Bias at warp speed: how AI may contribute to the disparities gap in the time of COVID-19

Author:

Röösli Eliane12,Rice Brian3,Hernandez-Boussard Tina24

Affiliation:

1. School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland

2. Department of Medicine (Biomedical Informatics), Stanford University, Stanford, California, USA

3. Department of Emergency Medicine, Stanford University, Stanford, California, USA

4. Department of Biomedical Data Sciences, Stanford University, Stanford, California, USA

Abstract

Abstract 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.

Publisher

Oxford University Press (OUP)

Subject

Health Informatics

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