Browsing by Author "Shi, Jiamin"
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Item Ageism and artificial intelligence: protocol for a scoping review(2022) Chu, Charlene H.; Leslie, Kathleen; Shi, Jiamin; Nyrup, Rune; Bianchi, Andria; Khan, Shehroz; Rahimi, Samira Abbasgholizadeh; Lyn, Alexandra; Grenier, AmandaArtificial intelligence (AI) has emerged as a major driver of technological development in the 21st century, yet little attention has been paid to algorithmic biases toward older adults. This paper documents the search strategy and process for a scoping review exploring how age-related bias is encoded or amplified in AI systems as well as the corresponding legal and ethical implications.Item Digital ageism: challenges and opportunities in artificial intelligence for older adults(2022) Chu, Charlene H.; Nyrup, Rune; Leslie, Kathleen; Shi, Jiamin; Bianchi, Andria; Lyn, Alexandra; McNicholl, Molly; Khan, Shehroz; Rahimi, Samira; Grenier, AmandaArtificial 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.