Artificial General Intelligence in health professions education: are we really prepared?

Authors

DOI:

https://doi.org/10.29105/innoacad.v1i3.46

Keywords:

generative artificial intelligence, Prevention, health

Abstract

The review of the article Preparing for Artificial General Intelligence (AGI) in Health Professions Education analyzes the potential impact of Artificial General Intelligence (AGI) on health sciences education. The authors explore how the emergence of AGI in 2022 caught educational institutions by surprise and argue that the same could happen with AGI if adequate preparation measures are not taken. Key characteristics of AGI are described, such as multimodality, adaptability, and autonomy, and the review examines how these will revolutionize teaching through personalized electronic tutors, adaptive curricula, and the automation of administrative tasks. The possibility of enhancing personalized learning and redefining the role of the teacher is highlighted, with educators shifting from being knowledge transmitters to facilitators of critical thinking and decision-making. The arrival of AGI demands strategic planning from institutions, fostering its ethical and effective integration to improve the training of health professionals.

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Author Biography

Manuel Millán Hernández, Universidad Nacional Autónoma de México

Doctorante en Educación. Doctorante en Alta Dirección de Establecimientos de Salud. Maestro en Gestión Directiva en Salud. Médico Especialista en Medicina Familiar. Médico Cirujano.

References

Masters, K., Herrmann-Werner, A., Festl-Wietek, T., & Taylor, D. (2024). Preparing for Artificial General Intelligence (AGI) in Health Professions Education: AMEE Guide No. 172. Medical Teacher, 46(10), 1258–1271. https://doi.org/10.1080/0142159X.2024.2387802 DOI: https://doi.org/10.1080/0142159X.2024.2387802

Published

2025-09-30

How to Cite

Millán Hernández, M. (2025). Artificial General Intelligence in health professions education: are we really prepared?. INNOVACADEMIA, 1(3), 68–70. https://doi.org/10.29105/innoacad.v1i3.46