In our everyday lives, we encounter many different people, while shopping for groceries, when passing them by in the street, or while looking for prospective partners on dating apps. Knowingly or not, we automatically judge others’ faces on factors like their age or attractiveness, as well as certain traits, such as how trustworthy they look. These judgments happen very quickly, from just a glance at a person’s face.
While these face judgments are quick and automatic, they can result in biased decisions with serious downsides. How trustworthy someone looks can lead to real-world consequences, predicting outcomes such as the likelihood to be hired for a job and political success in elections. In more serious cases, perceived trustworthiness also predicts sentencing decisions in the criminal justice system, with untrustworthy-looking prisoners more likely to be assigned harsher punishments including the death penalty.
Due to the potentially severe consequences of these face judgments, we were interested in whether it was possible to reduce people’s tendency to make judgments based on facial appearance. How might we go about changing these judgments, which occur very quickly and are seemingly outside our conscious control? In our research, we addressed this issue by creating a short “counterstereotype” training where faces that are typically considered trustworthy were paired with short sentences describing untrustworthy behaviors (example: “punched someone in the face”) and faces that are typically considered untrustworthy were paired with trustworthy behaviors (example: “saved a lost kitten”). The purpose of the training was to alter the associations we typically have with trustworthy and untrustworthy faces and to overcome the ingrained biases we have with those faces and their features.
If the counterstereotype training were effective, then we would expect that face biases based on facial trustworthiness to be reduced—or even eliminated—after training. To see if the training worked, we compared participants who underwent the training with a group who saw the same untrustworthy and untrustworthy faces but with names instead of behaviors.
We used three different tasks to assess judgments for faces high and low in trustworthiness:
- A trust game, where participants decided how much money to entrust to other players.
For each round of the game, the amount of money entrusted to the other partner is tripled, and they could return a portion of that amount back in reciprocation. More money entrusted in this game is an index of trustworthiness.
- A mock hiring task where participants read through job applications that included short bios as well as the applicant’s face. They rated each applicant’s suitability for an interview and for the job.
- A word categorization task that measures the positivity or negativity of the participant’s automatic reaction to different kinds of faces (trustworthy or untrustworthy), based on how quickly they respond to a positive or negative word that is paired with the face. For example, seeing a trustworthy face makes it faster to categorize the word “Nice” as positive.
Across the three tasks, the untrained group expectedly gave more money to people with trustworthy faces, deemed them more suitable for jobs, and exhibited a strong automatic positive evaluation of them. In contrast, all these biases were either reduced or eliminated for those who got our “counterstereotype” training. Our short training successfully eliminated biases involving facial trustworthiness, resulting in trustworthy and untrustworthy faces being judged equally. This happened in the context of hiring decisions as well as with people’s automatic snap judgments of faces. Researchers tend to think that these biases based on facial appearance are ingrained and very difficult to change, but here we show that the right kind of experience and training might be able to combat these biases. More research is needed to determine how long this kind of training might last, but the next time you pass by a stranger or swipe around looking for partners, remember that we do not necessarily have to judge books by their covers.
For Further Reading
Bar, M., Neta, M., & Linz, H. (2006). Very first impressions. Emotion, 6(2), 269-278.
Hehman, E., Stolier, R., Freeman, J.B., Flake, J.K., Xie, S.Y. (2018). Toward of comprehensive model of face impressions: What we know, what we do not, and paths forward. Personality and Social Psychology Compass. 1-16.
Oosterhof, N. N., & Todorov, A. (2008). The functional basis of face evaluation. Proceedings of the National Academy of Sciences, 105(32), 11087-11092.
Wilson, J. P., & Rule, N. O. (2015). Facial trustworthiness predicts extreme criminal-sentencing outcomes. Psychological Science, 26(8), 1325-1331.
Kao-Wei Chua is a postdoctoral scholar in the Social Psychology Department at New York University. He works with Jonathan Freeman at the Social Cognitive and Neural Sciences Lab.