绘制知识流作为医疗人工智能道德实施指南:一项定性研究
Magali Goirand1, Elizabeth Austin1, Robyn Clay-Williams1
1Australian Institute of Health Innovation, Macquarie University, Sydney, Australia.
PloS one
|November 2, 2023
概括
在医疗人工智能 (AI) 中实施伦理需要一种系统思维方法. 让临床医生和患者等各种利益相关者参与透明对话对于公共卫生中的道德AI应用程序开发至关重要.
科学领域:
- 医疗保健技术 医疗保健技术 医疗保健技术
- 公共卫生信息学 公共卫生信息学
- 生物伦理学生物伦理学
背景情况:
- COVID-19危机加速了人工智能 (AI) 在医疗保健和公共卫生中的应用.
- 人工智能应用的紧急实施不能忽视关键的伦理考虑.
- 将道德纳入医疗人工智能需要全面的系统思维方法.
研究的目的:
- 探索AI应用在公共卫生中的伦理影响.
- 研究一种系统思维方法,用于在医学AI中实施伦理.
- 分析利益相关者参与AI医疗保健工具的开发.
主要方法:
- 采用软系统方法论和批判性系统思维.
- 在咨询讨论中参与临床医生,患者和AI开发人员.
- 在模拟的人工智能医疗应用程序中分析了知识流和伦理界限.
主要成果:
- 利益相关者的参与揭示了与人工智能系统中的数据和知识交换相关的伦理问题.
- 利益相关者参与的过程本身为道德AI实施提供了洞察力.
- 透明,包容和尊重对话对于道德的人工智能发展至关重要.
结论:
- 系统思维方法对于将伦理纳入医疗AI至关重要.
- 与各种利益相关者进行参与的参与确保了伦理方面的考虑.
- 在医疗保健中建立人工智能的伦理界限需要持续,坦诚的对话.
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