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Bias at warp speed: how AI may contribute to the disparities gap in the time of COVID-19
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 underdeve...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7454645/ https://www.ncbi.nlm.nih.gov/pubmed/32805004 http://dx.doi.org/10.1093/jamia/ocaa210 |
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author | Röösli, Eliane Rice, Brian Hernandez-Boussard, Tina |
author_facet | Röösli, Eliane Rice, Brian Hernandez-Boussard, Tina |
author_sort | Röösli, Eliane |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7454645 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-74546452020-08-31 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 J Am Med Inform Assoc Perspective 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. Oxford University Press 2020-08-17 /pmc/articles/PMC7454645/ /pubmed/32805004 http://dx.doi.org/10.1093/jamia/ocaa210 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model) |
spellingShingle | Perspective Röösli, Eliane Rice, Brian Hernandez-Boussard, Tina Bias at warp speed: how AI may contribute to the disparities gap in the time of COVID-19 |
title | Bias at warp speed: how AI may contribute to the disparities gap in the time of COVID-19 |
title_full | Bias at warp speed: how AI may contribute to the disparities gap in the time of COVID-19 |
title_fullStr | Bias at warp speed: how AI may contribute to the disparities gap in the time of COVID-19 |
title_full_unstemmed | Bias at warp speed: how AI may contribute to the disparities gap in the time of COVID-19 |
title_short | Bias at warp speed: how AI may contribute to the disparities gap in the time of COVID-19 |
title_sort | bias at warp speed: how ai may contribute to the disparities gap in the time of covid-19 |
topic | Perspective |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7454645/ https://www.ncbi.nlm.nih.gov/pubmed/32805004 http://dx.doi.org/10.1093/jamia/ocaa210 |
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