Biases in human perception of facial age are present and more exaggerated in current AI technology.

Our estimates of a person's age from their facial appearance suffer from several well-known biases and inaccuracies. Typically, for example, we tend to overestimate the age of smiling faces compared to those with a neutral expression, and the accuracy of our estimates decreases for older faces. The growing interest in age estimation using artificial intelligence (AI) technology raises the question of how AI compares to human performance and whether it suffers from the same biases. Here, we compared human performance with the performance of a large sample of the most prominent AI technology available today. The results showed that AI is even less accurate and more biased than human observers when judging a person's age-even though the overall pattern of errors and biases is similar. Thus, AI overestimated the age of smiling faces even more than human observers did. In addition, AI showed a sharper decrease in accuracy for faces of older adults compared to faces of younger age groups, for smiling compared to neutral faces, and for female compared to male faces. These results suggest that our estimates of age from faces are largely driven by particular visual cues, rather than high-level preconceptions. Moreover, the pattern of errors and biases we observed could provide some insights for the design of more effective AI technology for age estimation from faces.

The Compositionality of Facial Expressions.

The principle of compositionality, an important postulation in language and cognition research, posits that the meaning of a complex expression is determined by the meaning of its constituting parts and the operation performed on those parts. Here, we provide strong evidence that this principle plays a significant role also in interpreting facial expressions. In three studies in which perceivers interpreted sequences of two emotional facial expression images, we show that the composite meaning of facial expressions results from the meaning of its constituting expressions and an algebraic operation performed on those expressions. Our study offers a systematic account as to how the meaning of facial expressions (single and sequences) are being formed and perceived. In a broader context, our results raise the possibility that the principle of compositionality may apply to human communication modalities beyond spoken language, whereby a minimal number of components are expanded to a much greater number of meanings.

For Your Local Eyes Only: Culture-Specific Face Typicality Influences Perceptions of Trustworthiness.

Recent findings show that typical faces are judged as more trustworthy than atypical faces. However, it is not clear whether employment of typicality cues in trustworthiness judgment happens across cultures and if these cues are culture specific. In two studies, conducted in Japan and Israel, participants judged trustworthiness and attractiveness of faces. In Study 1, faces varied along a cross-cultural dimension ranging from a Japanese to an Israeli typical face. Own-culture typical faces were perceived as more trustworthy than other-culture typical faces, suggesting that people in both cultures employ typicality cues when judging trustworthiness, but that the cues, indicative of typicality, are culture dependent. Because perceivers may be less familiar with other-culture typicality cues, Study 2 tested the extent to which they rely on available facial information other than typicality, when judging other-culture faces. In Study 2, Japanese and Israeli faces varied from either Japanese or Israeli attractive to unattractive with the respective typical face at the midpoint. For own-culture faces, trustworthiness judgments peaked around own-culture typical face. However, when judging other-culture faces, both cultures also employed attractiveness cues, but this effect was more apparent for Japanese participants. Our findings highlight the importance of culture when considering the effect of typicality on trustworthiness judgments.

What is typical is good: the influence of face typicality on perceived trustworthiness.

The role of face typicality in face recognition is well established, but it is unclear whether face typicality is important for face evaluation. Prior studies have focused mainly on typicality's influence on attractiveness, although recent studies have cast doubt on its importance for attractiveness judgments. Here, we argue that face typicality is an important factor for social perception because it affects trustworthiness judgments, which approximate the basic evaluation of faces. This effect has been overlooked because trustworthiness and attractiveness judgments have a high level of shared variance for most face samples. We show that for a continuum of faces that vary on a typicality-attractiveness dimension, trustworthiness judgments peak around the typical face. In contrast, perceived attractiveness increases monotonically past the typical face, as faces become more like the most attractive face. These findings suggest that face typicality is an important determinant of face evaluation.