生成性AI的双刃剑:超越一个专家或一个欺骗性的"假朋友"?
Franziska C S Altorfer1, Michael J Kelly2, Fedan Avrumova2
1Department of Spine Surgery, Hospital for Special Surgery, New York, NY, USA; Universtity Spine Center Zurich, Balgrist University Hospital, University of Zurich, 8006 Zurich, Switzerland.
概括
生成型人工智能工具提供可接受的医疗答案,但伪造了近25%的参考. 建议在临床使用时谨慎使用,因为科学引用是不真实的.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 科学文献分析 科学文献分析
背景情况:
- 以ChatGPT为例的生成性人工智能 (AI) 越来越多地被用于医学应用.
- 人工智能工具往往缺乏科学依据,可能会产生伪造的引用 (AI幻觉).
研究的目的:
- 通过评估参考真实性和响应可靠性来评估生成性AI的科学基础.
- 将AI反应与基于证据的指导方针进行比较.
主要方法:
- 一项比较研究使用了33个北美脊柱学会 (NASS) 准则问题作为两个AI工具的提示.
- 对答案进行了评分,以与NASS指导方针 (5分级) 保持一致.
- 引用的参考文献被分析为真实性,来源类型,出版年份和包含在指南中.
主要成果:
- 人工智能工具实现了可接受的对齐得分 (3.5±1.1) 与NASS指南.
- 在创建的254个引用中,有24%是伪造的.
- 一个人工智能工具 (克劳德) 引用的同行评审论文和旧参考文献比另一个工具 (双子) 更多.
结论:
- 生成型人工智能响应可接受地与NASS指南保持一致,但很大一部分引用是不真实的.
- 伪造的参考资料的高率阻止了临床实施.
- 在临床环境中使用人工智能生成的内容时需要谨慎.
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