Understanding trait impressions from faces

Trait judgments of medieval Japanese illustrated portraits

Psychological studies have revealed that people can easily draw inferences regarding others' personal traits from their faces, which has a considerable impact on social decisions. Impressions from faces can be summarized into two orthogonal dimensions: valence and dominance. Owing to their prominence in social relationships, faces appear in paintings across all ages and cultures. These observations lead to the question of whether the structure of trait impressions from illustrated portraits is similar to that of real faces. To examine this issue, we collected trait ratings of illustrated portraits of historical individuals from old Japanese artwork. In the Study 1 section, we applied a principal component analysis to 13 traits by Japanese raters and observed two orthogonal dimensions consistent with the valence and dominance model; the first component was correlated with trustworthiness but not with dominance, while the second component was correlated with dominance but not with trustworthiness. In the Study 2 section, we collected the trait ratings of real faces by Japanese raters and directly assessed the similarity between the two components. Highly similar structures were observed for the illustrated and real faces. Our findings provide evidence that portraits of historical individuals were painted to convey distinctive impressions of trustworthiness and dominance. This suggests that these traits were fundamental dimensions of people's perception in medieval Japan similar to today's society.

Faces displaying dominance and trustworthiness do not automatically capture attention

Contesting the viewpoint that personality impressions are spontaneously extracted from triggering facial cues, recent research suggests that such inferences emerge only when instructions are given to judge individuals in terms of the trait characteristics of interest. Notwithstanding this demonstration, however, it is possible that faces displaying fundamental character traits may exert influence over lower-level aspects of cognition that precede-and serve as the foundation for-impression formation. For example, paralleling work on emotional expressions, faces conveying important traits may automatically attract attentional resources. Accordingly, employing a dot-probe task, the current research explored whether faces varying in dominance (Experiments 1 & 2) and trustworthiness (Experiment 3) trigger attentional capture. The results were consistent across all three experiments. Using both naturalistic and computer-generated faces of women and men, neither dominance nor trustworthiness captured attention. The theoretical implications of these findings are considered.

Stereotypical bias amplification and reversal in an experimental model of human interaction with generative artificial intelligence

Stereotypical biases are readily acquired and expressed by generative artificial intelligence (AI), causing growing societal concern about these systems amplifying existing human bias. This concern rests on reasonable psychological assumptions, but stereotypical bias amplification during human-AI interaction relative to pre-existing baseline levels has not been demonstrated. Here, we use previous psychological work on gendered character traits to capture and control gender stereotypes expressed in character descriptions generated by Open AI's GPT3.5. In four experiments (N = 782) with a first impressions task, we find that unexplained ('black-box') character recommendations using stereotypical traits already convey a potent persuasive influence significantly amplifying baseline stereotyping within first impressions. Recommendations that are counter-stereotypical eliminate and effectively reverse human baseline bias, but these stereotype-challenging influences propagate less well than reinforcing influences from stereotypical recommendations. Critically, the bias amplification and reversal phenomena occur when GPT3.5 elaborates on the core stereotypical content, although GPT3.5's explanations propagate counter-stereotypical influence more effectively and persuasively than black-box recommendations. Our findings strongly imply that without robust safeguards, generative AI will amplify existing bias. But with safeguards, existing bias can be eliminated and even reversed. Our novel approach safely allows such effects to be studied in various contexts where gender and other bias-inducing social stereotypes operate.

How do people perceive listeners?

Listening is essential in shaping social interactions, relationships and communication. While listening research has generated significant insights on how speakers benefit from good listening, one fundamental question has been largely overlooked: how do people perceive listeners? This gap is crucial for understanding how perceptions of listeners impact relational dynamics. In three studies (two preregistered; total N = 1509), we assessed the attributes and behaviours associated with good and bad listeners, and whether the favourability of these attributes and behaviours impact downstream consequences. In Study 1, participants identified an acquaintance they judged as a good or bad listener. Good listeners were rated higher in positive listening attributes and behaviours, which mediated their perceived warmth, competence and values. Study 2 replicated this using a reverse correlation technique: one sample generated faces of a good or bad listener, which were then evaluated by a second, naïve sample. Consistent with Study 1, good listener faces were rated higher in positive listening attributes and behaviours, mediating perceptions of warmth, competence, humility and values. Study 3 extended Study 2 by showing that the effects were not due to a general positivity bias, demonstrating the significant interpersonal consequences of being perceived as a good or bad listener.

Gaze cues (repeatedly) fail to influence person evaluation

Eye gaze is an important social signal that people generally cannot help but follow, leading to joint attention. Joint attention has been shown to speed basic processing of objects, enhance memory for them, and even affect immediate value-based appraisal by increasing object likability. Here, across 8 experiments, we investigate for the first time whether jointly attending to other faces positively affects their longer-term social value (liking, trust) and attentional value (attention allocation and prioritisation). Emanating the basic gaze cuing paradigm, a central cue face looked towards or away from a 'target' face, which the participant had to respond to. Unbeknownst to participants, some target faces were always looked at (jointly attended - high value) and others were never looked at ('ignored' - low value). In studies 1 to 6, we investigated how these gaze-induced value conditions positively affected subsequent liking and trust social judgements of a person. Then, in studies 7 and 8, we additionally investigated whether effects of gaze on others may occur implicitly, affecting subsequent attentional engagement with others by using the target faces as gaze cues, or attentional targets in a dot probe task. Confirmed through mini meta-analysis, we found no significant effect of being jointly attended versus ignored on either the social (N = 214) or attentional (N = 77) value of faces. We discuss whether faces are different from objects in this context.

Judgment of Social Traits and Emotions of "Neutral" Avatars

With the rapid advance of technology, human interactions with virtual avatars in simulated social environments are becoming increasingly common. The aim of the current study was to examine users' perception of social traits and emotions of "neutral," expressionless avatars using an open-source collection. These avatars represented different ethnicities, genders, and occupations via visual features including skin tone, facial structure, and apparel. We hypothesized that the social evaluation of "neutral" avatars would be influenced by these visual features. In two online studies, we asked survey participants (N = 225) to identify and rate the social traits and determine the expressed emotion of avatars. Female avatars were rated more attractive, trustworthy, friendly, and less aggressive than male avatars. Black avatars were rated more attractive, friendly, and trustworthy in comparison to White avatars. Avatars in martial uniforms were rated as more aggressive and less friendly than avatars in non-martial uniforms. In turn, non-martial uniformed avatars were rated higher in trustworthiness and intelligence than avatars in martial uniforms and avatars without uniforms. These results suggest that users attribute social traits and emotions to "neutral" avatars. These findings have implications for the design of tasks and products that rely on the selection of avatars in virtual reality.

Close encounters: Interpersonal proximity amplifies social appraisals

Social appraisals reflect the rapid integration of available perceptual information with broader contextual factors (e.g., intentions). While interpersonal distance affects both information availability and social context, how it changes trait impressions remains unknown. Over four experiments, we used a novel paradigm to address this question. In Experiment 1, we assessed participants' attributions of attractiveness, competence, dominance and trustworthiness of life size full body images of people when they appeared at near (1 m) and far (4 m) distances. Proximity amplified the relative magnitude of both positive and negative socio-evaluative impressions. However, this effect of proximity leading to more extreme positive or negative ratings was selectively weaker for aesthetic (attractiveness) judgements. In Experiment 2 (size) and Experiment 3 (spatial frequency), we held distance constant while manipulating visual cues relating to implied distance, revealing broadly similar results to Experiment 1. In Experiment 4, we used the interpersonal comfort distance paradigm to confirm that our life-sized projected images elicited similar comfort distance to interacting with a real person, helping to validate our general approach. These findings demonstrate the crucial role of interpersonal distance in impression judgements.

An investigation on the face inversion effect in deaf children

The face inversion effect is an important indicator of holistic face perception and reflects the developmental level of face processing. This study examined the face inversion effect in deaf or hard of hearing (DHH) children aged 7-17 using the face dimensions task. This task uses photographic images of a face, in which configural and featural information in the eye and mouth regions have been parametrically and independently manipulated. The study aimed to discuss the effect of face inversion on facial processing in DHH children, including two aspects of information processing types (configural versus featural) and processing regions (eyes versus mouth) and compared the results with hearing children. The results revealed that DHH children aged 7-17 years exhibit significant face inversion effect, with disruptions observed in both the featural and configural processing of eyes and mouths when faces were inverted. Configural processing was more affected by inversion than featural processing in all children, with larger differences observed in DHH children than in hearing children. This supports the dual-mode hypothesis of holistic face processing. Age correlations were observed in the sensitivity of DHH children to face inversion effect but not among hearing children. The inversion effect of configural mouth processing decreases with age in DHH children.

Semantic Content in Face Representation: Essential for Proficient Recognition of Unfamiliar Faces by Good Recognizers

Face recognition is adapted to achieve goals of social interactions, which rely on further processing of the semantic information of faces, beyond visual computations. Here, we explored the semantic content of face representation apart from visual component, and tested their relations to face recognition performance. Specifically, we propose that enhanced visual or semantic coding could underlie the advantage of familiar over unfamiliar faces recognition, as well as the superior recognition of skilled face recognizers. We asked participants to freely describe familiar/unfamiliar faces using words or phrases, and converted these descriptions into semantic vectors. Face semantics were transformed into quantifiable face vectors by aggregating these word/phrase vectors. We also extracted visual features from a deep convolutional neural network and obtained the visual representation of familiar/unfamiliar faces. Semantic and visual representations were used to predict perceptual representation generated from a behavior rating task separately in different groups (bad/good face recognizers in familiar-face/unfamiliar-face conditions). Comparisons revealed that although long-term memory facilitated visual feature extraction for familiar faces compared to unfamiliar faces, good recognizers compensated for this disparity by incorporating more semantic information for unfamiliar faces, a strategy not observed in bad recognizers. This study highlights the significance of semantics in recognizing unfamiliar faces.

What will we judge a book by its cover?-Content analysis of face perception in a Chinese sample

People can perceive various information from faces. Most of previous studies of face perception only focused on one of attributes, such as gender, expression, personality etc., the whole picture of face perception is far from clear. Therefore, the present study recruited Chinese participants to provide spontaneous descriptions of unfamiliar Chinese faces without any constraints of content. It turned out that descriptions employed a broad spectrum of descriptors, as well as a consistent pattern across different identities: descriptions that incorporated psychological characteristics were most prevalent, whereas mentions of physiological attributes generally occurred earlier in the description than other types of descriptive vocabulary. These results underscore the special role of free description analysis in revealing the panorama of face perception, where perceivers swiftly infer a plenty of character traits in an organized way, ultimately forming a comprehensive impression of others.

Exploring gender stereotypes in financial reporting: An aspect-level sentiment analysis using big data and deep learning

This study delves into the intricate interplay between gender stereotypes and financial reporting through an aspect-level sentiment analysis approach. Leveraging Big Data comprising 129,251 human face images extracted from 2085 financial reports in Chile, and employing Deep Learning techniques, we uncover the underlying factors influencing the representation of women in financial reports. Our findings reveal that gender stereotypes, combined with external economic factors, significantly shape the portrayal of women in financial reports, overshadowing intentional efforts by companies to influence stakeholder perceptions of financial performance. Notably, economic expansion periods correlate with a decline in women's representation, while economic instability amplifies their portrayal. Furthermore, the financial inclusion of women positively correlates with their presence in financial report images. Our results underscore a bias in image selection within financial reports, diverging from the neutrality principles advocated by the International Accounting Standards Board (IASB). This pioneering study, combining Big Data and Deep Learning, contributes to gender stereotype literature, financial report soft information research, and business impression management research.

Learned trustworthiness does not have the same influence on implicit responses measured via fast periodic visual stimulation as face trustworthiness

Past research has demonstrated that it is possible to detect implicit responses to face trustworthiness using fast periodic visual stimulation (FPVS). Because people readily retrieve affective associations with faces, the current study investigated whether learned trustworthiness would yield similar responses to face trustworthiness as measured via FPVS. After learning to associate faces with untrustworthy or trustworthy behaviors, participants completed three separate tasks while electroencephalography (EEG) was recorded. In each of these tasks, participants viewed oddball sequences of faces where a single base face was presented repeatedly at a rate of 6 Hz and oddball faces with different identities were presented every fifth face (6 Hz/5 = 1.2 Hz). Providing evidence of learning, the oddball response at 1.2 Hz and its harmonics was stronger for the learned faces compared to novel faces over bilateral occipitotemporal cortex and beyond. In addition, reproducing previous findings with face trustworthiness, we observed a stronger response at 1.2 Hz and its harmonics for sequences with less trustworthy-looking versus trustworthy-looking oddball faces over bilateral occipitotemporal cortex and other sites. However, contrary to our predictions, we did not observe a significant influence of learned trustworthiness on the oddball response. These data indicate that impressions based on learning are treated differently than impressions based on appearance, and they raise questions about the types of design and stimuli that yield responses that are measurable via FPVS.

Implicit bias and experience influence overall but not relative trustworthiness judgment of other-race faces

Impressions of trustworthiness are formed quickly from faces. To what extent are these impressions shared among observers of the same or different races? Although high consensus of trustworthiness evaluation has been consistently reported, recent studies suggested substantial individual differences. For instance, negative implicit racial bias and low contact experience towards individuals of the other race have been shown to be related to low trustworthiness judgments for other-race faces. This pre-registered study further examined the effects of implicit social bias and experience on trustworthiness judgments of other-race faces. A relatively large sample of White (N = 338) and Black (N = 299) participants completed three tasks: a trustworthiness rating task of faces, a race implicit association test, and a questionnaire of experience. Each participant rated trustworthiness of 100 White faces and 100 Black faces. We found that the overall trustworthiness ratings for other-race faces were influenced by both implicit bias and experience with individuals of the other-race. Nonetheless, when comparing to the own-race baseline ratings, high correlations were observed for the relative differences in trustworthiness ratings of other-race faces for participants with varied levels of implicit bias and experience. These results suggest differential impact of social concepts (e.g., implicit bias, experience) vs. instinct (e.g., decision of approach-vs-avoid) on trustworthiness impressions, as revealed by overall vs. relative ratings on other-race faces.

The social factors behind the mask: contextual effects on trait impressions from faces wearing a face mask

The presence of face masks can significantly impact processes related to trait impressions from faces. In the present research, we focused on trait impressions from faces either wearing a mask or not by addressing how contextual factors may shape such inferences. In Study 1, we compared trait impressions from faces in a phase of the COVID-19 pandemic in which wearing masks was a normative behavior (T1) with those assessed one year later when wearing masks was far less common (T2). Results at T2 showed a reduced positivity in the trait impressions elicited by faces covered by a mask. In Study 2, it was found that trait impressions from faces were modulated by the background visual context in which the target face was embedded so that faces wearing a mask elicited more positive traits when superimposed on an indoor rather than outdoor visual context. Overall, the present studies indicate that wearing face masks may affect trait impressions from faces, but also that such impressions are highly flexible and can significantly fluctuate across time and space.

Decoding the language of first impressions: Comparing models of first impressions of faces derived from free-text descriptions and trait ratings

First impressions formed from facial appearance predict important social outcomes. Existing models of these impressions indicate they are underpinned by dimensions of Valence and Dominance, and are typically derived by applying data reduction methods to explicit ratings of faces for a range of traits. However, this approach is potentially problematic because the trait ratings may not fully capture the dimensions on which people spontaneously assess faces. Here, we used natural language processing to extract 'topics' directly from participants' free-text descriptions (i.e., their first impressions) of 2222 face images. Two topics emerged, reflecting first impressions related to positive emotional valence and warmth (Topic 1) and negative emotional valence and potential threat (Topic 2). Next, we investigated how these topics were related to Valence and Dominance components derived from explicit trait ratings. Collectively, these components explained only ~44% of the variance in the topics extracted from free-text descriptions and suggested that first impressions are underpinned by correlated valence dimensions that subsume the content of existing trait-rating-based models. Natural language offers a promising new avenue for understanding social cognition, and future work can examine the predictive utility of natural language and traditional data-driven models for impressions in varying social contexts.

Business culture impairs facial trustworthiness judgments

Previous research has found that business culture has a detrimental impact on interpersonal trust. To understand whether this impact extends to rapid, automatic, bottom-up judgments of facial trustworthiness, we conducted 4 experiments involving 244 participants from economic and non-economic backgrounds. We presented participants with both trustworthy and untrustworthy faces and asked them to make judgments on trustworthiness. The results show that individuals who are engaged in studying economics, work in an economics-related occupation, or are exposed to an imagined business culture evaluate trustworthy faces to be less trustworthy. The findings shed light on why and how business culture affects the formation of interpersonal trust.

Racial Prejudice Affects Representations of Facial Trustworthiness

What makes faces seem trustworthy? We investigated how racial prejudice predicts the extent to which perceivers employ racially prototypical cues to infer trustworthiness from faces. We constructed participant-level computational models of trustworthiness and White-to-Black prototypicality from U.S. college students' judgments of White (Study 1, N = 206) and Black-White morphed (Study 3, N = 386) synthetic faces. Although the average relationships between models differed across stimuli, both studies revealed that as participants' anti-Black prejudice increased and/or intergroup contact decreased, so too did participants' tendency to conflate White prototypical features with trustworthiness and Black prototypical features with untrustworthiness. Study 2 (N = 324) and Study 4 (N = 397) corroborated that untrustworthy faces constructed from participants with pro-White preferences appeared more Black prototypical to naive U.S. adults, relative to untrustworthy faces modeled from other participants. This work highlights the important role of racial biases in shaping impressions of facial trustworthiness.

Facial first impressions are not mandatory: A priming investigation

A common assertion is that, based around prominent character traits, first impressions are spontaneously extracted from faces. Specifically, mere exposure to a person is sufficient to trigger the involuntary extraction of core personality characteristics (e.g., trustworthiness, dominance, competence), an outcome that supports a range of significant judgments (e.g., hiring, investing, electing). But is this in fact the case? Noting ambiguities in the extant literature, here we used a repetition priming procedure to probe the extent to which impressions of dominance are extracted from faces absent the instruction to evaluate the stimuli in this way. Across five experiments in which either the character trait of interest was made increasingly obvious to participants (Expts. 1-3) or attention was explicitly directed toward the faces to generate low-level/high-level judgments (Expts. 4 & 5), no evidence for the spontaneous extraction of first impressions was observed. Instead, priming only emerged when judgments of dominance were an explicit requirement of the task at hand. Thus, at least using a priming methodology, the current findings contest the notion that first impressions are a mandatory product of person perception.

Effects of masculinity vs. femininity on competence judgement of politician faces and election outcome prediction

First impressions of politician faces can be effective in predicting election outcomes, based on perceived competence from candidate photographs. However, it remains unclear whether such effects arose from facial features or other non-facial information present in the photographs (e.g. hairstyles, clothes, or poses). In four pre-registered studies, participants completed two tasks in a counter-balanced order: rating competence of individually presented faces and predicting election outcome of each pair of winner and runner-up faces. We examined competence judgment and election outcome prediction on faces from male politicians depicted on original portraits (Experiment 1), or on computer-generated faces with facial features extracted from the portraits (Experiment 2). The faces were then either masculinized or feminized (Experiments 3 and 4). We found that competence ratings were significantly higher for winners than runners-up and that winners were more likely predicted to win the elections than runners-up in all but Experiment 4, where faces of the winners were feminized and faces of the runners-up were masculinized. Regardless of facial feature changes, correlations were found between competence ratings and election outcome prediction. These findings suggest that facial features are critical for evaluating competence and predicting election outcome, and that masculine features may enhance stereotypical leadership impressions.

Three's a crowd: Fast ensemble perception of first impressions of trustworthiness

Trustworthiness impressions are fundamental social judgements with far-reaching consequences in many aspects of society, including criminal justice, leadership selection and partner preferences. Thus far, most research has focused on facial characteristics that make a face individually appear more or less trustworthy. However, in everyday life, faces are not always perceived in isolation but are often encountered in crowds. It has been proposed that we deal with the large amount of facial information in a group by extracting summary statistics of the crowd, a phenomenon called ensemble perception. Prior research showed that ensemble perception occurs for various facial features, such as emotional expression, facial identity, and attractiveness. Here, we investigated whether observers can integrate the level of trustworthiness from multiple faces to extract an average impression of the crowd. Across four studies, participants were presented with crowds of faces and were asked to report their average level of trustworthiness with an adjustment (Experiment 1) and a rating task (Experiments 2 and 3). Participants were able to extract an ensemble perception of trustworthiness impressions from multiple faces. Moreover, observers were able to form a summary statistic of trustworthiness impressions from a group of faces as quickly as 250 ms (Experiment 4). Taken together, these results demonstrate that ensemble perception can occur at the level of impressions of trustworthiness. Thus, these critical social judgements not only occur for individual faces but are also integrated into a unique ensemble impression of crowds. Our findings contribute to the development of a more ecological approach to the study of trust impressions, since they provide an understanding of trustworthiness judgements not only on an individual level, but on a much broader social group level. Furthermore, our results drive forward new theory because they demonstrate for the first time that ensemble representations cover a broad range of phenomena than previously recognized, including complex high-level facial trait judgements such as trustworthiness impressions.

Comprehensive Social Trait Judgments From Faces in Autism Spectrum Disorder

Processing social information from faces is difficult for individuals with autism spectrum disorder (ASD). However, it remains unclear whether individuals with ASD make high-level social trait judgments from faces in the same way as neurotypical individuals. Here, we comprehensively addressed this question using naturalistic face images and representatively sampled traits. Despite similar underlying dimensional structures across traits, online adult participants with self-reported ASD showed different judgments and reduced specificity within each trait compared with neurotypical individuals. Deep neural networks revealed that these group differences were driven by specific types of faces and differential utilization of features within a face. Our results were replicated in well-characterized in-lab participants and partially generalized to more controlled face images (a preregistered study). By investigating social trait judgments in a broader population, including individuals with neurodevelopmental variations, we found important theoretical implications for the fundamental dimensions, variations, and potential behavioral consequences of social cognition.

Data-driven studies in face identity processing rely on the quality of the tests and data sets

There is growing interest in how data-driven approaches can help understand individual differences in face identity processing (FIP). However, researchers employ various FIP tests interchangeably, and it is unclear whether these tests 1) measure the same underlying ability/ies and processes (e.g., confirmation of identity match or elimination of identity match) 2) are reliable, 3) provide consistent performance for individuals across tests online and in laboratory. Together these factors would influence the outcomes of data-driven analyses. Here, we asked 211 participants to perform eight tests frequently reported in the literature. We used Principal Component Analysis and Agglomerative Clustering to determine factors underpinning performance. Importantly, we examined the reliability of these tests, relationships between them, and quantified participant consistency across tests. Our findings show that participants' performance can be split into two factors (called here confirmation and elimination of an identity match) and that participants cluster according to whether they are strong on one of the factors or equally on both. We found that the reliability of these tests is at best moderate, the correlations between them are weak, and that the consistency in participant performance across tests and is low. Developing reliable and valid measures of FIP and consistently scrutinising existing ones will be key for drawing meaningful conclusions from data-driven studies.

Aesthetic dental treatment, orofacial appearance, and life satisfaction of Finnish and Brazilian adults

AIMS

To study the probability of seeking/undergoing aesthetic dental treatment (ADT) and compare self-perception of orofacial appearance (OA) based on sex, age, and monthly income; and to estimate the impact of OA on life satisfaction (LS) among Finnish and Brazilian adults, considering the indirect effect of receiving ADT and the moderating effects of those sociodemographic variables.

METHODS

This was an online cross-sectional study. Orofacial Esthetic Scale (OES), Psychosocial Impact of Dental Aesthetics Questionnaire (PIDAQ) and Satisfaction with Life Scale (SWLS) were used. Probability of seeking/receiving ADT was calculated using logistic regression and odds ratio (OR). OA scores were compared according to sociodemographic characteristics (ANOVA, α = 5%). Structural equations models estimated the impact of OA on LS.

RESULTS

3,614 Finns [75.1% female, 32.0 (SD = 11.6) years] and 3,979 Brazilians [69.9% female, 33.0 (SD = 11.3) years] participated in the study. Women were more likely to receive ADT than men in both countries (OR>1.3). However, no statistically or practical significant differences were observed in OA between sexes (p>0.05 or p<0.05, ηp2 = 0.00-0.02). In Finland, demand for ADT (OR = 0.9-1.0) and OA scores (p>0.05) were the same among different ages and monthly income. In Brazil, younger individuals (OR>1.6) and those with higher monthly income (OR>2.7) were more likely to receive ADT, while those with lower income had a greater psychosocial impact of OA (p<0.05; ηp2>0.07). Individuals who were more satisfied with their own OA and had less psychosocial impact from OA had higher levels of LS (β = 0.31-0.34; p<0.01; explained variance: 9.8-13.1%).

CONCLUSION

Demand for ADT is influenced by sociodemographic and cultural factors. Greater societal pressure on physical appearance is observed among women in Western countries. In countries with high socioeconomic inequalities, consumerism and social prestige are involved in this demand. Self-perception of orofacial appearance plays a significant role in individuals' subjective well-being. Therefore, the planning of aesthetic treatments in the orofacial region should consider the patient's perceptions and social context.

First impressions from faces in the real world: Commentary on Sutherland and Young (2022)

The study of first impressions from faces now emphasizes the need to understand trait inferences made to naturalistic face images (British Journal of Psychology, 113, 2022, 1056). Face recognition algorithms based on deep convolutional neural networks simultaneously represent invariant, changeable and environmental variables in face images. Therefore, we suggest them as a comprehensive 'face space' model of first impressions of naturalistic faces. We also suggest that to understand trait inferences in the real world, a logical next step is to consider trait inferences made to whole people (faces and bodies). On the role of cultural contributions to trait perception, we think it is important for the field to begin to consider the way in which trait inferences motivate (or not) behaviour in independent and interdependent cultures.

Generative models for visualizing idiosyncratic impressions

In their comprehensive review of research on impressions from faces, Sutherland and Young (this issue) highlight both the remarkable progress and the many challenges facing the field. We focus on two of the challenges: the need for generative, powerful models of impressions and the idiosyncratic nature of complex impressions.

Trait impressions from faces depend on the goals of the perceiver

Trait impressions from faces formed in the real world likely depend on the circumstances in which a face is seen, in particular, on the goal of the perceiver in that circumstance. This goal dependency is typically not incorporated into laboratory studies, an omission that has limited our understanding of trait impressions from faces.

We need to move beyond rating scales, white faces and adult perceivers: Invited Commentary on Sutherland & Young (2022), understanding trait impressions from faces

Sutherland and Young's perspective is a timely and rigorous examination of trait impressions based on facial cues. We propose three strtegies to further advance the field: incorporating natural language processing, including diverse facial stimuli, and re-interpreting developmental data.

Trait impressions from voices: Considering multiple ‘origin stories’ and the dynamic nature of trait‐related cues

Experimental findings for trait impressions from voices are often discussed in relation to potential evolutionary origins. This commentary takes Sutherland and Young's (2022) account of the different potential origins of facial trait impressions to suggest that vocal trait impressions should also be viewed as having been shaped by cultural and individual learning.

Mapping physical characteristics in face images to social judgements

Sutherland and Young (Br. J. Psychol., 113, 2022, 1056) provide a comprehensive and timely overview of recent developments in research on social judgements of faces, emphasizing the utility of data-driven approaches. Here, we expand on this theme, focusing on how data-driven approaches can provide new insights into the physical characteristics in face images that best predict social judgements.