用大型语言模型撰写个人陈述和推信的伦理
Logan Hostetter1, Diana Kelm1, Darlene Nelson1
1Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, Minnesota.
ATS scholar
|January 17, 2025
概括
人工智能 (AI) 在研究生医学教育应用中的使用正在增加. 需要指导,以确保道德使用和保持应用程序的完整性,解决诸如抄袭和AI检测等问题.
科学领域:
- 医学教育 医学教育
- 人工智能的人工智能
- 学术诚信 学术诚信
背景情况:
- 大型语言模型 (LLM) 越来越多地用于内容生成.
- 它们在学术和专业写作中的应用是有争议的,现有出版商的指导.
- 对于在研究生医学教育 (GME) 应用中使用人工智能,没有具体的指导方针.
研究的目的:
- 审查在GME应用程序内容生成中对AI的看法.
- 探索人工智能对整体应用审查的影响.
- 为应对伦理挑战,并为在GME应用中使用AI提出建议.
主要方法:
- 在学术写作中对人工智能的当前文学和专家观点的审查.
- 对道德考虑的分析,包括抄袭和AI检测.
- 为GME项目和申请人制定建议.
主要成果:
- 人们对AI在应用中的使用的看法各不相同.
- 人工智能集成给整体审查带来了挑战,并引发了 plagia 的担忧.
- 人工智能文本分类器正在开发中,但并非万无一失.
结论:
- 对于在GME应用中使用人工智能的明确指导是非常必要的.
- 建议侧重于维护申请流程的完整性.
- 积极的措施是必要的,以导航在医学教育中人工智能的不断发展的景观.
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