Bias at Warp Speed: How AI may Contribute to the Disparities Gap in the Time of COVID-19

Röösli, Eliane; Rice, Brian; Hernandez-Boussard, Tina

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 under-developed 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.