Item-level Implicit Affective Measures Reveal the Uncanny Valley of Robot Faces

As the opportunity to interact with humanoid robots and virtual avatars increases, the emotional impact of the interaction with these artificial agents becomes an important consideration. The uncanny valley effect is a psychological phenomenon relevant to such a consideration. Although the uncanny valley remained untested for several decades, recent empirical studies confirmed the uncanny valley effect when human observers rated their liking of robots’ faces. To uncover the uncanny valley in affective responses, the present study used two implicit affective measures, affective priming and single-category IAT, and derived the positivity scores for each of the images of robot faces, which was then plotted against the humanness rating of the robot faces. The results demonstrated the uncanny valley effect in these implicit measures. The finding indicates the effectiveness of using these implicit measures to assess affective responses to individual items rather than to groups of items, and it suggests the potential of these behavioral paradigms for wider application outside laboratory research.