Portraits made to measure : manipulating social judgments about individuals with a statistical face model

The social judgments people make on the basis of the facial appearance of strangers strongly affect their behavior in different contexts. However, almost nothing is known about the physical information underlying these judgments. In this article, we present a new technology (a) to quantify the information in faces that is used for social judgments and (b) to manipulate the image of a human face in a way which is almost imperceptible but changes the personality traits ascribed to the depicted person. This method was developed in a high-dimensional face space by identifying vectors that capture maximum variability in judgments of personality traits. Our method of manipulating the salience of these vectors in faces was successfully transferred to novel photographs from an independent database. We evaluated this method by showing pairs of face photographs which differed only in the salience of one of six personality traits. Subjects were asked to decide which face was more extreme with respect to the trait in question. Results show that the image manipulation produced the intended attribution effect. All response accuracies were significantly above chance level. This approach to understanding and manipulating how a person is socially perceived could be useful in psychological research and could also be applied in advertising or the film industries.