In humans, femininity shapes women's interactions with both genders, but its influence on animals remains unknown. Using 10 years of data on a wild primate, we developed an artificial intelligence-based method to estimate facial femininity from naturalistic portraits. Our method explains up to 30% of the variance in perceived femininity in humans, competing with classical methods using standardized pictures taken under laboratory conditions. We then showed that femininity estimated on 95 female mandrills significantly correlated with various socio-sexual behaviors. Unexpectedly, less feminine female mandrills were approached and aggressed more frequently by both sexes and received more male copulations, suggesting a positive valuation of masculinity attributes rather than a perception bias. This study contributes to understand the role of femininity on animal's sociality and offers a framework for non-invasive research on visual communication in behavioral ecology.
Keywords: Artificial intelligence; Biology of gender; Ethology.
© 2023 The Authors.