White Faces Research Articles

Hawai‘i face database: a racially and ethnically diverse set of facial stimuli

ABSTRACT Within psychology, face perception processes have been widely studied, examining traits and social categories that a face can communicate. However, much of this research has predominately focused on White faces. We review existing face databases that include racially diverse stimuli and note the lack of representation of Asian subgroups (e.g. East, South, and Southeast Asian), Pacific Islanders, as well as both Multiracial and multiethnic faces (especially with multiple minoritized backgrounds). We provide a new racially diverse set of free, standardized images including 140 unique faces representing eight different groups that vary in ethnicity and race (Asian, East Asian, Southeast Asian, Pacific Islander/Native Hawaiian, Hispanic/Latinx, White, Multiracial, and Multiracial Asian), along with norming data. These images and data are available for access use in research: https://osf.io/fkn7y

Racial biases, facial trustworthiness, and resting heart rate variability: unravelling complexities in pain recognition.

The study explores whether racial identity and appearance-based trustworthiness judgments can affect recognition of pain in medical students differing in levels of resting heart rate variability (HRV), a measure of parasympathetic control of the heart. After undergoing HRV assessment, 68 medical students (37 females) participated in a dynamic pain recognition task, viewing video clips of White and Black faces,which differed in perceived trustworthiness based on facial appearance, transitioning from neutral to intense pain expressions. Response time, pain intensity attribution and treatment recommendations were analyzed. Pain was recognized slower and estimated as less intense in Black compared to White faces, leading to a lower likelihood of recommending therapy. Pain recognition was faster for untrustworthy-looking White faces compared to trustworthy ones, while perceived trustworthiness had a minimal impact on the speed of pain recognition in Black faces. However, untrustworthy-looking faces were estimated to express more pain, particularly for Black faces. Notably,thesebiases were more pronounced in individuals with low, rather than high, resting HRV. Considering that therapeutic decisions mirrored pain intensity attribution, it would be important to increase awareness of these biases during medical training in order to promote equity in future pain assessment and treatment.

Spotting missing or wanted people: racial biases in prospective person memory

Searching for missing or wanted people is a crucial task in our society. Previous work on prospective person memory (PPM) has demonstrated that performance on this type of search task is worse relative to standard prospective memory tasks. Importantly, this process may be further affected by the race of the missing person, yet this has never been tested in laboratory settings. To test the effects of race on PPM, a convenience sample consisting primarily of self-identified Caucasian participants was asked to search for either a Caucasian or an Indian target person while judging the orientation of different Caucasian and Indian faces. Although the tasks were otherwise identical, 89% of Caucasian PPM targets were found while only 53% of Indian targets were found. Furthermore, relative to a control group with no PPM requirements, participants were slower and more error-prone when judging Indian faces relative to White faces, particularly if they were searching for an Indian face. We interpret these results as revealing other-race effects in prospective person memory, highlighting race as a critical factor for finding missing people. Importantly, this also emphasizes the need for real-world search efforts to factor in difficulty differences when people monitor for missing/wanted people from their own or different racial backgrounds. For example, media coverage of missing persons cases could perhaps be distributed more equitably by considering whether the missing person is from a racial minority in that region.

The self can be associated with novel faces of in-group and out-group members: A cross-cultural study

The self can be associated with arbitrary images, such as geometric figures or unknown faces. By adopting a cross-cultural perspective, we explored in two experiments whether the self can be associated with faces of unknown people from different ethnic groups. In Experiment 1, Asian Japanese participants completed a perceptual matching task, associating Asian or White faces with themselves. The same task was used in Experiment 2 with White Italians. Both experiments showed a reliable association between the self and facial stimuli. Importantly, this association was similar for both Asian and White faces. Additionally, no correlations were found between the strength of this association and an index of implicit bias towards Asian and White individuals. These results suggest that the self is malleable and can incorporate social stimuli from different groups.

Different features for different races: Tracking the eyes of Asian, Black, and White participants viewing Asian, Black, and White Faces.

The own-race bias (ORB) is an effect in which humans remember faces from their own race better than faces from another race. Where people look when processing faces of different races plays a role in this effect, but the exact relationship between looking and the ORB is debated. One perspective is that the same facial features are important for memory for faces of all races and the ORB emerges when people look longer at the useful features for own- than other-race faces. Another perspective is that different facial features are useful for faces of different races and the ORB emerges when people look longer at features that are useful for their own race than at features that are useful for other-race faces. The present study aimed to discriminate these perspectives by examining looking patterns in Asian, Black, and White participants while they learned and later recognized Asian, Black, and White faces. Regardless of their race, participants looked at different facial features depending on the race of the face. In addition, different features were useful for memory depending on the race of the face. As such, results are in line with the perspective that different facial features are useful for different race faces.

Instrumentalising race: why critical terrorism studies continues to have a race problem

ABSTRACT This paper interrogates how the racial logic of instrumentalisation – the intended exploitation of racialised peoples for intellectual capital – shapes the field of Critical Terrorism Studies (CTS). I argue that the problem of instrumentalisation highlights CTS’s limitations to advance anti-racism because of how it standardises non-racist (rather than anti-racist) logic and practices in academia. Adopting a postcolonial perspective inspired by Frantz Fanon and Robbie Shilliam, this paper discusses the problem of CTS furthering the structural issue that is counterterrorism policymaking spaces privileging “white faces” rather than engaging knowledge production practices that are more cognisant of the relational attributes of ontology. This distinction of “rather than” is argued to be an important emphasis in how this distinction challenges the quality of criticality within CTS if CTS cannot meet its core commitments in the context of anti-racism. The aim of pursuing this evaluation is not to replace white faces with non-white representations by way of calling for diversity in the CTS professoriate. The focus of this critique of CTS is instead to explain why CTS scholars should re-examine their philosophical commitments and knowledge relations to evaluate how they can better demonstrate intellectual generosity and allyship in service to anti-racist intellectual traditions.

Artificial intelligence ethics: ethical consideration and regulations from theory to practice

<p><span lang="EN-US">The advancement of artificial intelligence (AI) has led to its widespread use in sectors such as finance, healthcare, military, and employment in developed countries. However, this reliance has raised concerns about AI governance, particularly regarding algorithmic biases based on skin color, gender, race, and age. Consequently, many countries have introduced regulations and ethical frameworks to address these issues. The Ministry of Digital Economy and Entrepreneurship in Jordan has included AI in its 2022 plan, signaling significant progress. The integration of AI in education programs underscores this commitment. However, addressing AI's potential negative impacts is essential. We propose ethical considerations and regulations for AI to complement Jordan's initiatives. Our research aims to promote responsible AI usage by developing ethical guidelines in Jordan. It presents techniques to identify and mitigate biases related to skin color, gender, and age in AI outputs and datasets. The research includes extensive testing on datasets, analyzing approximately 100 images, and revealing notable error rates, including a 16% error rate in detecting skin color, a 4% error rate in seeing white faces, and a 6% error rate in identifying females over men. Therefore, ethical considerations and regulations for AI applications in Jordan must be implemented.</span></p>

Examining implicit and explicit anti-Black racial bias in children: A repeated measure design using the Function Acquisition Speed Test (FAST)

ABSTRACT Anti-Black bias involves negative evaluations of individuals from African-descendent groups. Researchers use explicit and implicit measures to detect this bias and evaluate intervention effectiveness. However, few behavior analysis studies have focused on identifying and addressing racial bias in children, and none have explored the effects of test-retest on implicit measures in this context. This study aimed to identify implicit and explicit anti-Black racial bias in children and examine the test-retest reliability of these measures over three time points. Thirty-four children (average age 8.60 years, 24 females) rated images of Black and White faces on a five-point Likert scale. The Modified Function Acquisition Speed Test (FAST), an implicit measure, assessed how fluently participants categorized Black and White faces with positive and negative images. Results showed no explicit racial bias in the sample. However, implicit measure results revealed an anti-Black bias, with 11 participants consistently displaying this bias across three repetitions. Regarding test-retest reliability, there were no significant performance differences on the implicit and explicit measures across the three repetitions. These findings suggest that the FAST is a sensitive tool for identifying racial bias in children, and the absence of test-retest effects supports its feasibility for repeated use.

Racial salience modulated the face race lightness illusion: A comparative study of Caucasians and Asians.

Previous research has demonstrated the existence of the face race lightness (FRL) illusion. It indicates that Black faces tend to appear darker than White faces, even when their luminance values are objectively adjusted to be the same. However, the debate over the exclusive influence of face-race categories on the FRL illusion continues, with the impact of racial groups on the illusion remaining relatively unexplored. To address these gaps, we conducted studies to investigate whether the FRL illusion varies in terms of racial salience and racial groups. We manipulated the racial salience by altering the orientation of the faces. A total of 64 Caucasians (Study 1) and 63 Asians (Study 2) were recruited. Participants were shown pairs of faces in rapid succession and were asked to report which face appeared lighter or darker. In each trial, the two faces belonged to the same race category: Black, Black-White ambiguous, or White. The luminance of the first face remained consistent across trials while the luminance of the second face varied and was adjusted across eight levels (- 20, - 12, - 8, - 4, + 4, + 8, + 12, + 20). Our findings reveal that the FRL illusion is largely dependent on the salience of face-race information. When faces were presented upright, the FRL illusion was prominent; however, it disappeared when faces were inverted. Remarkably, the FRL illusion was observed not only in Caucasians but also in Asians. Therefore, our results suggest that the FRL illusion primarily stems from race salience rather than participants' racial groups.

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.

Interactive effects of participant and stimulus race on cognitive performance in youth: Insights from the ABCD study

An extensive literature shows that race information can impact cognitive performance. Two key findings include an attentional bias to Black racial cues in U.S. samples and diminished recognition of other-race faces compared to same-race faces in predominantly White adult samples. Yet face stimuli are increasingly used in psychological research often unrelated to race (Conley et al., 2018) or without consideration for how race information may influence cognitive performance, especially among developmental participants from different racial groups. In the current study we used open-access data from the Adolescent Brain Cognitive DevelopmentSM (ABCD) Study® 4.0.1 release to test for developmentally similar other- and same-race effects of Black and White face stimuli on attention, working memory, and recognition memory in 9- and 10-year-old Black and White children (n=5,659) living in the U.S. Black and White children showed better performance when attending to Black versus White faces. We also show an advantage in recognition memory of same-race compared to other-race faces in White children that did not generalize to Black children. Together the findings highlight how race information, even when irrelevant to an experiment, may indirectly lead to misinterpretation of group differences in cognitive performance in children of different racial backgrounds.

Impact of Duchenne and non-Duchenne smiles on perceived trustworthiness of Black and White faces: A Black perspective.

In five experiments, we investigated how Black participants perceive Duchenne and non-Duchenne smiles on Black and White targets. Results consistently demonstrated that when assessing happiness, faces with Duchenne compared to non-Duchenne smiles were rated as happier on both Black and White targets. However, when assessing a more socially evaluative dimension, trustworthiness, perceptions of Black and White targets diverged. Whereas White targets with Duchenne compared to non-Duchenne smiles were rated as more trustworthy, ratings of Black targets with Duchenne and non-Duchenne smiles did not differ, with both appraised as highly trustworthy. Although the degree to which Black participants identified with their race did not moderate these effects, the perceived genuineness of targets did mediate the relationship. One reason why Duchenne compared to non-Duchenne smiles on White but not Black targets were perceived as more trustworthy is because Duchenne compared to non-Duchenne smiles on White but not Black targets were perceived as more genuine. A final study extended these findings by exploring the impact of target race and smile type on partner choice. In accordance with the results related to trustworthiness ratings, Black participants selected White partners with Duchenne compared to non-Duchenne smiles more often but did not differentiate in their choice of Black partners with Duchenne versus non-Duchenne smiles. These findings underscore the importance of investigating not only diverse targets but also diverse perceivers. Our results suggest that Black perceivers use facial cues differently when rating the trustworthiness of Black and White targets and that these perceptions have important downstream consequences. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Abstract 36: Clinical Guidelines May Help Mitigate the Impact of Physician Implicit Bias on Patient Care and Treatment

Introduction: We previously found that physician pro-White implicit bias was associated with the performance of low-value revascularization procedures for Black patients with claudication. These treatments are commonly considered risk greater than benefit but are not expressly discouraged by guidelines. We sought to investigate whether implicit bias is less likely to impact care in settings with well-defined Class Ia-supported guidelines. Hypothesis: We hypothesized that a physician’s implicit bias would not be associated with the performance of clinical practices as outlined in the 2016 AHA/ACC Guidelines on the Management of Patients with Lower Extremity Peripheral Artery Disease. Methods: We measured implicit bias via the race Implicit Association Test (IAT) using a sample of physicians from the Society for Vascular Surgery’s Vascular Quality Initiative (VQI). The IAT asks participants to classify sequential images of Black and White faces to positive and negative attributes. Based on reaction times and responses on the IAT, physicians were categorized as having no bias, pro-Black bias, or pro-White bias. IAT results were then weighted to reflect the overall VQI demographics and linked to peripheral revascularization data. We used mixed effects logistic regression models to assess the association of physician implicit bias category with pre-operative prescriptions of antiplatelets (ASA, P2Y12) and statins, as well as current smoking status (reported as aORs). All models included a random intercept for the physician and were adjusted for year, physician race/ethnicity, and patient factors of race/ethnicity, diabetes, and hypertension. We examined effect modification by patient race/ethnicity through the inclusion of an interaction term with physician implicit bias category. Finally, we calculated a summary index across the four primary clinical practices and assessed the association with physician implicit bias category via a mixed effects Poisson model (reported as IRRs). Results: A total of 218 physicians successfully completed the IAT and were linked to 6,588 peripheral revascularizations they completed for claudication. We found no significant associations between the physician’s implicit bias category and the performance of any of the assessed guideline metrics for their Black or White patients (Summary Index - IRR: 1.02, 95% CI: 0.98-1.06). Additionally, we found no evidence of effect modification by patient race/ethnicity (ASA - aOR: 0.91, 95% CI: 0.61-1.34; P2Y12 - aOR: 1.22, 95% CI: 0.88-1.69; Statin - aOR: 1.12, 95% CI: 0.76-1.67). Conclusions: The performance of guideline-driven practices were not associated with a physician’s measured racial implicit bias. We provide preliminary evidence that appropriately designed guidelines could be successful in combatting Black-White health inequities stemming from the implicit bias of physicians.

Do They Look the Same Unless They Are Angry? Investigating the Other-Race Effect in the Presence of Angry Expressions

Ethnic out-group members are disproportionately more often the victim of misidentifications. The so-called other-race effect (ORE), the tendency to better remember faces of individuals belonging to one’s own ethnic in-group than faces belonging to an ethnic out-group, has been identified as one causal ingredient in such tragic incidents. Investigating an important aspect for the ORE—that is, emotional expression—the seminal study by Ackerman and colleagues (2006) found that White participants remembered neutral White faces better than neutral Black faces, but crucially, Black angry faces were better remembered than White angry faces (i.e., a reversed ORE). In the current study, we sought to replicate this study and directly tackle the potential causes for different results with later work. Three hundred ninety-six adult White U.S. citizens completed our study in which we manipulated the kind of employed stimuli (as in the original study vs. more standardized ones) whether participants knew of the recognition task already at the encoding phase. Additionally, participants were asked about the unusualness of the presented faces. We were able to replicate results from the Ackerman et al. (2006) study with the original stimuli but not with more standardized stimuli.

Artificial Intelligence Versus Human Focus Group Rating of Facial Attractiveness.

Background: Many open-access artificial intelligence (AI)-based websites that rate facial attractiveness are available, but none have been compared with human focus group outcomes. Objective: To compare human and AI-based websites scoring of facial attractiveness of adult female white faces. Methods: A 40-photograph database of AI-generated adult, white, female, expressionless, and frontal-view facial images were scored by otolaryngology residents and five AI-based facial rating websites: prettyscale.com, attractivenesstest.com, face-score.com/en, hotchat3000.com, and beautyscoretest.com. Sample t-test and bivariate correlation were performed for statistical analyses. Results: The focus group of 24 otolaryngology residents consisted of 62.5% males and 58.3% white participants. There was a strong positive correlation between average human score and average AI score for each photo (Pearson's correlation 0.84, p < 0.01). The average human raters' scores were significantly lower than the average AI scores (5.0 ± 1.8 vs. 6.9 ± 0.9, p < 0.01). Thirty images (75.0%) had statistically higher scores from the AI websites versus the focus group. On correlation analysis, all AI-based websites individually had scores that positively correlate with the human scores (all p < 0.05). Conclusion: AI-based websites and human focus-group scoring of facial attractiveness of adult white female faces were significantly correlated with the AI ratings biased toward higher values, encouraging their cautious utilization in future research.

Stereotypes bias social class perception from faces: The roles of race, gender, affect, and attractiveness.

People quickly form consequential impressions of others' social class standing from nonverbal cues, including facial appearance. Extant research shows that perceivers judge faces that appear more positive, attractive, and healthy as higher-class, in line with stereotypes associating high class standing with happiness, attractiveness, and better wellbeing (which bear a kernel of truth). A wealth of research, moreover, demonstrates strong stereotypical associations between social class and both race and gender. The current work bridged these areas of inquiry to explore (1) intersectional biases in social class impressions from faces and (2) how associations between social class and attractiveness/health and affect can be used to shift social class impressions. Our studies found evidence of race and gender stereotypes impacting British perceivers' social class judgements, with Black (vs. White and Asian) and female (vs. male) faces judged as lower in class. Furthermore, manipulating faces' emotion expression shifted judgements of their social class, with variations in magnitude by faces' race, such that emotion expressions shifted judgements of Black faces more than White faces. Finally, manipulating faces' complexion to appear healthier/more attractive shifted social class judgements, with the magnitude of this varying by faces' and perceivers' race, suggesting a role of perceptual expertise. These findings demonstrate that stereotypes bias social class impressions and can be used to manipulate them.

EEG evidence for racial ingroup bias in collective empathy for pain.

Previous research on racial ingroup bias in empathy for pain focused on neural responses to a single person's suffering. It is unclear whether empathy for simultaneously perceived multiple individuals' pain (denoted as collective empathy in this study) is also sensitive to perceived racial identities of empathy targets. We addressed this issue by recording electroencephalography from Chinese adults who responded to racial identities of 2 × 2 arrays of Asian or White faces in which 4 faces, 1 face, or no face showed painful expressions. Participants reported greater feelings of others' pain and their own unpleasantness when viewing 4 compared to 1 (or no) painful faces. Behavioral responses to racial identities of faces revealed decreased speeds of information acquisition when responding to the face arrays with 4 (vs. 1 or no) painful expressions of Asian (but not White) faces. Moreover, Asian compared to White face arrays with 4 (vs. 1 or no) painful expressions elicited a larger positive neural response at 160-190ms (P2) at the frontal/central electrodes and enhanced alpha synchronizations at 288-1,000ms at the central electrodes. Our findings provide evidence for racial ingroup biases in collective empathy for pain and unravel its relevant neural underpinnings.

Analysis of Sexual Dimorphic Features of the Jawline and Chin in White Celebrity Faces.

The jawline greatly influences facial shape and contributes to facial dimorphism. Analysis of lower facial shape and sexual dimorphic differences in contemporary attractive white faces can advance the goals of lower facial aesthetics and facial gender-affirming surgery (FGAS). Full-face, front-view photos of 47 white female and 21 white male celebrities were included from a list generated using GQ magazine's Highest Paid Models issue, People Magazine's Beautiful issue (1991-2022), and celebrities featured on lifestyle websites. Facial landmarks were detected through a facial analysis program using Vision framework and MATLAB. After converting pixel distances to absolute distances, lower face measurements were compared between males and females. The mean lower facial height was 6.08cm in females and 7.00cm in males (P value<0.001). The mean bigonial width was 11.21cm in females and 12.30cm in males (P value<0.001). The ratio of facial height to lower facial height was 2.98 in females and 2.76 in males (P value<0.001), signifying that symmetry in facial thirds is more prevalent in attractive female faces, while a longer lower face is more common in attractive male faces. The greatest differences in female and male facial contours were at gonial angles and chin. Analysis of contemporary white celebrity faces demonstrated significantly wider and longer lower facial measurements in males. The overall contour of the female lower face was more tapered at the gonial angles and chin compared to males. These results are important when planning lower facial rejuvenation or FGAS, as lower face size and proportions influence perceived gender and attractiveness.

Exploring effects of social information on talker-independent accent adaptation.

The present study examined whether race information about speakers can promote rapid and generalizable perceptual adaptation to second-language accent. First-language English listeners were presented with Cantonese-accented English sentences in speech-shaped noise during a training session with three intermixed talkers, followed by a test session with a novel (i.e., fourth) talker. Participants were assigned to view either three East Asian or three White faces during training, corresponding to each speaker. Results indicated no effect of the social priming manipulation on the training or test sessions, although both groups performed better at test than a control group.

AI Hyperrealism: Why AI Faces Are Perceived as More Real Than Human Ones

Recent evidence shows that AI-generated faces are now indistinguishable from human faces. However, algorithms are trained disproportionately on White faces, and thus White AI faces may appear especially realistic. In Experiment 1 (N = 124 adults), alongside our reanalysis of previously published data, we showed that White AI faces are judged as human more often than actual human faces—a phenomenon we term AI hyperrealism. Paradoxically, people who made the most errors in this task were the most confident (a Dunning-Kruger effect). In Experiment 2 (N = 610 adults), we used face-space theory and participant qualitative reports to identify key facial attributes that distinguish AI from human faces but were misinterpreted by participants, leading to AI hyperrealism. However, the attributes permitted high accuracy using machine learning. These findings illustrate how psychological theory can inform understanding of AI outputs and provide direction for debiasing AI algorithms, thereby promoting the ethical use of AI.