Learning Faces as Concepts Rather Than Percepts Improves Face Recognition

Our ability to recognize familiar faces is remarkable. During the process of becoming familiar with new people we acquire both perceptual and conceptual information about them. Which of these two types of information contributes to our ability to recognize a person in future encounters? Previously, we showed that associating faces with person-related conceptual information (e.g., name, occupation) during learning improves face recognition. Here, we provide further evidence and assess several possible accounts to the conceptual encoding benefit in face recognition. In a series of experiments, participants were asked to make perceptual (e.g., how round/symmetric is the face?) or conceptual (e.g., how trustworthy/ intelligent does the face look?) evaluations about faces. We found better face recognition following conceptual than perceptual encoding. We further showed that this effect cannot be attributed to more global than part-based feature processing, more variable ratings, or more elaborative encoding during conceptual than perceptual evaluations. Finally, we showed that the conceptual over perceptual encoding advantage reflects a conceptual encoding benefit rather than a perceptual encoding cost. Overall these findings show that conceptual evaluations do not improve recognition by modifying the perceptual representation of a face (e.g., elaboration, global processing). Instead, we propose that face recognition benefits from representing faces as socially meaningful concepts rather than percepts during learning. These results highlight the importance of linking cognition and perception to understand recognition.