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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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Detalles Bibliográficos
Autor principal: Okolo, Chinasa T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
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.
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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
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