School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland.
Department of Medicine (Biomedical Informatics), Stanford University, Stanford, California, USA.
J Am Med Inform Assoc. 2021 Jan 15;28(1):190-192. doi: 10.1093/jamia/ocaa210.
The COVID-19 pandemic is presenting a disproportionate impact on minorities in terms of infection rate, hospitalizations, and mortality. Many believe artificial intelligence (AI) is a solution to guide clinical decision-making for this novel disease, resulting in the rapid dissemination of underdeveloped and potentially biased models, which may exacerbate the disparities gap. We believe there is an urgent need to enforce the systematic use of reporting standards and develop regulatory frameworks for a shared COVID-19 data source to address the challenges of bias in AI during this pandemic. There is hope that AI can help guide treatment decisions within this crisis; yet given the pervasiveness of biases, a failure to proactively develop comprehensive mitigation strategies during the COVID-19 pandemic risks exacerbating existing health disparities.
在感染率、住院率和死亡率方面，COVID-19 疫情对少数族裔造成了不成比例的影响。许多人认为人工智能（AI）是指导针对这种新型疾病进行临床决策的一种解决方案，导致欠发达且可能存在偏差的模型迅速传播，这可能会加剧差距。我们认为迫切需要强制使用报告标准，并为共享 COVID-19 数据源制定监管框架，以解决疫情期间 AI 中存在的偏差挑战。人们希望 AI 可以帮助指导这场危机中的治疗决策；然而，鉴于偏见的普遍性，如果在 COVID-19 大流行期间未能积极制定全面的缓解策略，可能会加剧现有的健康差距。
