A generated image repository of aging faces.

Faces are a rich source of information for humans and a substantial amount of behavioral science research uses face stimuli to assess person perception. Unfortunately, this body of research is limited by an overreliance on young, predominantly white faces normed on young adult perceivers. To address these limitations, we created an open-access database of AI-generated faces that represents the same individuals at three life stages (young adulthood, middle age, and older adulthood) including equal numbers of males and females. Using advanced generative algorithms, the approach digitally aged 62 young individuals, thus preserving identity-specific features while realistically portraying age-related changes. The resulting database comprises 186 images. Each image has been age-normed and validated for authenticity. Although the database will be useful for many research questions, the stimuli are especially well-suited for research on age comparisons because the same individuals can be presented at different ages.