These findings suggest that face typicality is an important determinant of face evaluation. In contrast, perceived attractiveness increases monotonically past the typical face, as faces become more like the most attractive face. We show that for a continuum of faces that vary on a typicality-attractiveness dimension, trustworthiness judgments peak around the typical face. This effect has been overlooked because trustworthiness and attractiveness judgments have a high level of shared variance for most face samples. because it affects trustworthiness judgments, which approximate the basic evaluation of faces. Here, we argue that face typicality is an important factor for social perception. Prior studies have focused mainly on typicality's influence on attractiveness, although recent studies have cast doubt on its importance for attractiveness judgments. The role of face typicality in face recognition is well established, but it is unclear whether face typicality is important for face evaluation. This pattern of results is discussed in relation to mechanisms that may contribute to declines in facial perceptual processing in older adulthood. We observe that aging is linked with declines in the ability to make fine-grained judgements in the perception of facial happiness and facial identity (from older adult faces), but not for non-social (object) perception. We developed novel tasks that permitted the ability to assess facial happiness, facial identity, and non-social perception (object perception) across similar task parameters. Here we sought to examine how typical aging is associated with the perception of subtle changes in facial happiness and facial identity in older adult faces.
While useful, this can influence performance differences between groups due to perceptual biases and limitations on task. The majority of this work has tended to examine performance on tasks involving young adult faces and prototypical emotions.
Previous findings suggest that older adults show impairments in the social perception of faces, including the perception of emotion and facial identity. These and similar cross-modal congruencies suggest that social judgment involves not only amodal application of stored information (e.g., stereotypes) to new stimuli, but also integration of perceptual and bodily input. Finally, we show that such bias could have important practical consequences: An analysis of voting data reveals that Senatorial candidates earn 10% more votes when their names fit their faces very well, versus very poorly. Moreover, consistent with a bias for expectancy-consistent information, we find that participants like targets with "matching" names, both when name-face fit is measured and when it is experimentally manipulated. Here we show for the first time a "social" bouba/kiki effect, such that experimental participants associate round names ("Bob," "Lou") with round-faced (vs. angular objects) with names that require rounding of the mouth to pronounce, and may reflect synesthesia-like mapping across perceptual modalities. The "bouba/kiki effect" is the robust tendency to associate rounded objects (vs. The findings suggest that face evaluation involves an overgeneralization of adaptive mechanisms for inferring harmful intentions and the ability to cause harm and can account for rapid, yet not necessarily accurate, judgments from faces. Fourth, we show that important social judgments, such as threat, can be reproduced as a function of the two orthogonal dimensions of valence and dominance. Third, using these models, we show that, whereas valence evaluation is more sensitive to features resembling expressions signaling whether the person should be avoided or approached, dominance evaluation is more sensitive to features signaling physical strength/weakness. Second, using a data-driven statistical model for face representation, we build and validate models for representing face trustworthiness and face dominance. First, using a principal components analysis of trait judgments of emotionally neutral faces, we identify two orthogonal dimensions, valence and dominance, that are sufficient to describe face evaluation and show that these dimensions can be approximated by judgments of trustworthiness and dominance. Based on behavioral studies and computer modeling, we develop a 2D model of face evaluation. People automatically evaluate faces on multiple trait dimensions, and these evaluations predict important social outcomes, ranging from electoral success to sentencing decisions.
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