doctors can perform better with AI support, but doctor + AI is not always better than AI alone. So for now, AI looks most useful in specific, well-defined tasks. Full clinical autonomy is still too early.