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Ideal Facial Proportions in Generative Artificial Intelligence: What Does Artificial Intelligence Consider an
Sindhura Sridhar1, Richmond L Laryea2, Harry D Vildibill2
1Texas A&M University College of Medicine, Houston, Texas, USA.
Facial Plastic Surgery & Aesthetic Medicine
|June 26, 2025
Summary
Generative artificial intelligence (AI) models create faces that differ from classical proportions, suggesting AI biases or evolving beauty standards. These AI-generated ideal faces may not align with traditional aesthetic principles.
Area of Science:
- Medical Aesthetics
- Computer Science
- Anthropometry
Background:
- Investigating facial proportions and characteristics considered ideal and attractive by generative AI.
- Understanding the aesthetic outputs of current popular text-to-image AI models.
Purpose of the Study:
- To compare facial proportions generated by AI with neoclassical canons.
- To identify discrepancies in perceived facial attractiveness between AI models and classical standards.
Main Methods:
- Generating "attractive" and "ideal" face images using five text-to-image AI models.
- Measuring facial proportions of generated images and comparing them to facial thirds and fifths.
- Statistical analysis including ANOVA and unpaired Student's t-test to compare proportions.
Main Results:
- Generated faces were predominantly female (70%) and Caucasian (75%).
- Significant differences observed in horizontal and vertical facial segments compared to classical proportions (p < 0.001).
- AI-generated "ideal" faces had smaller middle horizontal segments and "attractive" faces had larger lower horizontal segments.
Conclusions:
- Generative AI models define attractive and ideal faces differently than classical proportions.
- Discrepancies may indicate inherent AI model biases.
- These differences could also reflect evolving cultural perceptions of beauty.
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