







The out-group homogeneity effect is the perception of out-group members as more similar to one another than are in-group members, i.e. "they are alike; we are diverse".[1] Perceivers tend to have impressions about the diversity or variability of group members around those central tendencies or typical attributes of those group members. Thus, outgroup stereotypicality judgments are overestimated, supporting the view that out-group stereotypes are overgeneralizations.[2] The term "outgroup homogeneity effect", "outgroup homogeneity bias" or "relative outgroup homogeneity" have been explicitly contrasted with "outgroup homogeneity" in general,[3] the latter referring to perceived outgroup variability unrelated to perceptions of the ingroup.
As diversity increases, people paradoxically perceive social groups as more similar
With globalization and immigration, societal contexts differ in sheer variety of resident social groups. Social diversity challenges individuals to think in new ways about new kinds of people and where their groups all stand, relative to each other. However, psychological science does not yet specify how human minds represent social diversity, in homogeneous or heterogenous contexts. Mental maps of the array of society’s groups should differ when individuals inhabit more and less diverse ecologies. Nonetheless, predictions disagree on how they should differ. Confirmation bias suggests more diversity means more stereotype dispersion: With increased exposure, perceivers’ mental maps might differentiate more among groups, so their stereotypes would spread out (disperse). In contrast, individuation suggests more diversity means less stereotype dispersion, as perceivers experience within-group variety and between-group overlap. Worldwide, nationwide, individual, and longitudinal datasets ( n = 12,011) revealed a diversity paradox: More diversity consistently meant less stereotype dispersion. Both contextual and perceived ethnic diversity correlate with decreased stereotype dispersion. Countries and US states with higher levels of ethnic diversity (e.g., South Africa and Hawaii, versus South Korea and Vermont), online individuals who perceive more ethnic diversity, and students who moved to more ethnically diverse colleges mentally represent ethnic groups as more similar to each other, on warmth and competence stereotypes. Homogeneity shows more-differentiated stereotypes; ironically, those with the least exposure have the most-distinct stereotypes. Diversity means less-differentiated stereotypes, as in the melting pot metaphor. Diversity and reduced dispersion also correlate positively with subjective wellbeing.

The Illusion of Asymmetric Insight
The Misconception: You celebrate diversity and respect others’ points of view. The Truth: You are driven to create and form groups and then believe others are wrong just because they are oth…

Analytic racecraft: Race-based averages create illusory group differences in perceptions of racism.
So It Is, So It Shall Be: Group Regularities License Children's Prescriptive Judgments
Abstract When do descriptive regularities (what characteristics individuals have) become prescriptive norms (what characteristics individuals should have)? We examined children's (4–13 years) and adults' use of group regularities to make prescriptive judgments, employing novel groups (Hibbles and Glerks) that engaged in morally neutral behaviors (e.g., eating different kinds of berries). Participants were introduced to conforming or non‐conforming individuals (e.g., a Hibble who ate berries more typical of a Glerk). Children negatively evaluated non‐conformity, with negative evaluations declining with age (Study 1). These effects were replicable across competitive and cooperative intergroup contexts (Study 2) and stemmed from reasoning about group regularities rather than reasoning about individual regularities (Study 3). These data provide new insights into children's group concepts and have important implications for understanding the development of stereotyping and norm enforcement.

Groupthink
Groupthink is a psychological phenomenon that occurs within a group of people in which the desire for harmony or conformity in the group results in an irrational or dysfunctional decision-making outcome. Cohesiveness, or the desire for cohesiveness, in a group may produce a tendency among its members to agree at all costs.[1] This causes the group to minimize conflict and reach a consensus decision without critical evaluation.[2][3]
Misperceptions About Others
Perceptions about others play an important role in shaping people's attitudes and behaviors, as well as social norms more broadly. This review presents a meta-analysis of the recent empirical literature that examines perceptions about others in the field, covering over a million observations for a total of 434 elicited perceptions. We document a number of stylized facts. Misperceptions about others are widespread, asymmetric, much larger when about out-group members, and positively associated with one's own attitudes. Experimental treatments to recalibrate misperceptions generally work as intended; they sometimes lead to meaningful changes in behaviors, though this often occurs only immediately after the treatments. We discuss different conceptual frameworks that could explain the origin, persistence, and rigidity of misperceptions about others. We point to several directions for future research.

Network dynamics of social influence in the wisdom of crowds
Significance Since the discovery of the wisdom of crowds over 100 years ago theories of collective intelligence have held that group accuracy requires either statistical independence or informational diversity among individual beliefs. Empirical evidence suggests that allowing people to observe the beliefs of others leads to increased similarity of individual estimates, reducing independence and diversity without a corresponding increase in group accuracy. As a result, social influence is expected to undermine the wisdom of crowds. We present theoretical predictions and experimental findings demonstrating that, in decentralized networks, social influence generates learning dynamics that reliably improve the wisdom of crowds. We identify general conditions under which influence, not independence, produces the most accurate group judgments. , A longstanding problem in the social, biological, and computational sciences is to determine how groups of distributed individuals can form intelligent collective judgments. Since Galton’s discovery of the “wisdom of crowds” [Galton F (1907) Nature 75:450–451], theories of collective intelligence have suggested that the accuracy of group judgments requires individuals to be either independent, with uncorrelated beliefs, or diverse, with negatively correlated beliefs [Page S (2008) The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools, and Societies ]. Previous experimental studies have supported this view by arguing that social influence undermines the wisdom of crowds. These results showed that individuals’ estimates became more similar when subjects observed each other’s beliefs, thereby reducing diversity without a corresponding increase in group accuracy [Lorenz J, Rauhut H, Schweitzer F, Helbing D (2011) Proc Natl Acad Sci USA 108:9020–9025]. By contrast, we show general network conditions under which social influence improves the accuracy of group estimates, even as individual beliefs become more similar. We present theoretical predictions and experimental results showing that, in decentralized communication networks, group estimates become reliably more accurate as a result of information exchange. We further show that the dynamics of group accuracy change with network structure. In centralized networks, where the influence of central individuals dominates the collective estimation process, group estimates become more likely to increase in error.

If you rise, I fall: Equality is prevented by the misperception that it harms advantaged groups
Nine preregistered studies ( n = 4197) demonstrate that advantaged group members misperceive equality as necessarily harming their access to resources and inequality as necessarily benefitting them. Only when equality is increased within their ingroup, instead of between groups, do advantaged group members accurately perceive it as unharmful. Misperceptions persist when equality-enhancing policies offer broad benefits to society or when resources, and resource access, are unlimited. A longitudinal survey of the 2020 U.S. voters reveals that harm perceptions predict voting against actual equality-enhancing policies, more so than voters’ political and egalitarian beliefs. Finally two novel-groups experiments reveal that advantaged participants’ harm misperceptions predict voting for inequality-enhancing policies that financially hurt them and against equality-enhancing policies that financially benefit them. Misperceptions persist even after an intervention to improve decision-making. This misperception that equality is necessarily zero-sum may explain why inequality prevails even as it incurs societal costs that harm everyone. , Advantaged groups misperceive equality as harming their resource access, which predicts voting against equality policies.

Diversification bias: Explaining the discrepancy in variety seeking between combined and separated choices.
Religious intolerance is 'bigger cause of prejudice than race', says report
Attitudes to faith said to drive negative perceptions more than nationality or ethnicity

Asymmetry in Games
“Asymmetry”, in this context, refers to the player or players having different abilities from the start of a match. A Street Fighter II character, a StarCraft race, or a Magic: T…

Les mesures de discrimination positive bénéficient-elles aux populations qu’elles ciblent ?
Les mesures de discrimination positive sont apparues il y a un demi-siècle : elles instaurant un traitement inégal des individus en vue de réduire les inégalités. Aux Etats-Unis, des politiques de discrimination positive (sous le nom d’« affirmative action...
The Task Space: An Integrative Framework for Team Research
Research on teams spans many contexts, but integrating knowledge from heterogeneous sources is challenging because studies typically examine different tasks that cannot be directly compared. Most investigations involve teams working on just one or a handful of tasks, and researchers lack principled ways to quantify how similar or different these tasks are from one another. We address this challenge by introducing the “Task Space,” a multidimensional space in which tasks—and the distances between them—can be represented formally, and use it to create a “Task Map” of 102 crowd-annotated tasks from the published experimental literature. We then demonstrate the Task Space’s utility by performing an integrative experiment that addresses a fundamental question in team research: when do interacting groups outperform individuals? Our experiment samples 20 diverse tasks from the Task Map at three complexity levels and recruits 1,231 participants to work either individually or in groups of three or six (180 experimental conditions). We find striking heterogeneity in group advantage, with groups performing anywhere from three times worse to 60% better than the best individual working alone, depending on the task context. Critically, the Task Space makes this heterogeneity predictable: it significantly outperforms traditional typologies in predicting group advantage on unseen tasks. Our models also reveal theoretically meaningful interactions between task features; for example, group advantage on creative tasks depends on whether the answers are objectively verifiable. We conclude by arguing that the Task Space enables researchers to integrate findings across different experiments, thereby building cumulative knowledge about team performance. This paper was accepted by Sameer Srivastava, organizations. Funding: The authors thank the Alfred P. Sloan Foundation [Grant #202-13924] and the MIT Wade Fund for their generous support of this research. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.03544 .

Why Diversity Programs Fail
After Wall Street firms repeatedly had to shell out millions to settle discrimination lawsuits, businesses started to get serious about their efforts to increase diversity. But unfortunately, they don’t seem to be getting results: Women and minorities have not gained much ground in management over the past 20 years. The problem is, organizations are trying to reduce bias with the same kinds of programs they’ve been using since the 1960s. And the usual tools—diversity training, hiring tests, performance ratings, grievance systems—tend to make things worse, not better. The authors’ analysis of data from 829 firms over three decades shows that these tools actually decrease the proportion of women and minorities in management. They’re designed to preempt lawsuits by policing managers’ decisions and actions. But as lab studies show, this kind of force-feeding can activate bias and encourage rebellion. However, in their analysis the authors uncovered numerous diversity tactics that do move the needle, such as recruiting initiatives, mentoring programs, and diversity task forces. They engage managers in solving the problem, increase contact with women and minority workers, and promote social accountability. In this article, the authors dig into the data, executive interviews, and several examples to shed light on what doesn’t work and what does.

🧵New preprint: Adults often agree with their ingroup even when evidence says otherwise. Why? To find out, we studied kids, who show the same tendency but *before* political identities take hold. With developmental data, we can see the basic psychological ingredients. doi.org/10.31234/osf.io/gf38p_v1 1/11
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How large language models can reshape collective intelligence

Sharing Notes about Collective Intelligence — Pop Junctions

Socially Minded Intelligence: How Individuals, Groups, and Artificial Intelligence Can Make Each Other Smarter (or Not)

Profile: Adrien Treuille

NOVA | The Wisdom of the Crowds | Season 45 | Episode 6
Mapping Citizen Science through the Lens of Human-Centered AI