评估ChatGPT对疫苗相关问题的回应:问题框架对内容和质量的影响
Yoshiki Kusama1,2, Satoshi Kutsuna1,2
1Department of Infectious Diseases, University of Osaka Hospital, Osaka, Japan.
Translational pediatrics
|December 10, 2025
概括
聊天GPT提供一致的日本回应疫苗问题,无论框架. 然而,专家们指出了潜在的偏见和误导性信息,强调了人工智能产生的健康内容需要人类监督的必要性.
科学领域:
- 医疗保健中的人工智能
- 公共卫生传播 公共卫生传播
- 医疗信息的准确性 医疗信息的准确性
背景情况:
- 疫苗犹是一个重要的公共卫生问题,由不信任和错误信息驱动.
- 像ChatGPT这样的生成人工智能工具越来越多地被用作信息来源,尤其是年轻人群.
- 确保医疗准确的人工智能生成的内容至关重要,特别是对于疫苗等敏感话题.
研究的目的:
- 为了评估ChatGPT对日语中提出的疫苗相关问题的答案的质量.
- 具体来评估,当问题是批判性而不是支持性的时,ChatGPT的答案是否有所不同.
- 识别人工智能生成的疫苗信息中的潜在偏见或不准确性.
主要方法:
- 一项针对日本儿科传染病专家的匿名调查.
- 为ChatGPT-4o生成20个支持性和关键性疫苗问题对.
- 专家使用五分利克特级别 (清晰度,适当性,模糊性,长度) 评估ChatGPT的日语回复.
- 对自由文本评论进行定性分析,以确定具体问题.
主要成果:
- 支持性和关键性疫苗问题答案之间的清晰度,适当性,模糊性或长度没有显著差异.
- 专家们发现了反复出现的担忧,包括对COVID-19疫苗的偏见 (38条评论),解释不足 (19条评论),以及可能误导性的措辞 (9条评论).
- 偏见的具体例子包括过度强调COVID-19和对疫苗不良事件的有问题的描述.
结论:
- 聊天GPT在保持响应质量方面表现出了弹性,无论日本语中的问题框架如何.
- 尽管评级相似,但专家审查显示了AI产生的疫苗内容中的专题偏见和潜在的误导性信息.
- 持续的人类监督,日本语言输出的完善和算法调整是必要的,以减轻偏差并确保准确性.
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