This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: Imagine sitting on a city bus full of strangers. Look around at the people riding with you.
If you needed help, how would you choose whom to trust? By scanning people's faces, your brain is already making interpretations about their personalities by judging certain facial features. For decades, neuroscientists have been studying how facial bias ultimately influences the way people behave, but the experiments have been limited by the words used to describe people.
Studies typically ask participants to rate faces on a fixed set of rating scales provided by the experimenter using words like "competent" or "trustworthy." Now, a team of researchers at Caltech has developed a way to study trait judgment of faces without using any word labels. "We asked people to directly interpret the similarity in personality between faces," explains Yue Xu (Ph.D. '26), who led the study and is first author on a paper about it published Oct. 19 in Nature Human Behaviour. "It's a more natural way of thinking about people's personalities without being cued to think about specific trait words." In the past, studies aiming to link our perception of faces with personality traits typically involved study subjects who looked at faces on a computer monitor, then made a quick judgment by answering questions like, "How trustworthy does this person look to you on a scale from 1 to 5?" The results of prior work have linked such snap opinions to decisions people make in real life about politicians, hiring considerations and more.
But they also raise questions about what happens if you speak a different language, if you are only given a particular set of words concocted by the experimenter, or if you're unable to use language at all. The new study is the latest effort by Ralph Adolphs (Ph.D. '93), Bren professor of psychology, neuroscience and biology at Caltech and senior author of the paper, to reduce bias in face perception studies. Instead of rating faces on trait words, Adolphs, Xu and the team asked more than 3,000 study participants in two different experiments to look at faces on a computer screen without giving them any rating scale.
Instead, participants were instructed to arrange the faces based on how similar or different they appeared to be based on personality traits; similar faces were placed close to one another, and different faces were placed farther apart. The first experiment focused on a set of predominantly white faces to allow the researchers to do a direct comparison with a previous study that used those same faces. The second experiment featured Black and Asian faces, in addition to white faces, to examine how the first experiment's findings extend to individuals of different races.
Using computational methods to assess how participants had arranged faces on their screen, the researchers were able to identify five key trait dimensions present across both experiments: approachability, warmth, competence, morality and youthfulness. As expected by the researchers, the second experiment also showed prominent effects of stereotypes associated with race. "It's important to note that what we are studying is people's bias and stereotypes, because they actually don't know about these people outside of this task," Xu says.
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