Digital Ageism: Challenges and Opportunities in Artificial Intelligence for Older Adults

Author:

Chu Charlene H12ORCID,Nyrup Rune3ORCID,Leslie Kathleen4ORCID,Shi Jiamin15ORCID,Bianchi Andria56ORCID,Lyn Alexandra4,McNicholl Molly78,Khan Shehroz29ORCID,Rahimi Samira1011ORCID,Grenier Amanda1213ORCID

Affiliation:

1. Lawrence S. Bloomberg Faculty of Nursing, University of Toronto, Toronto, Ontario, Canada

2. KITE—Toronto Rehabilitation Institute, University Health Network, Toronto, Ontario, Canada

3. Leverhulme Centre for the Future of Intelligence, University of Cambridge, Cambridge, UK

4. Faculty of Health Disciplines, Athabasca University, Athabasca, Alberta, Canada

5. Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada

6. University Health Network, Toronto, Ontario, Canada

7. University of Cambridge, Cambridge, UK

8. London School of Hygiene and Tropical Medicine, University of London, London, UK

9. Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada

10. Department of Family Medicine, McGill University, Montreal, Quebec, Canada

11. Mila—Quebec AI Institute, Montréal, Quebec, Canada

12. Factor-Inwentash Faculty of Social Work, University of Toronto, Toronto, Ontario, Canada

13. Baycrest Hospital, Toronto, Ontario, Canada

Abstract

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.

Funder

Social Sciences and Humanities Research Council of Canada

Publisher

Oxford University Press (OUP)

Subject

Geriatrics and Gerontology,Gerontology,General Medicine

Reference74 articles.

1. No country for older people? Age and the digital divide;Abbey;Journal of Information, Communication and Ethics in Society,2009

2. How artificial intelligence can make employment discrimination worse;Ajunwa;The Independent,2018

3. Beware of automated hiring;Ajunwa;The New York Times,2019

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