Achieving Health Equity for All Canadians: Is AI Currently Up to the Task?

Stephanie Garies, Jessalyn K Holodinsky, Jason E Black, Tyler Williamson
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Abstract

Artificial intelligence (AI) deployed into healthcare settings is touted as an exciting approach for improving health equity. However, several issues need to be addressed before this could be achieved, including improving the collection and use of the social determinants of health data, enhancing data interoperability, closing the digital divide and conducting rigorous assessment and evaluation of AI applications to ensure that they achieve fair and equitable outcomes in real-world settings. Importantly, we should not neglect evidence-based strategies that will truly advance health equity, such as adequate housing, poverty reduction, accessible mental healthcare, food security and many other structural and social determinants of health.

为所有加拿大人实现健康公平:人工智能目前能胜任这项任务吗?
将人工智能(AI)部署到医疗保健环境中,被吹捧为改善医疗公平的一种令人兴奋的方法。然而,在实现这一目标之前,需要解决几个问题,包括改进卫生数据的社会决定因素的收集和使用,加强数据互操作性,缩小数字鸿沟,并对人工智能应用进行严格的评估和评价,以确保它们在现实环境中取得公平公正的结果。重要的是,我们不应忽视将真正促进卫生公平的循证战略,例如适足住房、减贫、可获得的精神卫生保健、粮食安全和许多其他健康结构和社会决定因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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