Can people detect the trustworthiness of strangers based on their facial appearance?

Bastian Jaeger*, Bastiaan Oud, Tony Williams, Eva G. Krumhuber, Ernst Fehr, Jan B. Engelmann

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Although cooperation can lead to mutually beneficial outcomes, cooperative actions only pay off for the individual if others can be trusted to cooperate as well. Identifying trustworthy interaction partners is therefore a central challenge in human social life. How do people navigate this challenge? Prior work suggests that people rely on facial appearance to judge the trustworthiness of strangers. However, the question of whether these judgments are actually accurate remains debated. The present research examines accuracy in trustworthiness detection from faces and three moderators proposed by previous research. We investigate whether people show above-chance accuracy (a) when they make trust decisions and when they provide explicit trustworthiness ratings, (b) when judging male and female counterparts, and (c) when rating cropped images (with non-facial features removed) and uncropped images. Two studies showed that incentivized trust decisions (Study 1, n = 131 university students) and incentivized trustworthiness predictions (Study 2, n = 266 university students) were unrelated to the actual trustworthiness of counterparts. Accuracy was not moderated by stimulus type (cropped vs. uncropped faces) or counterparts' gender. Overall, these findings suggest that people are unable to detect the trustworthiness of strangers based on their facial appearance, when this is the only information available to them.

Original languageEnglish
Pages (from-to)296-303
Number of pages8
JournalEvolution and Human Behavior
Volume43
Issue number4
Early online date2 May 2022
DOIs
Publication statusPublished - Jul 2022

Bibliographical note

Publisher Copyright:
© 2022 The Authors

Keywords

  • Accuracy
  • Cooperation
  • Face perception
  • Prediction
  • Trust
  • Trustworthiness

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