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Optimizing human-centered AI for healthcare in the Global South
Over the past 60 years, artificial intelligence (AI) has made significant progress, but most of its benefits have failed to make a significant impact within the Global South. Current practices that have led to biased systems will prevent AI from being actualized unless significant efforts are made t...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Elsevier
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8848006/ https://www.ncbi.nlm.nih.gov/pubmed/35199066 http://dx.doi.org/10.1016/j.patter.2021.100421 |
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author | Okolo, Chinasa T. |
author_facet | Okolo, Chinasa T. |
author_sort | Okolo, Chinasa T. |
collection | PubMed |
description | Over the past 60 years, artificial intelligence (AI) has made significant progress, but most of its benefits have failed to make a significant impact within the Global South. Current practices that have led to biased systems will prevent AI from being actualized unless significant efforts are made to change them. As technical advances in AI and an interest in solving new problems lead researchers and tech companies to develop AI applications that target the health of marginalized communities, it is crucially important to study how AI can be used to empower those on the front lines in the Global South and how these tools can be optimally designed for marginalized communities. This perspective examines the landscape of AI for healthcare in the Global South and the evaluations of such systems and provides tangible recommendations for AI practitioners and human-centered researchers to incorporate in the development of AI systems for use with marginalized populations. |
format | Online Article Text |
id | pubmed-8848006 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-88480062022-02-22 Optimizing human-centered AI for healthcare in the Global South Okolo, Chinasa T. Patterns (N Y) Perspective Over the past 60 years, artificial intelligence (AI) has made significant progress, but most of its benefits have failed to make a significant impact within the Global South. Current practices that have led to biased systems will prevent AI from being actualized unless significant efforts are made to change them. As technical advances in AI and an interest in solving new problems lead researchers and tech companies to develop AI applications that target the health of marginalized communities, it is crucially important to study how AI can be used to empower those on the front lines in the Global South and how these tools can be optimally designed for marginalized communities. This perspective examines the landscape of AI for healthcare in the Global South and the evaluations of such systems and provides tangible recommendations for AI practitioners and human-centered researchers to incorporate in the development of AI systems for use with marginalized populations. Elsevier 2022-01-03 /pmc/articles/PMC8848006/ /pubmed/35199066 http://dx.doi.org/10.1016/j.patter.2021.100421 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Perspective Okolo, Chinasa T. Optimizing human-centered AI for healthcare in the Global South |
title | Optimizing human-centered AI for healthcare in the Global South |
title_full | Optimizing human-centered AI for healthcare in the Global South |
title_fullStr | Optimizing human-centered AI for healthcare in the Global South |
title_full_unstemmed | Optimizing human-centered AI for healthcare in the Global South |
title_short | Optimizing human-centered AI for healthcare in the Global South |
title_sort | optimizing human-centered ai for healthcare in the global south |
topic | Perspective |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8848006/ https://www.ncbi.nlm.nih.gov/pubmed/35199066 http://dx.doi.org/10.1016/j.patter.2021.100421 |
work_keys_str_mv | AT okolochinasat optimizinghumancenteredaiforhealthcareintheglobalsouth |