Effect of Artificial Intelligence-Augmented Human Instruction on Surgical Simulation Performance

At the Neurosurgical Simulation and Artificial Intelligence Learning Centre, we seek to provide surgical trainees with innovative technologies that allow them to improve their surgical technical skills in risk-free environments, potentially improving patient operative outcomes. The Intelligent Continuous Expertise Monitoring System (ICEMS), a deep learning application that assesses and trains neurosurgical technical skill and provides continuous intraoperative feedback, is one such technology that may improve surgical education. In this randomized controlled trial, medical students from four Quebec universities will be blinded and randomized to one of three groups (one control and two experimental). Group 1 (control) will be provided with verbal AI tutor feedback based on the ICEMS error detection. Group 2 will be tutored by a human instructor who will receive ICEMS error data and deliver verbal instruction using the same words as the ICEMS. Group 3 will be tutored by a human instructor who will be provided with ICEMS data and will then deliver personalized feedback. The aim of this study is to determine how the method of delivery of verbal surgical error instruction influences trainee technical skill acquisition and transfer. Evaluating trainee responses to AI instructor verbal feedback as compared to feedback from human instructors will allow for further development, testing, and optimization of the ICEMS and other AI tutoring systems.