Summary: Researchers report we make up our minds about others after seeing their faces for a fraction of a second, and that these snap judgments, which are usually incorrect, predict economic, legal, voting and other decisions.
The pseudoscience of physiognomy – judging people’s character from their faces – has been around for centuries, but a new Princeton University study shows that people make such judgments based on their own experiences.
The results appear in the journal Nature Human Behavior.
In previous research, senior author Alexander Todorov, a professor of psychology, and colleagues showed that we make up our minds about others after seeing their faces for a fraction of a second – and that these snap judgments, which are usually incorrect, predict economic, legal, voting and other decisions. “People form instantaneous impressions from facial appearance, but what drives these impressions?” Todorov says.
Most previous research has focused on identifying configurations of facial features that lead to specific impressions, but there are other important determinants of these impressions that are grounded in one’s idiosyncratic history of exposure to faces. In their new study, Todorov and his colleagues propose a new direction in the study of inferences from faces. They argue that any face can be positioned in a statistical distribution of faces extracted from the environment and that understanding inferences from faces requires consideration of their statistical position on that distribution – or how typical facial features are to the viewer.
The study’s participants were shown hundreds of faces and asked to judge their trustworthiness, attractiveness, competence and other characteristics. The results showed that exposure to different faces not only shifts what faces people perceive as typical, but also what faces they evaluate more positively (more typical faces are evaluated more positively).
“Our results show that the mere statistical position of faces imbues them with social meaning — faces are evaluated more negatively the more they deviate from a learned central tendency, or what each person considers a typical face,” Todorov says. “These determinants of impressions are not about facial features per se but about one’s learning of faces. In other words, although there is no ‘average’ human face, you like faces that are closer to your own definition of a typical face. Our findings have important implications for understanding cross-cultural and inter-group differences in evaluation of faces.”
Funding: Study funded by NWO Rubicon, United States-Israel Binational Science Foundation.
Source: John Cramer – Princeton
Image Source: NeuroscienceNews.com image is credited to BruceBlaus and is licensed CC BY 3.0.
Original Research: Full open access research for “Statistical learning shapes face evaluation” by Ron Dotsch, Ran R. Hassin & Alexander Todorov in Nature Human Behavior. Published online November 14 2016 doi:10.1038/s41562-016-0001
Statistical learning shapes face evaluation
The belief in physiognomy—the art of reading character from faces—has been with us for centuries. People everywhere infer traits (for example, trustworthiness) from faces, and these inferences predict economic, legal and even voting decisions. Research has identified many configurations of facial features that predict specific trait inferences, and detailed computational models of such inferences have recently been developed. However, these configurations do not fully account for trait inferences from faces. Here, we propose a new direction in the study of inferences from faces, inspired by a cognitive–ecological and implicit-learning approach. Any face can be positioned in a statistical distribution of faces extracted from the environment. We argue that understanding inferences from faces requires consideration of the statistical position of the faces in this learned distribution. Four experiments show that the mere statistical position of faces imbues them with social meaning: faces are evaluated more negatively the more they deviate from a learned central tendency. Our findings open new possibilities for the study of face evaluation, providing a potential model for explaining both individual and cross-cultural variation, as individuals are immersed in varying environments that contain different distributions of facial features.
“Statistical learning shapes face evaluation” by Ron Dotsch, Ran R. Hassin & Alexander Todorov in Nature Human Behavior. Published online November 14 2016 doi:10.1038/s41562-016-0001