Medical Education and Informatics Department, College of Medicine and Health Sciences, Sultan Qaboos University, Muscat, Sultanate of Oman.
Tübingen Institute for Medical Education, University of Tübingen, Tübingen, Germany.
Med Teach. 2024 Oct;46(10):1258-1271. doi: 10.1080/0142159X.2024.2387802. Epub 2024 Aug 8.
Generative Artificial Intelligence (GenAI) caught Health Professions Education (HPE) institutions off-guard, and they are currently adjusting to a changed educational environment. On the horizon, however, is Artificial Intelligence (AGI) which promises to be an even greater leap and challenge. This Guide begins by explaining the context and nature of AGI, including its characteristics of multi-modality, generality, adaptability, autonomy, and learning ability. It then explores the implications of AGI on students (including personalised learning and electronic tutors) and HPE institutions, and considers some of the context provided by AGI in healthcare. It then raises the problems to address, including the impact on employment, social risks, student adaptability, costs, quality, and others. After considering a possible timeline, the Guide then ends by indicating some first steps that HPE institutions and educators can take to prepare for AGI.
生成式人工智能（GenAI）让医学专业学术文献教育（HPE）机构猝不及防，他们目前正在适应一个已经改变的教育环境。然而，即将到来的是人工智能（AGI），它有望带来更大的飞跃和挑战。本指南首先解释了 AGI 的背景和性质，包括其多模态、通用性、适应性、自主性和学习能力等特点。然后，它探讨了 AGI 对学生（包括个性化学习和电子导师）和 HPE 机构的影响，并考虑了 AGI 在医疗保健领域提供的一些背景。接着提出了需要解决的问题，包括对就业的影响、社会风险、学生适应性、成本、质量等。在考虑了可能的时间表之后，指南最后指出了 HPE 机构和教育者可以采取的一些初步步骤，为 AGI 做好准备。
