TY - JOUR
T1 - Digital Ageism
T2 - Challenges and Opportunities in Artificial Intelligence for Older Adults
AU - Chu, Charlene H.
AU - Nyrup, Rune
AU - Leslie, Kathleen
AU - Shi, Jiamin
AU - Bianchi, Andria
AU - Lyn, Alexandra
AU - McNicholl, Molly
AU - Khan, Shehroz
AU - Rahimi, Samira
AU - Grenier, Amanda
N1 - Publisher Copyright:
© 2022 The Author(s). Published by Oxford University Press on behalf of The Gerontological Society of America.
PY - 2022/9/1
Y1 - 2022/9/1
N2 - 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.
AB - 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.
KW - Bias
KW - Gerontology
KW - Machine learning
KW - Technology
UR - http://www.scopus.com/inward/record.url?scp=85129235014&partnerID=8YFLogxK
U2 - 10.1093/geront/gnab167
DO - 10.1093/geront/gnab167
M3 - Review article
C2 - 35048111
AN - SCOPUS:85129235014
SN - 0016-9013
VL - 62
SP - 947
EP - 955
JO - The Gerontologist
JF - The Gerontologist
IS - 7
ER -