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.

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.

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.

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 (selfreport) 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. attitudes | Implicit Association Test | implicit social cognition | stereotypes | word embeddings

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Gender stereotypes are widely shared “collective representations” that link gender groups (e.g., male/female) with roles or attributes (e.g., career/family, science/arts). Such collective stereotypes, especially implicit stereotypes, are assumed to be so deeply embedded in society that they are resistant to change. Yet over the past several decades, shifts in real-world gender roles suggest the possibility that gender stereotypes may also have changed alongside such shifts. The current project tests the patterns of recent gender stereotype change using a decade (2007–2018) of continuously collected data from 1.4 million implicit and explicit tests of gender stereotypes (male-science/female-arts, male-career/female-family). Time series analyses revealed that, over just 10 years, both implicit and explicit male-science/female-arts and male-career/female-family stereotypes have shifted toward neutrality, weakening by 13%–19%. Furthermore, these trends were observed across nearly all demographic groups and in all geographic regions of the United States and several other countries, indicating worldwide shifts in collective implicit and explicit gender stereotypes.

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.

Humans possess a tendency to rapidly and consistently make character evaluations from mere facial appearance. Recent work shows that this tendency emerges surprisingly early: children as young as 3-years-old provide adult-like assessments of others on character attributes such as "nice," "strong," and "smart" based only on subtle variations in targets' face shape and physiognomy (i.e., latent face-traits). The present research examined the behavioral consequences of children's face-trait judgments by asking whether, and if so when in development, the appearance of face-traits also (a) shapes children's judgments of targets' behaviors and (b) guides children's behavior toward targets. Experiments 1 and 2 showed that, by 3 years of age, children used facial features in character evaluations but not in judgments of targets' behavior, whereas by 5 years of age, children reliably made both character and behavior judgments from face-traits. Age-related change in behavior judgments was also observed in children's own behaviors toward targets: Experiments 3 and 4 showed that, by age 5 (but not earlier), children were more likely to give gifts to targets with trustworthy and submissive-looking faces (Experiment 3) and showed concordance between their character evaluations and gift-giving behaviors (Experiment 4). These findings newly suggest that, although children may rapidly make character evaluations from face-trait appearance, predicting and performing social behaviors based on face-traits may require more developed and specific understanding of traits and their relationships to behaviors. Nevertheless, by kindergarten, even relatively arbitrary and subtle face-traits appear to have meaningful consequences in shaping children's social judgments and interactions.