AI-faces by Illinois: a database of AI-generated faces depicting children
Chao, Tim Wei-Ting
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https://hdl.handle.net/2142/129969
Description
Title
AI-faces by Illinois: a database of AI-generated faces depicting children
Author(s)
Chao, Tim Wei-Ting
Issue Date
2025-07-21
Director of Research (if dissertation) or Advisor (if thesis)
Rizzo, Michael T.
Committee Member(s)
Straka, Brenda C
Department of Study
Psychology
Discipline
Psychology
Degree Granting Institution
University of Illinois Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
Child Faces
Face Database
Artificial Intelligence
Ai
Stimuli
Language
eng
Abstract
Human faces serve as gateways of impression formation during human interactions and are widely used in psychological research. However, existing databases using real images of children could constrain the types of research questions that can be ethically pursued and potentially raises concerns particularly regarding the use of children’s faces without fully informed consent. The present paper introduces “AI-Faces by Illinois”— a database of 1,152 photorealistic, AI-generated child faces. These images vary systematically by perceived age (3, 6, 10, 15 years), gender (male, female), race/ethnicity (Black, East Asian, Latino/a/e, Middle Eastern/North African, Native American, Pacific Islander, South Asian, White), and emotional expression (10 smiling, 4 angry, 4 sad per group). A norming study provides subjective ratings of each image along key psychological dimensions. Critically, results indicate that faces across race and gender groups were rated as equally real, and many well-documented perceptual biases observed with real faces—such as the Own-Race Bias—also generalize to AI-generated faces. These validation data highlight methodological advantages of using AI-generated child faces in developmental psychology research.
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