医疗保健中的人工智能偏见:使用ImpactPro作为医疗保健从业人员参与反偏见措施的责任案例研究

IF 0.3 Q4 MEDICAL ETHICS

Canadian Journal of Bioethics Pub Date : 2021-06-01 DOI:10.7202/1077639AR

Sam Sargent

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引用次数: 2

摘要

引入ImpactPro来识别具有复杂健康需求的患者表明，医疗保健人工智能中当前的偏见和偏见的影响源于历史上有偏见的做法，导致有偏见的数据集，缺乏监督，以及监督人工智能的从业人员的偏见。为了改善这些结果，医疗保健从业人员需要参与当前反偏见培训的最佳实践。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

AI Bias in Healthcare: Using ImpactPro as a Case Study for Healthcare Practitioners’ Duties to Engage in Anti-Bias Measures

The introduction of ImpactPro to identify patients with complex health needs suggests that current bias and impacts of bias in healthcare AIs stem from historically biased practices leading to biased datasets, a lack of oversight, as well as bias in practitioners who are overseeing AIs. In order to improve these outcomes, healthcare practitioners need to engage in current best practices for anti-bias training.

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来源期刊

Canadian Journal of Bioethics Arts and Humanities-Philosophy

CiteScore

0.50

自引率

0.00%

发文量

审稿时长

35 weeks