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Digital Ageism: Challenges and Opportunities in Artificial Intelligence for Older Adults
Artificial intelligence (AI) and machine learning are changing our world through their impact on sectors including health care, education, employment, finance, and law. AI systems are developed using data that reflect the implicit and explicit biases of society, and there are significant concerns ab...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9372891/ https://www.ncbi.nlm.nih.gov/pubmed/35048111 http://dx.doi.org/10.1093/geront/gnab167 |
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author | Chu, Charlene H Nyrup, Rune Leslie, Kathleen Shi, Jiamin Bianchi, Andria Lyn, Alexandra McNicholl, Molly Khan, Shehroz Rahimi, Samira Grenier, Amanda |
author_facet | Chu, Charlene H Nyrup, Rune Leslie, Kathleen Shi, Jiamin Bianchi, Andria Lyn, Alexandra McNicholl, Molly Khan, Shehroz Rahimi, Samira Grenier, Amanda |
author_sort | Chu, Charlene H |
collection | PubMed |
description | Artificial intelligence (AI) and machine learning are changing our world through their impact on sectors including health care, education, employment, finance, and law. AI systems are developed using data that reflect the implicit and explicit biases of society, and there are significant concerns about how the predictive models in AI systems amplify inequity, privilege, and power in society. The widespread applications of AI have led to mainstream discourse about how AI systems are perpetuating racism, sexism, and classism; yet, concerns about ageism have been largely absent in the AI bias literature. Given the globally aging population and proliferation of AI, there is a need to critically examine the presence of age-related bias in AI systems. This forum article discusses ageism in AI systems and introduces a conceptual model that outlines intersecting pathways of technology development that can produce and reinforce digital ageism in AI systems. We also describe the broader ethical and legal implications and considerations for future directions in digital ageism research to advance knowledge in the field and deepen our understanding of how ageism in AI is fostered by broader cycles of injustice. |
format | Online Article Text |
id | pubmed-9372891 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-93728912022-08-12 Digital Ageism: Challenges and Opportunities in Artificial Intelligence for Older Adults Chu, Charlene H Nyrup, Rune Leslie, Kathleen Shi, Jiamin Bianchi, Andria Lyn, Alexandra McNicholl, Molly Khan, Shehroz Rahimi, Samira Grenier, Amanda Gerontologist Forum Artificial intelligence (AI) and machine learning are changing our world through their impact on sectors including health care, education, employment, finance, and law. AI systems are developed using data that reflect the implicit and explicit biases of society, and there are significant concerns about how the predictive models in AI systems amplify inequity, privilege, and power in society. The widespread applications of AI have led to mainstream discourse about how AI systems are perpetuating racism, sexism, and classism; yet, concerns about ageism have been largely absent in the AI bias literature. Given the globally aging population and proliferation of AI, there is a need to critically examine the presence of age-related bias in AI systems. This forum article discusses ageism in AI systems and introduces a conceptual model that outlines intersecting pathways of technology development that can produce and reinforce digital ageism in AI systems. We also describe the broader ethical and legal implications and considerations for future directions in digital ageism research to advance knowledge in the field and deepen our understanding of how ageism in AI is fostered by broader cycles of injustice. Oxford University Press 2022-01-20 /pmc/articles/PMC9372891/ /pubmed/35048111 http://dx.doi.org/10.1093/geront/gnab167 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of The Gerontological Society of America. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Forum Chu, Charlene H Nyrup, Rune Leslie, Kathleen Shi, Jiamin Bianchi, Andria Lyn, Alexandra McNicholl, Molly Khan, Shehroz Rahimi, Samira Grenier, Amanda Digital Ageism: Challenges and Opportunities in Artificial Intelligence for Older Adults |
title | Digital Ageism: Challenges and Opportunities in Artificial Intelligence for Older Adults |
title_full | Digital Ageism: Challenges and Opportunities in Artificial Intelligence for Older Adults |
title_fullStr | Digital Ageism: Challenges and Opportunities in Artificial Intelligence for Older Adults |
title_full_unstemmed | Digital Ageism: Challenges and Opportunities in Artificial Intelligence for Older Adults |
title_short | Digital Ageism: Challenges and Opportunities in Artificial Intelligence for Older Adults |
title_sort | digital ageism: challenges and opportunities in artificial intelligence for older adults |
topic | Forum |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9372891/ https://www.ncbi.nlm.nih.gov/pubmed/35048111 http://dx.doi.org/10.1093/geront/gnab167 |
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