人工智能修订内容在药房住院意向书中的可感知性
Nariman Piri1, Chase De Guio2, Clifford Qualls3
1Pharmacy Service, New Mexico Veterans Affairs Health Care System, United States Department of Veterans Affairs, Albuquerque, NM, USA.
概括
药房住院意向书的生成AI修订很难检测和提高得分,特别是多次修订. 需要对人工智能的进一步研究.
科学领域:
- 药房教育 在药房教育.
- 在学术界的人工智能.
- 住院计划的应用程序.
背景情况:
- 生成型人工智能 (AI) 可能会影响药房住院应用.
- 人工智能对意向书 (LOI) 的可检测性和影响尚未得到充分研究.
研究的目的:
- 评估AI修订在药房住院LOI中的可感知性.
- 评估AI修订对药房住院LOI质量的影响.
主要方法:
- 使用ChatGPT修改了六个基线LOI (2,4,6次修订).
- 十二名药剂师使用标题评估了24个独特的LOI,用于AI检测和质量.
- 主要结果:AI的可检测性;次要结果:对质量评分的影响.
主要成果:
- 审查人员只在35%的时间内正确识别了AI修订.
- 人工智能修订使得字母难以检测,随着修订的增加,检测能力下降.
- 有6个AI修订的信件得分明显高 (15.9/20) 比原始信件 (10.0/20).
结论:
- 对药房住院LOI的生成AI修订并不容易被检测出来.
- 多次AI修改赋予了显著的得分优势.
- 需要进一步研究AI在研究生培训应用中的作用.
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