生成型人工智能和非药物偏见:对癌症患者性健康传播的实验研究
Akiko Hanai1,2, Tetsuo Ishikawa3,2,4,5, Shoichiro Kawauchi3
1Medical Data Mathematical Reasoning Team, Advanced Data Science Project, RIKEN Information R&D and Strategy Headquarters, RIKEN, Yokohama, Japan hanaaki0803@gmail.com.
BMJ health & care informatics
|April 4, 2024
概括
生成型人工智能 (AI) 可以帮助癌症幸存者讨论性健康问题. 人工智能反应更倾向于非药物干预,强调需要管理患者对治疗选择的期望.
科学领域:
- 在瘤学瘤学.
- 人工智能的人工智能
- 性健康 性的健康
背景情况:
- 癌症幸存者经常面临讨论性健康问题的挑战.
- 生成型人工智能为解决敏感健康话题提供了一个新的工具.
研究的目的:
- 探索生成性人工智能 (AI) 在为癌症幸存者产生有关性健康问题的能力.
- 分析有关性健康干预的AI产生的反应的性质.
主要方法:
- 使用生成式预训练过的变压器-3.5 (GPT) 和DocsBot来生成问题和检索引文.
- 开发了一个基于流行病学数据的结构化提示,以生成100个问题.
- 从标准GPT模型 (Bot1) 和从临床指南 (Bot2) 中获取的模型中比较反应.
主要成果:
- 生成型人工智能没有对性表达或医学术语进行审查.
- 人工智能反应显著偏好"咨询"而不是药理干预 (ORs 47.3和97.2,p<0.001).
- 响应显示了对非药物干预的偏见,可能是由于人工智能模式政策.
结论:
- 生成性AI可以提供关于性健康等敏感话题的健康信息.
- 人工智能反应中对非药物干预的偏见需要注意与患者的期望保持一致.
- 需要进一步的研究来完善人工智能,以便为癌症幸存者提供平衡的性健康信息.
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