Detecting the Trustworthiness of Novel Partners in Economic Exchange

Abstract

Because trusting strangers can entail high risk, an ability to infer a potential partner’s trustworthiness would be highly advantageous. To date, however, little evidence indicates that humans are able to accurately assess the cooperative intentions of novel partners by using nonverbal signals. In two studies involving human-human and human-robot interactions, we found that accuracy in judging the trustworthiness of novel partners is heightened through exposure to nonverbal cues and identified a specific set of cues that are predictive of economic behavior. Employing the precision offered by robotics technology to model and control humanlike movements, we demonstrated not only that experimental manipulation of the identified cues directly affects perceptions of trustworthiness and subsequent exchange behavior, but also that the human mind will utilize such cues to ascribe social intentions to technological entities.