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STRATEGIES TO MITIGATE MACHINE LEARNING BIAS...
Journal article

STRATEGIES TO MITIGATE MACHINE LEARNING BIAS AFFECTING OLDER ADULTS: RESULTS FROM A SCOPING REVIEW

Abstract

Abstract

Digital ageism, defined as age-related bias in artificial intelligence (AI) and technological systems, has emerged as a significant concern for its potential impact on society, health, equity, and older people’s well-being. This scoping review aims to identify mitigation strategies used in research studies to address age-related bias in machine learning literature. We conducted a scoping review following Arksey & O’Malley’s methodology, …

Authors

Chu C; Donato-Woodger S; Khan S; Leslie K; Shi T; Nyrup R; Grenier A

Journal

Innovation in Aging, Vol. 7, No. Supplement_1, pp. 717–718

Publisher

Oxford University Press (OUP)

Publication Date

December 21, 2023

DOI

10.1093/geroni/igad104.2325

ISSN

2399-5300

Labels

Sustainable Development Goals (SDG)