将生成人工智能集成到医学教育中:课程,政策和治理策略
概括
生成型人工智能 (GAI) 要求医学院将道德和技术培训纳入课程. 教育工作者需要指导,为学生准备未来的GAI在医疗保健领域的转变.
科学领域:
- 医学教育 医学教育
- 人工智能的人工智能
- 医疗保健技术 技术 医疗保健 技术
背景情况:
- 生成型人工智能 (GAI) 为医学教育和医疗保健带来了重大机遇.
- 医疗教育工作者目前缺乏将GAI纳入课程所需的能力和指导.
- 越来越需要在本科医学教育中解决GAI的伦理,技术和教学影响.
研究的目的:
- 突出医学院需要适应GAI范式的必要性.
- 建议实施GAI的政策,治理和课程.
- 定义医疗教育中GAI的基本能力.
主要方法:
- 学术观点和政策和课程发展的建议.
- 强调道德和公平的GAI使用,数据保护和教师/学习者培训.
- 基于现有的AI框架,提出新的GAI能力.
主要成果:
- 医学院必须制定适当使用GAI的政策,保护患者数据.
- 机构GAI治理对于道德和公平的实施至关重要.
- 教师和学生的培训和定义能力对于安全的GAI实验至关重要.
- 课程应侧重于GAI的临床影响.
结论:
- 医学教育必须主动整合GAI,解决其道德和实际挑战.
- 合作和持续的更新对于为学生准备GAI影响的医疗未来至关重要.
- 对学生和教育工作者来说,开发特定的GAI能力是必要的.
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