使用人类因素方法来减轻基于人工智能的临床决策支持方面的偏见
Laura G Militello1, Julie Diiulio1, Debbie L Wilson2
1Applied Decision Science, LLC, Dayton, OH 45429, United States.
Journal of the American Medical Informatics Association : JAMIA
|November 21, 2024
概括
用户界面设计在临床决策支持 (CDS) 中显著影响人工智能 (AI) 偏见. 优化UI设计对于减轻AI偏见和提高CDS安全性和有效性至关重要.
科学领域:
- 医疗信息学 医疗信息学
- 人与计算机的交互
- 人工智能的人工智能
背景情况:
- 人工智能 (AI) 算法中的偏差是临床决策支持 (CDS) 中的一个重大问题.
- 目前关于AI偏见的讨论主要集中在数据质量和算法设计上.
- 用户界面 (UI) 设计对用户行为和AI应用结果的影响往往被低估.
研究的目的:
- 强调UI设计在缓解基于AI的CDS中的偏见方面的关键,但经常被忽视的角色.
- 探索AI算法开发和UI设计之间的相互依赖关系.
- 通过改进UI设计,提出提高CDS安全性和有效性的策略.
主要方法:
- 这篇观点论文回顾了关于设计对用户行为影响的现有文献.
- 它讨论了AI算法开发和UI设计之间的关系.
- 它提供了一个UI设计在基于机器学习的CDS中表现出偏见的作用的例子.
主要成果:
- 设计对用户行为的影响在诸如行为经济学等领域已经得到了很好的证实.
- 用户界面设计选择可以直接影响基于人工智能的CDS中的偏见.
- 特定的UI设计元素可以无意中强化或减轻算法限制.
结论:
- 用户界面设计是解决基于AI的CDS偏差的一个关键因素,与数据和算法一起.
- 在CDS部署之前,应使用人为因素方法来识别和纠正UI相关的问题.
- 有效的风险沟通策略对于管理用户感知和减轻偏见至关重要.
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