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Recapitulation of Ageism in Artificial Intelligence-Generated Images: Longitudinal Comparative Study.

Lindsey Martens1, Nicole Virgin1, Phillip Hoffarth1

  • 1Department of Geriatrics, School of Medicine and Health Sciences, University of North Dakota, 1301 N Columbia Rd, Grand Forks, ND, 58202, United States, 1 7017774455.

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Summary

Generative AI image tools perpetuate digital ageism, consistently portraying older adults as White and with neutral emotions, despite societal shifts towards positive aging views. This bias persists over time, highlighting a need for more inclusive AI development.

Keywords:
ageismagingartificial intelligencedigital ageism, geriatrics

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Area of Science:

  • Artificial intelligence (AI) and its societal impact.
  • Gerontology and the study of aging.
  • Media representation and bias.

Background:

  • Positive media portrayals of aging enhance older adults' health and longevity.
  • Generative AI may amplify age-related societal biases, termed digital ageism.
  • Research is needed on the evolution of digital ageism in AI images.

Purpose of the Study:

  • To examine changes in visual characteristics of digital ageism in AI-generated older adult images over time.
  • To understand the interaction between AI advancements, aging attitudes, and digital media's effect on older adults.

Main Methods:

  • Longitudinal comparison of 164 AI-generated images from DALL-E 2 (2022 vs. 2023).
  • Utilized identical geriatric lexicon text prompts for image generation.
  • Evaluated demographic (gender, race, socioeconomic status) and emotional characteristics; analyzed using ANOVA.

Main Results:

  • Predominantly White-racialized older adults depicted (5x higher than other races) in both years.
  • Increased representation of Asian-racialized (20 to 31) and other racialized individuals (6 to 14).
  • Consistent middle-class socioeconomic status representation; neutral emotional expressions in images despite neutral prompts.

Conclusions:

  • AI image generators persist in creating digital ageism, despite positive societal aging narratives.
  • Lack of improved emotional representation in AI images highlights persistent ageist visual characteristics.
  • Findings underscore the need to address and mitigate digital ageism in AI-generated content.