机器学习中的生物伦理学原则-医疗保健应用设计:实现健康正义和健康公平。

Harvard public health review (Cambridge, Mass.) Pub Date : 2024-01-01 Epub Date: 2024-08-09 DOI:10.54111/0001/aaaa1
Roschelle L Fritz, Connie Kim Yen Nguyen-Truong, Thomas May, Katherine Wuestney, Diane J Cook
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引用次数: 0

摘要

以人工智能(AI)为特色的医疗技术正变得越来越普遍。一些保健人工智能对代表性不足的人和人群表现出偏见。尽管许多计算机科学家和医疗保健专业人员都认为,需要消除或减轻医疗保健人工智能中的偏见,但关于如何在产品设计和实施中实现自主等生物伦理原则的信息很少。这个短期课程以健康的社会决定因素以及健康正义和健康公平的立场为框架,以支持计算机科学家和医疗保健专业人员建立和部署道德医疗保健人工智能。在这门短期课程中,我们将介绍以人为本的设计背景下的自主生物伦理原则(模块1)和设计思维模型的共享选择权,建议在设计过程中嵌入伦理原则的四项活动(模块2)。然后,我们讨论获得不同群体的观点的重要性,以尽量减少伤害,并支持代表性不足的人的基本人类价值观,以支持健康公平和健康正义理想(模块3)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bioethics Principles in Machine Learning-Healthcare Application Design: Achieving Health Justice and Health Equity.

Health technologies featuring artificial intelligence (AI) are becoming more common. Some healthcare AIs are exhibiting bias towards underrepresented persons and populations. Although many computer scientists and healthcare professionals agree that eliminating or mitigating bias in healthcare AIs is needed, little information exists regarding how to operationalize bioethics principles like autonomy in product design and implementation. This short course is framed with a Social Determinants of Health lens and a health justice and health equity stance to support computer scientists and healthcare professionals in building and deploying ethical healthcare AI. In this short course we introduce the bioethics principle of autonomy in the context of human-centered design (Module 1) and share options for design thinking models, suggesting four activities to embed ethics principles during design (Module 2). We then discuss the importance of gaining the perspectives of diverse groups to minimize harm and support the fundamental human values of underrepresented persons in support of health equity and health justice ideals (Module 3).

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