Transformative Landscape of Anesthesia Education: Simulation, AI Integration, and Learner-Centric Reforms: A Narrative Review

Abstract

This article examines the intersection of simulation-based education and the AI revolution in anesthesia medicine. With AI technologies reshaping perioperative management, simulation education faces both challenges and opportunities. The integration of AI into anesthesia practice offers personalized management possibilities, particularly in preoperative assessment and monitoring. However, the ethical, legal, and social implications necessitate careful navigation, emphasizing patient data privacy and accountability. Anesthesiologists must develop non-technical skills, including ethical decision-making and effective AI management, to adapt to the AI era. The experience-based medical education (EXPBME) framework underscores reflective learning and AI literacy acquisition, fostering lifelong learning and adaptation. Learner-centered approaches are pivotal in anesthesia education, promoting active engagement and self-regulated learning. Simulation-based learning, augmented by AI technologies, provides a dynamic platform for technical and non-technical skills development. Ultimately, by prioritizing non-technical skills, embracing learner-centered education, and responsibly leveraging AI technologies, anesthesiologists can contribute to enhanced patient care and safety in the evolving perioperative landscape.