双边算法:快速审查,探索在公共卫生中可靠和负责任地使用生成人工智能
Melissa MacKay1, Anjali Kukan1, Jennifer E McWhirter1
1Department of Population Medicine, University of Guelph, Guelph, Ontario, Canada.
Digital health
|November 24, 2025
概括
生成型人工智能 (genAI) 提供公共卫生效益,但需要道德准则. 负责任的genAI实施需要针对公平,隐私和信任的政策,以实现有效的公共卫生功能.
科学领域:
- 公共卫生 公共卫生
- 人工智能的人工智能
- 医疗信息学 医疗信息学
背景情况:
- 生成型人工智能 (genAI) 提供了增强公共卫生功能 (如通信,监视和应急准备) 的机会.
- 潜在的好处包括定制消息,打击错误信息和数据驱动的决策.
- 然而,genAI集成引发了关于公平,隐私和信任的重大担忧.
研究的目的:
- 探索在公共卫生中对基因AI的可靠和负责任使用的指导原则.
- 确定那些为公共卫生中 genAI 采用政策制定提供信息的主题.
主要方法:
- 采用了快速审查方法.
- 自2014年以来出版的同行评审和灰色文献被系统地搜索和主题分析.
主要成果:
- 十篇文章符合纳入标准,产生了十个主题,用于公共卫生中负责任的genAI使用.
- 关键原则包括人为监督,透明度,公平,问责和文化相关的沟通.
- 基因AI可以支持健康行为改变和沟通,但必须减轻算法偏见和虚假信息放大等风险.
结论:
- 组织政策必须整合道德考虑,并解决监管差距,以减轻genAI风险.
- 劳动力培训,跨学科合作和政策制定对于负责任的genAI实施至关重要.
- 本次审查为公共卫生组织提供了基础,以制定以人为中心,以道德为基础的政策,以促进基因AI的采用和使用.
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