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dc.contributor.authorChu, Charlene H
dc.contributor.authorNyrup, Rune
dc.contributor.authorLeslie, Kathleen
dc.contributor.authorShi, Jiamin
dc.contributor.authorBianchi, Andria
dc.contributor.authorLyn, Alexandra
dc.contributor.authorMcNicholl, Molly
dc.contributor.authorKhan, Shehroz
dc.contributor.authorRahimi, Samira
dc.contributor.authorGrenier, Amanda
dc.date.accessioned2021-11-02T00:30:23Z
dc.date.available2021-11-02T00:30:23Z
dc.date.issued2022-01-20
dc.identifier.issn0016-9013
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/330156
dc.description.abstractArtificial 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.
dc.description.sponsorshipLeverhulme Trust, through the Leverhulme Centre for the Future of Intelligence
dc.publisherOxford University Press (OUP)
dc.rightsAll rights reserved
dc.rights.urihttp://www.rioxx.net/licenses/all-rights-reserved
dc.subjectdigital ageism
dc.subjectageism
dc.subjectartificial intelligence
dc.subjectbias
dc.subjecttechnology
dc.titleDigital Ageism: Challenges and Opportunities in Artificial Intelligence for Older Adults.
dc.typeArticle
prism.publicationNameGerontologist
dc.identifier.doi10.17863/CAM.77599
dcterms.dateAccepted2021-10-21
rioxxterms.versionofrecord10.1093/geront/gnab167
rioxxterms.versionAM
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.licenseref.startdate2021-10-21
dc.contributor.orcidChu, Charlene H [0000-0002-0333-7210]
dc.contributor.orcidNyrup, Rune [0000-0002-9880-6912]
dc.contributor.orcidLeslie, Kathleen [0000-0003-0581-126X]
dc.contributor.orcidShi, Jiamin [0000-0002-1187-1990]
dc.contributor.orcidBianchi, Andria [0000-0003-3802-0771]
dc.contributor.orcidKhan, Shehroz [0000-0002-1195-4999]
dc.contributor.orcidRahimi, Samira [0000-0003-3781-1360]
dc.contributor.orcidGrenier, Amanda [0000-0003-2251-6035]
dc.identifier.eissn1758-5341
rioxxterms.typeJournal Article/Review
pubs.funder-project-idWellcome Trust (213660/Z/18/Z)
pubs.funder-project-idLeverhulme Trust (RC-2015-067)
cam.issuedOnline2022-01-20
cam.orpheus.successTue Feb 01 19:02:07 GMT 2022 - Embargo updated*
cam.orpheus.counter3
rioxxterms.freetoread.startdate2023-01-20


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