Four dimensions characterize comprehensive trait judgments of faces

People readily attribute many traits to faces: some look beautiful, some competent, some aggressive. These snap judgments have important consequences in real life, ranging from success in political elections to decisions in courtroom sentencing. Modern psychological theories argue that the hundreds of different words people use to describe others from their faces are well captured by only two or three dimensions, such as valence and dominance, a highly influential framework that has been the basis for numerous studies in social and developmental psychology, social neuroscience, and in engineering applications. However, all prior work has used only a small number of words (12 to 18) to derive underlying dimensions, limiting conclusions to date. Here we employed deep neural networks to select a comprehensive set of 100 words that are representative of the trait words people use to describe faces, and to select a set of 100 faces. In two large-scale, preregistered studies we asked participants to rate the 100 faces on the 100 words (obtaining 2,850,000 ratings from 1,710 participants), and discovered a novel set of four psychological dimensions that best explain trait judgments of faces: warmth, competence, femininity, and youth. We reproduced these four dimensions across different regions around the world, in both aggregated and individual-level data. These results provide a new and most comprehensive characterization of face judgments, and reconcile prior work on face perception with work in social cognition and personality psychology

Personality traits are directly associated with anti-black prejudice in the United States

Modern psychological theories postulate that individual differences in prejudice are determined by social and ideological attitudes instead of personality. For example, the dual-process motivational (DPM) model argues that personality does not directly associate with prejudice when controlling for the attitudinal variables that capture the authoritarian-conservatism motivation and the dominance motivation. Previous studies testing the DPM model largely relied on convenience samples and/or European samples, and have produced inconsistent results. Here we examined the extent to which anti-black prejudice was associated with the Big Five personality traits and social and ideological attitudes (authoritarianism, social dominance orientation, political party affiliation) in two large probability samples of the general population (N₁ = 3,132; N₂ = 2,483) from the American National Election Studies (ANES). We performed structural equation modeling (SEM) to test the causal assumptions between the latent variables and used survey weights to generate estimates that were representative of the population. Different from prior theories, across both datasets we found that two personality traits, agreeableness and conscientiousness, were directly associated with anti-black prejudice when controlling for authoritarianism, social dominance orientation, and political party affiliation. We also found that a substantial part of the associations between personality traits and anti-black prejudice were mediated through those social and ideological attitudes, which might serve as candidates for prejudice-reduction interventions in the real world

Inferring Whether Officials Are Corruptible From Looking At Their Faces

While inferences of traits from unfamiliar faces prominently reveal stereotypes, some facial inferences also correlate with real-world outcomes. We investigated whether facial inferences are associated with an important real-world outcome closely linked to the face bearer’s behavior: political corruption. In four preregistered studies (N = 325), participants made trait judgments of unfamiliar government officials on the basis of their photos. Relative to peers with clean records, federal and state officials convicted of political corruption (Study 1) and local officials who violated campaign finance laws (Study 2) were perceived as more corruptible, dishonest, selfish, and aggressive but similarly competent, ambitious, and masculine (Study 3). Mediation analyses and experiments in which the photos were digitally manipulated showed that participants’ judgments of how corruptible an official looked were causally influenced by the face width of the stimuli (Study 4). The findings shed new light on the complex causal mechanisms linking facial appearances with social behavior

Understanding How People Make Trait Attributions from Faces

This thesis is motivated by the fascinating question of how people make inferences about others from their faces. How do we infer somebody’s intent or personality merely from looking at them? I studied this question by investigating how people make trait attributions in two specific contexts -- political election (Chapter 2) and political corruption (Chapter 3) -- as well as how people make a large variety of trait attributions from faces in general (Chapter 4). I employed novel methods to representatively sample the words used to rate faces, and to select the facial stimuli themselves (e.g., using artificial neural networks), to test the reproducibility and generalizability of my results (e.g., pre-registration, generalization across participants from different cultures), and to elucidate the underlying mechanisms (e.g., mediation modeling, digital manipulation of facial stimuli). The results demonstrated that trait attributions from politician’s faces were associated with real election outcomes in different cultures, and that culture shaped trait attributions relevant to a given context (Chapter 2); trait attributions from politician’s faces were also associated with real corruption/violation records of the politicians, and perceived corruptibility was associated with the width of the face (Chapter 3). Trait attributions from faces in general (Chapter 4) were well-described by four novel dimensions that I discovered: critical/condescending, leadership/competence, female-stereotype, and youth-stereotype. Taken together, the findings provide a new psychological framework for trait attributions, demonstrate cross- cultural generalizability, and link trait attributions to real-world behaviors.</p

Efficient prediction of trait judgments from faces using deep neural networks

Judgments of people from their faces are often invalid but influence many social decisions (e.g., legal sentencing), making them an important target for automated prediction. Direct training of deep convolutional neural networks (DCNNs) is difficult because of sparse human ratings, but features obtained from DCNNs pre-trained on other classifications (e.g., object recognition) can predict trait judgments within a given face database. However, it remains unknown if this latter approach generalizes across faces, raters, or traits. Here we directly compare three distinct types of face features, and test them across multiple out-of-sample datasets and traits. DCNNs pre-trained on face identification provided features that generalized the best, and models trained to predict a given trait also predicted several other traits. We demonstrate the flexibility, generalizability, and efficiency of using DCNN features to predict human trait judgments from faces, providing an easily scalable framework for automated prediction of human judgment

Cultural effects on the association between election outcomes and face-based trait inferences

How competent a politician looks, as assessed in the laboratory, is correlated with whether the politician wins in real elections. This finding has led many to investigate whether the association between candidate appearances and election outcomes transcends cultures. However, these studies have largely focused on European countries and Caucasian candidates. To the best of our knowledge, there are only four cross-cultural studies that have directly investigated how face-based trait inferences correlate with election outcomes across Caucasian and Asian cultures. These prior studies have provided some initial evidence regarding cultural differences, but methodological problems and inconsistent findings have complicated our understanding of how culture mediates the effects of candidate appearances on election outcomes. Additionally, these four past studies have focused on positive traits, with a relative neglect of negative traits, resulting in an incomplete picture of how culture may impact a broader range of trait inferences. To study Caucasian-Asian cultural effects with a more balanced experimental design, and to explore a more complete profile of traits, here we compared how Caucasian and Korean participants’ inferences of positive and negative traits correlated with U.S. and Korean election outcomes. Contrary to previous reports, we found that inferences of competence (made by participants from both cultures) correlated with both U.S. and Korean election outcomes. Inferences of open-mindedness and threat, two traits neglected in previous cross-cultural studies, were correlated with Korean but not U.S. election outcomes. This differential effect was found in trait judgments made by both Caucasian and Korean participants. Interestingly, the faster the participants made face-based trait inferences, the more strongly those inferences were correlated with real election outcomes. These findings provide new insights into cultural effects and the difficult question of causality underlying the association between facial inferences and election outcomes. We also discuss the implications for political science and cognitive psychology

A human single-neuron dataset for face perception

The human amygdala and hippocampus have long been associated with face perception. Here, we present a dataset of single-neuron activity in the human amygdala and hippocampus during face perception. We recorded 2082 neurons from the human amygdala and hippocampus when neurosurgical patients with intractable epilepsy performed a one-back task using natural face stimuli, which mimics natural face perception. Specifically, our data include (1) single-neuron activity from the amygdala (996 neurons) and hippocampus (1086 neurons), (2) eye movements (gaze position and pupil), (3) psychological assessment of the patients, and (4) social trait judgment ratings from a subset of patients and a large sample of participants from the general population. Together, our comprehensive dataset with a large population of neurons can facilitate multifaceted investigation of face perception with the highest spatial and temporal resolution currently available in humans

Blockade of EMAP II protects cardiac function after chronic myocardial infarction by inducing angiogenesis

Promoting angiogenesis is a key therapeutic target for protection from chronic ischemic cardiac injury. Endothelial-Monocyte-Activating-Polypeptide-II (EMAP II) protein, a tumor-derived cytokine having anti-angiogenic properties in cancer, is markedly elevated following myocardial ischemia. We examined whether neutralization of EMAP II induces angiogenesis and has beneficial effects on myocardial function and structure after chronic myocardial infarction (MI). EMAP II antibody (EMAP II AB), vehicle, or non-specific IgG (IgG) was injected ip at 30 min and 3, 6, and 9 days after permanent coronary artery occlusion in mice. EMAP II AB, compared with vehicle or non-specific antibody, significantly, p<0.05, improved the survival rate after MI, reduced scar size and attenuated the development of heart failure, i.e., left ventricular ejection fraction was significantly higher in EMAP II AB group, fibrosis was reduced by 24%, and importantly, more myocytes were alive in EMAP II AB group in the infarct area. In support of an angiogenic mechanism, capillary density (193/HPF vs. 172/HPF), doubling of the number of proliferating endothelial cells, and angiogenesis related biomarkers were upregulated in mice receiving EMAP II AB treatment as compared to IgG. Furthermore, EMAP II AB prevented EMAP II protein inhibition of in vitro tube formation in HUVECs. We conclude that blockade of EMAP II induces angiogenesis and improves cardiac function following chronic MI, resulting in reduced myocardial fibrosis and scar formation and increased capillary density and preserved viable myocytes in the infarct area

Inferring Whether Officials Are Corruptible From Looking At Their Faces

While inferences of traits from unfamiliar faces prominently reveal stereotypes, some facial inferences also correlate with real-world outcomes. We investigated whether facial inferences are associated with an important real-world outcome closely linked to the face bearer’s behavior: political corruption. In four preregistered studies (N = 325), participants made trait judgments of unfamiliar government officials on the basis of their photos. Relative to peers with clean records, federal and state officials convicted of political corruption (Study 1) and local officials who violated campaign finance laws (Study 2) were perceived as more corruptible, dishonest, selfish, and aggressive but similarly competent, ambitious, and masculine (Study 3). Mediation analyses and experiments in which the photos were digitally manipulated showed that participants’ judgments of how corruptible an official looked were causally influenced by the face width of the stimuli (Study 4). The findings shed new light on the complex causal mechanisms linking facial appearances with social behavior