学会伪造:ChatGPT为医疗问题提供有限的答案和伪造的参考
Jocelyn Gravel1, Madeleine D'Amours-Gravel2, Esli Osmanlliu3
1Department of Pediatric Emergency Medicine, CHU Sainte-Justine, Université de Montréal, Montréal, Québec, Canada.
聊天GPT为医疗问题提供了低质量的答案和捏造的参考资料. 医学专家发现了事实上的错误和许多欺骗性的引用,敦促在科学手稿中使用人工智能生成的内容时谨慎使用.
科学领域:
- 人工智能在医学中的应用
- 医疗信息学 医疗信息学
- 科学写作 科研写作
背景情况:
- 像ChatGPT这样的大型语言模型越来越多地用于信息检索.
- 人工智能产生的医疗内容的可靠性,特别是参考资料,需要进行彻底的评估.
- 确保准确性对于科学出版物和医学实践至关重要.
研究的目的:
- 评估ChatGPT对医疗问题的响应质量.
- 评估ChatGPT提供的引用的准确性和真实性.
- 确定人工智能生成的内容是否适合用于医学文献.
主要方法:
- 三名研究人员向ChatGPT提出了20个医学问题,要求参考资料.
- 医学专家,来源文章的作者,评级响应质量 (0-100%).
- 评估的参考相关性,注意制造的流行.
主要成果:
- 聊天GPT回复的质量中位数为60%,发现了事实上的错误.
- 大多数 (69%) 的参考文献是伪造的,但看起来是真实的.
- 伪造的引用模仿了真实的引用,使用作者名称和可信的标题.
结论:
- 聊天GPT为科学用途生成质量有限的医疗答案.
- 人工智能经常产生欺骗性的,伪造的引用,看起来可信.
- 用户必须在将其纳入医疗手稿之前,严格核实 ChatGPT 提供的所有参考文献.
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