Bias at warp speed: how AI may contribute to the disparities gap in the time of COVID-19. (17th August 2020)

• Record Type: Journal Article
• Authors: Röösli, Eliane; Rice, Brian; Hernandez-Boussard, Tina
• Is Part Of: Journal of the American Medical Informatics Association. Volume 28:Number 1(2021)
• Page Start: 190
• Page End: 192
• Publication Date: 2020-08-17
• Subjects: COVID -- bias -- artificial intelligence -- disparities, reporting standards ; Medical informatics -- Periodicals; Information Services -- Periodicals; Medical Informatics -- Periodicals; Médecine -- Informatique -- Périodiques; Informatica; Geneeskunde; Informatique médicale; Computer network resources; Electronic journals; 610.285
• DOI: 10.1093/jamia/ocaa210
• Languages: English
• ISSNs: 1067-5027

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.