From likely to likable: The role of statistical typicality in human social assessment of faces
Journal
Proceedings of the National Academy of Sciences of the United States of America
Journal Volume
117
Journal Issue
47
Pages
29371-29380
Date Issued
2020
Author(s)
Abstract
Humans readily form social impressions, such as attractiveness and trustworthiness, from a stranger's facial features. Understanding the provenance of these impressions has clear scientific importance and societal implications. Motivated by the efficient coding hypothesis of brain representation, as well as Claude Shannon's theoretical result that maximally efficient representational systems assign shorter codes to statistically more typical data (quantified as log likelihood), we suggest that social "liking" of faces increases with statistical typicality. Combining human behavioral data and computational modeling, we show that perceived attractiveness, trustworthiness, dominance, and valence of a face image linearly increase with its statistical typicality (log likelihood). We also show that statistical typicality can at least partially explain the role of symmetry in attractiveness perception. Additionally, by assuming that the brain focuses on a task-relevant subset of facial features and assessing log likelihood of a face using those features, our model can explain the "ugliness-in-averageness" effect found in social psychology, whereby otherwise attractive, intercategory faces diminish in attractiveness during a categorization task. © 2020 National Academy of Sciences. All rights reserved.
Subjects
Attention; Attractiveness; Efficient coding; Face evaluation; Statistical typicality
SDGs
Other Subjects
article; attention; brain; computer model; controlled study; facies; human; human experiment; perception; psychology; anatomy and histology; computer simulation; decision making; esthetics; face; facial recognition; female; male; physiology; psychological model; psychology; social dominance; statistical model; trust; young adult; Beauty; Brain; Computer Simulation; Face; Facial Recognition; Female; Humans; Judgment; Likelihood Functions; Male; Models, Psychological; Social Dominance; Trust; Young Adult
Type
journal article