Digital Ageism: Challenges and Opportunities in Artificial Intelligence for Older Adults.
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Authors
Lyn, Alexandra
McNicholl, Molly
Publication Date
2022-08-12Journal Title
Gerontologist
ISSN
0016-9013
Publisher
Oxford University Press (OUP)
Type
Article
This Version
AM
Metadata
Show full item recordCitation
Chu, C. H., Nyrup, R., Leslie, K., Shi, J., Bianchi, A., Lyn, A., McNicholl, M., et al. (2022). Digital Ageism: Challenges and Opportunities in Artificial Intelligence for Older Adults.. Gerontologist https://doi.org/10.1093/geront/gnab167
Abstract
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.
Keywords
digital ageism, ageism, artificial intelligence, bias, technology
Sponsorship
Leverhulme Trust, through the Leverhulme Centre for the Future of Intelligence
Funder references
Wellcome Trust (213660/Z/18/Z)
Leverhulme Trust (RC-2015-067)
Identifiers
External DOI: https://doi.org/10.1093/geront/gnab167
This record's URL: https://www.repository.cam.ac.uk/handle/1810/330156
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