Presentation
Modeling the Role of AI Bias on Aging Anxiety: A Mediation Analysis
DescriptionThe present study investigates how experienced ageism mediates the relationship between perceived ageism from AI algorithms and age anxiety outcomes among an older adult cohort. We present a secondary data analysis from the Older Adult Annotator Demographic and Attitudinal Survey (OOADA), that contains responses from a nationally representative cohort of U.S. older adults (N = 1483, Age Range = 50 – 90+; 50% Female). Measures consist of participant responses to the previously validated Aging Anxiety Scale (AAS) and the unvalidated Age Experience Survey (AES). We conducted an exploratory factor analysis followed by a confirmatory factor analysis to validate and establish latent variables from both surveys. We tested a structural mediation model to assess whether the AES variable of Experienced Ageism mediated the relationship between the AES variable of attitudes towards algorithmic ageism and the AAS variables of age anxiety: Fear of Losses, Psychological Concern, Physical Appearance (implicit anxieties), and Fear of Old People (explicit anxiety). Experienced ageism mediated the relationship between attitudes toward algorithmic ageism and implicit age anxieties (ps <.05) but not for explicit age anxieties (p = .72). Future work should explore how perceived ageism in AI influences age anxiety and AI technology adoption among older adults.
Event Type
Lecture
TimeTuesday, October 14th12:10pm - 12:30pm CDT
LocationGrand B
Human AI Robot Teaming (AI)
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