All human social groups are human, but some are more human than others: A comprehensive investigation of the implicit association of "Human" to US racial/ethnic groups.

All human groups are equally human, but are they automatically represented as such? Harnessing data from 61,377 participants across 13 experiments (six primary and seven supplemental), a sharp dissociation between implicit and explicit measures emerged. Despite explicitly affirming the equal humanity of all racial/ethnic groups, White participants consistently associated Human (relative to Animal) more with White than Black, Hispanic, and Asian groups on Implicit Association Tests (IATs; experiments 1-4). This effect emerged across diverse representations of Animal that varied in valence (pets, farm animals, wild animals, and vermin; experiments 1-2). Non-White participants showed no such Human=Own Group bias (e.g., Black participants on a White-Black/Human-Animal IAT). However, when the test included two outgroups (e.g., Asian participants on a White-Black/Human-Animal IAT), non-White participants displayed Human=White associations. The overall effect was largely invariant across demographic variations in age, religion, and education but did vary by political ideology and gender, with self-identified conservatives and men displaying stronger Human=White associations (experiment 3). Using a variance decomposition method, experiment 4 showed that the Human=White effect cannot be attributed to valence alone; the semantic meaning of Human and Animal accounted for a unique proportion of variance. Similarly, the effect persisted even when Human was contrasted with positive attributes (e.g., God, Gods, and Dessert; experiment 5a). Experiments 5a-b clarified the primacy of Human=White rather than Animal=Black associations. Together, these experiments document a factually erroneous but robust Human=Own Group implicit stereotype among US White participants (and globally), with suggestive evidence of its presence in other socially dominant groups.

Historical representations of social groups across 200 years of word embeddings from Google Books.

Using word embeddings from 850 billion words in English-language Google Books, we provide an extensive analysis of historical change and stability in social group representations (stereotypes) across a long timeframe (from 1800 to 1999), for a large number of social group targets (Black, White, Asian, Irish, Hispanic, Native American, Man, Woman, Old, Young, Fat, Thin, Rich, Poor), and their emergent, bottom-up associations with 14,000 words and a subset of 600 traits. The results provide a nuanced picture of change and persistence in stereotypes across 200 y. Change was observed in the top-associated words and traits: Whether analyzing the top 10 or 50 associates, at least 50% of top associates changed across successive decades. Despite this changing content of top-associated words, the average valence (positivity/negativity) of these top stereotypes was generally persistent. Ultimately, through advances in the availability of historical word embeddings, this study offers a comprehensive characterization of both change and persistence in social group representations as revealed through books of the English-speaking world from 1800 to 1999.

Patterns of Implicit and Explicit Attitudes: IV. Change and Stability From 2007 to 2020.

Using more than 7.1 million implicit and explicit attitude tests drawn from U.S. participants to the Project Implicit website, we examined long-term trends across 14 years (2007-2020). Despite tumultuous sociopolitical events, trends from 2017 to 2020 persisted largely as forecasted from past data (2007-2016). Since 2007, all explicit attitudes decreased in bias between 22% (age attitudes) and 98% (race attitudes). Implicit sexuality, race, and skin-tone attitudes also continued to decrease in bias, by 65%, 26%, and 25%, respectively. Implicit age, disability, and body-weight attitudes, however, continued to show little to no long-term change. Patterns of change and stability were generally consistent across demographic groups (e.g., men and women), indicating widespread, macrolevel change. Ultimately, the data magnify evidence that (some) implicit attitudes reveal persistent, long-term change toward neutrality. The data also newly reveal the potential for short-term influence from sociopolitical events that temporarily disrupt progress toward neutrality, although attitudes eventually return to long-term homeostasis in trends.

Model-free and model-based learning processes in the updating of explicit and implicit evaluations.

Evaluating stimuli along a good-bad dimension is a fundamental computation performed by the human mind. In recent decades, research has documented dissociations and associations between explicit (i.e., self-reported) and implicit (i.e., indirectly measured) forms of evaluations. However, it is unclear whether such dissociations arise from relatively more superficial differences in measurement techniques or from deeper differences in the processes by which explicit and implicit evaluations are acquired and represented. The present project (total N = 2,354) relies on the computationally well-specified distinction between model-based and model-free reinforcement learning to investigate the unique and shared aspects of explicit and implicit evaluations. Study 1 used a revaluation procedure to reveal that, whereas explicit evaluations of novel targets are updated via model-free and model-based processes, implicit evaluations depend on the former but are impervious to the latter. Studies 2 and 3 demonstrated the robustness of this effect to (i) the number of stimulus exposures in the revaluation phase and (ii) the deterministic vs. probabilistic nature of initial reinforcement. These findings provide a framework, going beyond traditional dual-process and single-process accounts, to highlight the context-sensitivity and long-term recalcitrance of implicit evaluations as well as variations in their relationship with their explicit counterparts. These results also suggest avenues for designing theoretically guided interventions to produce change in implicit evaluations.

The relationship between implicit intergroup attitudes and beliefs.

Intergroup attitudes (evaluations) are generalized valence attributions to social groups (e.g., white-bad/Asian-good), whereas intergroup beliefs (stereotypes) are specific trait attributions to social groups (e.g., white-dumb/Asian-smart). When explicit (self-report) measures are used, attitudes toward and beliefs about the same social group are often related to each other but can also be dissociated. The present work used three approaches (correlational, experimental, and archival) to conduct a systematic investigation of the relationship between implicit (indirectly revealed) intergroup attitudes and beliefs. In study 1 (n = 1,942), we found significant correlations and, in some cases, evidence for redundancy, between Implicit Association Tests (IATs) measuring attitudes toward and beliefs about the same social groups (mean r = 0.31, 95% confidence interval: [0.24; 0.39]). In study 2 (n = 383), manipulating attitudes via evaluative conditioning produced parallel changes in belief IATs, demonstrating that implicit attitudes can causally drive implicit beliefs when information about the specific semantic trait is absent. In study 3, we used word embeddings derived from a large corpus of online text to show that the relative distance of 22 social groups from positive vs. negative words (reflecting generalized attitudes) was highly correlated with their distance from warm vs. cold, and even competent vs. incompetent, words (reflecting specific beliefs). Overall, these studies provide convergent evidence for tight connections between implicit attitudes and beliefs, suggesting that the dissociations observed using explicit measures may arise uniquely from deliberate judgment processes.

Two thousand years after Archimedes, psychologist finds three topics that will simply not yield to the experimental method.

Cesario argues that experiments cannot illuminate real group disparities because they leave out factors that operate in ordinary life. But what Cesario calls flaws are, in fact, the point of the experimental method. Of all the topics in science, we have to wonder why racial discrimination would be uniquely unsuited for investigating with experiments. The argument to give up the most powerful scientific method to study one of the hardest problems we confront is laughable.

Gender Stereotypes in Natural Language: Word Embeddings Show Robust Consistency Across Child and Adult Language Corpora of More Than 65 Million Words.

Stereotypes are associations between social groups and semantic attributes that are widely shared within societies. The spoken and written language of a society affords a unique way to measure the magnitude and prevalence of these widely shared collective representations. Here, we used word embeddings to systematically quantify gender stereotypes in language corpora that are unprecedented in size (65+ million words) and scope (child and adult conversations, books, movies, TV). Across corpora, gender stereotypes emerged consistently and robustly for both theoretically selected stereotypes (e.g., work-home) and comprehensive lists of more than 600 personality traits and more than 300 occupations. Despite underlying differences across language corpora (e.g., time periods, formats, age groups), results revealed the pervasiveness of gender stereotypes in every corpus. Using gender stereotypes as the focal issue, we unite 19th-century theories of collective representations and 21st-century evidence on implicit social cognition to understand the subtle yet persistent presence of collective representations in language.

Gender in Science, Technology, Engineering, and Mathematics: Issues, Causes, Solutions.

The landscape of gender in education and the workforce has shifted over the past decades: women have made gains in representation, equitable pay, and recognition through awards, grants, and publications. Despite overall change, differences persist in the fields of science, technology, engineering, and mathematics (STEM). This Viewpoints article on gender disparities in STEM offers an overarching perspective by addressing what the issues are, why the issues may emerge, and how the issues may be solved. In Part 1, recent data on gaps in representation, compensation, and recognition (awards, grants, publications) are reviewed, highlighting differences across subfields (e.g., computer science vs biology) and across career trajectories (e.g., bachelor's degrees vs senior faculty). In Part 2, evidence on leading explanations for these gaps, including explanations centered on abilities, preferences, and explicit and implicit bias, is presented. Particular attention is paid to implicit bias: mental processes that exist largely outside of conscious awareness and control in both male and female perceivers and female targets themselves. Given its prevalence and persistence, implicit bias warrants a central focus for research and application. Finally, in Part 3, the current knowledge is presented on interventions to change individuals' beliefs and behaviors, as well as organizational culture and practices. The moral issues surrounding equal access aside, understanding and addressing the complex issues surrounding gender in STEM are important because of the possible benefits to STEM and society that will be realized only when full participation of all capable and qualified individuals is guaranteed.

Children's implicit attitude acquisition: Evaluative statements succeed, repeated pairings fail.

From the earliest ages tested, children and adults show similar overall magnitudes of implicit attitudes toward various social groups. However, such consistency in attitude magnitude may obscure meaningful age-related change in the ways that children (vs. adults) acquire implicit attitudes. This experiment investigated children's implicit attitude acquisition by comparing the separate and joint effects of two learning interventions, previously shown to form implicit attitudes in adults. Children (N = 280, ages 7-11 years) were taught about novel social groups through either evaluative statements (ES; auditorily presented verbal statements such as 'Longfaces are bad, Squarefaces are good'), repeated evaluative pairings (REP; visual pairings of Longface/Squareface group members with valenced images such as a puppy or snake), or a combination of ES+REP. Results showed that children acquired implicit attitudes following ES and ES+REP, with REP providing no additional learning beyond ES alone. Moreover, children did not acquire implicit attitudes in four variations of REP, each designed to facilitate learning by systematically increasing verbal scaffolding to specify (a) the learning goal, (b) the valence of the unconditioned stimuli, and (c) the group categories of the conditioned stimuli. These findings underscore the early-emerging role of verbal statements in children's implicit attitude acquisition, as well as a possible age-related limit in children's acquisition of novel implicit attitudes from repeated pairings.

Pupillometric decoding of high-level musical imagery.

Humans report imagining sound where no physical sound is present: we replay conversations, practice speeches, and "hear" music all within the confines of our minds. Research has identified neural substrates underlying auditory imagery; yet deciphering its explicit contents has been elusive. Here we present a novel pupillometric method for decoding what individuals hear "inside their heads". Independent of light, pupils dilate and constrict in response to noradrenergic activity. Hence, stimuli evoking unique and reliable patterns of attention and arousal even when imagined should concurrently produce identifiable patterns of pupil-size dynamics (PSDs). Participants listened to and then silently imagined music while eye-tracked. Using machine learning algorithms, we decoded the imagined songs within- and across-participants following classifier-training on PSDs collected during both imagination and perception. Echoing findings in vision, cross-domain decoding accuracy increased with imagery strength. These data suggest that light-independent PSDs are a neural signature sensitive enough to decode imagination.

Inferring an unobservable population size from observable samples.

Success in the physical and social worlds often requires knowledge of population size. However, many populations cannot be observed in their entirety, making direct assessment of their size difficult, if not impossible. Nevertheless, an unobservable population size can be inferred from observable samples. We measured people's ability to make such inferences and their confidence in these inferences. Contrary to past work suggesting insensitivity to sample size and failures in statistical reasoning, inferences of populations size were accurate-but only when observable samples indicated a large underlying population. When observable samples indicated a small underlying population, inferences were systematically biased. This error, which cannot be attributed to a heuristics account, was compounded by a metacognitive failure: Confidence was highest when accuracy was at its worst. This dissociation between accuracy and confidence was confirmed by a manipulation that shifted the magnitude and variability of people's inferences without impacting their confidence. Together, these results (a) highlight the mental acuity and limits of a fundamental human judgment and (b) demonstrate an inverse relationship between cognition and metacognition.

Patterns of Implicit and Explicit Attitudes: I. Long-Term Change and Stability From 2007 to 2016.

Using 4.4 million tests of implicit and explicit attitudes measured continuously from an Internet population of U.S. respondents over 13 years, we conducted the first comparative analysis using time-series models to examine patterns of long-term change in six social-group attitudes: sexual orientation, race, skin tone, age, disability, and body weight. Even within just a decade, all explicit responses showed change toward attitude neutrality. Parallel implicit responses also showed change toward neutrality for sexual orientation, race, and skin-tone attitudes but revealed stability over time for age and disability attitudes and change away from neutrality for body-weight attitudes. These data provide previously unavailable evidence for long-term implicit attitude change and stability across multiple social groups; the data can be used to generate and test theoretical predictions as well as construct forecasts of future attitudes.

People Make the Same Bayesian Judgment They Criticize in Others.

When two individuals from different social groups exhibit identical behavior, egalitarian codes of conduct call for equal judgments of both individuals. However, this moral imperative is at odds with the statistical imperative to consider priors based on group membership. Insofar as these priors differ, Bayesian rationality calls for unequal judgments of both individuals. We show that participants criticized the morality and intellect of someone else who made a Bayesian judgment, shared less money with this person, and incurred financial costs to punish this person. However, participants made unequal judgments as a Bayesian statistician would, thereby rendering the same judgment that they found repugnant when offered by someone else. This inconsistency, which can be reconciled by differences in which base rate is attended to, suggests that participants use group membership in a way that reflects the savvy of a Bayesian and the disrepute of someone they consider to be a bigot.

The base rate principle and the fairness principle in social judgment.

Meet Jonathan and Elizabeth. One person is a doctor and the other is a nurse. Who is the doctor? When nothing else is known, the base rate principle favors Jonathan to be the doctor and the fairness principle favors both individuals equally. However, when individuating facts reveal who is actually the doctor, base rates and fairness become irrelevant, as the facts make the correct answer clear. In three experiments, explicit and implicit beliefs were measured before and after individuating facts were learned. These facts were either stereotypic (e.g., Jonathan is the doctor, Elizabeth is the nurse) or counterstereotypic (e.g., Elizabeth is the doctor, Jonathan is the nurse). Results showed that before individuating facts were learned, explicit beliefs followed the fairness principle, whereas implicit beliefs followed the base rate principle. After individuating facts were learned, explicit beliefs correctly aligned with stereotypic and counterstereotypic facts. Implicit beliefs, however, were immune to counterstereotypic facts and continued to follow the base rate principle. Having established the robustness and generality of these results, a fourth experiment verified that gender stereotypes played a causal role: when both individuals were male, explicit and implicit beliefs alike correctly converged with individuating facts. Taken together, these experiments demonstrate that explicit beliefs uphold fairness and incorporate obvious and relevant facts, but implicit beliefs uphold base rates and appear relatively impervious to counterstereotypic facts.

Introducing the Open Affective Standardized Image Set (OASIS).

We introduce the Open Affective Standardized Image Set (OASIS), an open-access online stimulus set containing 900 color images depicting a broad spectrum of themes, including humans, animals, objects, and scenes, along with normative ratings on two affective dimensions-valence (i.e., the degree of positive or negative affective response that the image evokes) and arousal (i.e., the intensity of the affective response that the image evokes). The OASIS images were collected from online sources, and valence and arousal ratings were obtained in an online study (total N = 822). The valence and arousal ratings covered much of the circumplex space and were highly reliable and consistent across gender groups. OASIS has four advantages: (a) the stimulus set contains a large number of images in four categories; (b) the data were collected in 2015, and thus OASIS features more current images and reflects more current ratings of valence and arousal than do existing stimulus sets; (c) the OASIS database affords users the ability to interactively explore images by category and ratings; and, most critically, (d) OASIS allows for free use of the images in online and offline research studies, as they are not subject to the copyright restrictions that apply to the International Affective Picture System. The OASIS images, along with normative valence and arousal ratings, are available for download from www.benedekkurdi.com/#oasis or https://db.tt/yYTZYCga .

The development of implicit gender attitudes.

The development course of implicit and explicit gender attitudes between the ages of 5 and adulthood is investigated. Findings demonstrate that implicit and explicit own-gender preferences emerge early in both boys and girls, but implicit own-gender preferences are stronger in young girls than boys. In addition, female participants' attitudes remain largely stable over development, whereas male participants' implicit and explicit attitudes show an age-related shift towards increasing female positivity. Gender attitudes are an anomaly in that social evaluations dissociate from social status, with both male and female participants tending to evaluate female more positively than male.

Cognition can affect perception: Restating the evidence of a top-down effect.

We argue that Firestone & Scholl (F&S) provide worthwhile recommendations but that their critique of research by Levin and Banaji (2006) is unfounded. In addition, we argue that F&S apply unjustified level of skepticism about top-down effects relative to other broad hypotheses about the sources of perceptual intelligence.

Inferring character from faces: a developmental study.

Human adults attribute character traits to faces readily and with high consensus. In two experiments investigating the development of face-to-trait inference, adults and children ages 3 through 10 attributed trustworthiness, dominance, and competence to pairs of faces. In Experiment 1, the attributions of 3- to 4-year-olds converged with those of adults, and 5- to 6-year-olds' attributions were at adult levels of consistency. Children ages 3 and above consistently attributed the basic mean/nice evaluation not only to faces varying in trustworthiness (Experiment 1) but also to faces varying in dominance and competence (Experiment 2). This research suggests that the predisposition to judge others using scant facial information appears in adultlike forms early in childhood and does not require prolonged social experience.

Implicit race attitudes predict trustworthiness judgments and economic trust decisions.

Trust lies at the heart of every social interaction. Each day we face decisions in which we must accurately assess another individual's trustworthiness or risk suffering very real consequences. In a global marketplace of increasing heterogeneity with respect to nationality, race, and multiple other social categories, it is of great value to understand how implicitly held attitudes about group membership may support or undermine social trust and thereby implicitly shape the decisions we make. Recent behavioral and neuroimaging work suggests that a common mechanism may underlie the expression of implicit race bias and evaluations of trustworthiness, although no direct evidence of a connection exists. In two behavioral studies, we investigated the relationship between implicit race attitude (as measured by the Implicit Association Test) and social trust. We demonstrate that race disparity in both an individual's explicit evaluations of trustworthiness and, more crucially, his or her economic decisions to trust is predicted by that person's bias in implicit race attitude. Importantly, this relationship is robust and is independent of the individual's bias in explicit race attitude. These data demonstrate that the extent to which an individual invests in and trusts others with different racial backgrounds is related to the magnitude of that individual's implicit race bias. The core dimension of social trust can be shaped, to some degree, by attitudes that reside outside conscious awareness and intention.

What do Different Beliefs Tell us? An Examination of Factual, Opinion-Based, and Religious Beliefs.

Children and adults differentiate statements of religious belief from statements of fact and opinion, but the basis of that differentiation remains unclear. Across three experiments, adults and 8-10-year-old children heard statements of factual, opinion-based, and religious belief. Adults and children judged that statements of factual belief revealed more about the world, statements of opinion revealed more about individuals, and statements of religious belief provided information about both. Children-unlike adults-judged that statements of religious belief revealed more about the world than the believer. These results led to three conclusions. First, judgments concerning the relative amount of information statements of religious belief provide about individuals change across development, perhaps because adults have more experience with diversity. Second, recognizing that statements of religious belief provide information about both the world and the believer does not require protracted learning. Third, statements of religious belief are interpreted as amalgams of factual and opinion-based statements.