Transmission of social bias through observational learning.

People often rely on social learning-learning by observing others' actions and outcomes-to form preferences in advance of their own direct experiences. Although typically adaptive, we investigated whether social learning may also contribute to the formation and spread of prejudice. In six experiments (n = 1550), we demonstrate that by merely observing interactions between a prejudiced actor and social group members, observers acquired the prejudices of the actor. Moreover, observers were unaware of the actors' bias, misattributing their acquired group preferences to the behavior of group members, despite identical behavior between groups. Computational modeling revealed that this effect was due to value shaping, whereby one's preferences are shaped by another's actions toward a target, in addition to the target's reward feedback. These findings identify social learning as a potent mechanism of prejudice formation that operates implicitly and supports the transmission of intergroup bias.

Affective prediction errors in persistence and escalation of aggression.

People generally empathize with others and find harm aversive. Yet aggression, for example, between groups, abounds. How do people learn to overcome this aversion in order to aggress? Many models of learning emphasize outcome prediction errors-deviations from expected outcomes in the environment-but aggression may also be fueled by affective prediction errors (affective PEs)-deviations from how we expect to feel. Across five preregistered online experiments that hold outcome prediction errors constant (N = 4,607), participants choosing aggressive or nonaggressive actions aggressed more against disliked group members and often escalated or persisted in taking actions that felt better than expected (positive affective PE), especially when those actions were aggressive. Crucially, inducing incidental empathy toward the group of the target rendered affective PE signals sensitive to group identification-participants escalated aggression that felt better than expected relatively less toward liked versus disliked group members. That said, affective PEs did not always add explanatory power beyond levels of postoutcome affect alone; we discuss the importance and implications of these results. In summary, we reveal affective PE integration as a candidate algorithm facilitating exceptions to harm aversion in intergroup conflict. More broadly, we highlight for affective science and decision-making researchers the necessity of appropriately testing separable components of affective signals in predicting subsequent behavior. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

A research agenda for understanding how social inequality is linked to brain structure and function.

Consistent evidence documents powerful effects of social inequality on health, well-being and academic achievement. Yet research on whether social inequality may also be linked to brain structure and function has, until recently, been rare. Here we describe three methodological approaches that can be used to study this question-single site, single study; multi-site, single study; and spatial meta-analysis. We review empirical work that, using these approaches, has observed associations between neural outcomes and structural measures of social inequality-including structural stigma, community-level prejudice, gender inequality, neighbourhood disadvantage and the generosity of the social safety net for low-income families. We evaluate the relative strengths and limitations of these approaches, discuss ethical considerations and outline directions for future research. In doing so, we advocate for a paradigm shift in cognitive neuroscience that explicitly incorporates upstream structural and contextual factors, which we argue holds promise for uncovering the neural correlates of social inequality.

A synthesis of evidence for policy from behavioural science during COVID-19.

Scientific evidence regularly guides policy decisions1, with behavioural science increasingly part of this process2. In April 2020, an influential paper3 proposed 19 policy recommendations ('claims') detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms 'physical distancing' and 'social distancing'. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization.

State-level macro-economic factors moderate the association of low income with brain structure and mental health in U.S. children.

Macrostructural characteristics, such as cost of living and state-level anti-poverty programs relate to the magnitude of socioeconomic disparities in brain development and mental health. In this study we leveraged data from the Adolescent Brain and Cognitive Development (ABCD) study from 10,633 9-11 year old youth (5115 female) across 17 states. Lower income was associated with smaller hippocampal volume and higher internalizing psychopathology. These associations were stronger in states with higher cost of living. However, in high cost of living states that provide more generous cash benefits for low-income families, socioeconomic disparities in hippocampal volume were reduced by 34%, such that the association of family income with hippocampal volume resembled that in the lowest cost of living states. We observed similar patterns for internalizing psychopathology. State-level anti-poverty programs and cost of living may be confounded with other factors related to neurodevelopment and mental health. However, the patterns were robust to controls for numerous state-level social, economic, and political characteristics. These findings suggest that state-level macrostructural characteristics, including the generosity of anti-poverty policies, are potentially relevant for addressing the relationship of low income with brain development and mental health.

Structure learning principles of stereotype change.

Why, when, and how do stereotypes change? This paper develops a computational account based on the principles of structure learning: stereotypes are governed by probabilistic beliefs about the assignment of individuals to groups. Two aspects of this account are particularly important. First, groups are flexibly constructed based on the distribution of traits across individuals; groups are not fixed, nor are they assumed to map on to categories we have to provide to the model. This allows the model to explain the phenomena of group discovery and subtyping, whereby deviant individuals are segregated from a group, thus protecting the group's stereotype. Second, groups are hierarchically structured, such that groups can be nested. This allows the model to explain the phenomenon of subgrouping, whereby a collection of deviant individuals is organized into a refinement of the superordinate group. The structure learning account also sheds light on several factors that determine stereotype change, including perceived group variability, individual typicality, cognitive load, and sample size.

Differentiating Between Us & Them: Reduced In-Group Bias as a Novel Mechanism Linking Childhood Violence Exposure with Internalizing Psychopathology.

Strong in-group bonds, facilitated by implicit favoritism for in-group members (i.e., in-group bias), promote mental health across development. Yet, we know little about how the development of in-group bias is shaped by early-life experiences. Childhood violence exposure is known to alter social information processing biases. Violence exposure may also influence social categorization processes, including in-group biases, in ways that influence risk for psychopathology. We examined associations of childhood violence exposure with psychopathology and behavioral and neural indices of implicit and explicit bias for novel groups in children followed longitudinally across three time points from age 5 to 10 years old (n = 101 at baseline; n = 58 at wave 3). To instantiate in-group and out-group affiliations, youths underwent a minimal group assignment induction procedure, in which they were randomly assigned to one of two groups. Youth were told that members of their assigned group shared common interests (in-group) and members of the other group did not (out-group). In pre-registered analyses, violence exposure was associated with lower implicit in-group bias, which in turn was associated prospectively with higher internalizing symptoms and mediated the longitudinal association between violence exposure and internalizing symptoms. During an fMRI task examining neural responses while classifying in-group and out-group members, violence-exposed children did not exhibit the negative functional coupling between vmPFC and amygdala to in-group vs. out-group members that was observed in children without violence exposure. Reduced implicit in-group bias may represent a novel mechanism linking violence exposure with the development of internalizing symptoms.

Interpersonal utility and children's social inferences from shared preferences.

Similarity of behaviors or attributes is often used to infer social affiliation and prosociality. Does this reflect reasoning using a simple expectation of homophily, or more complex reasoning about shared utility? We addressed this question by examining the inferences children make from similar choices when this similarity does or does not cause competition over a zero-sum resource. Four- to six-year-olds (N = 204) saw two vignettes, each featuring three characters (a target plus two others) choosing between two types of resources. In all stories, each character expressed a preference: one 'other' chose the same resource as the target, while a second 'other' chose the different resource. In one condition there were enough resources for all the characters; in the other condition, one type of resource was limited, with only one available (inducing potential competition between the target and the similar-choice other). Children then judged which of the two 'other' characters was being nicer (prosocial judgment) and which of the two was more preferred by the target (affiliative inference). When resources were limited (vs. unlimited), children were less likely to select the similar other as being nice. Children's initial tendency to report that the target preferred the similar other was also eliminated in the limited resource scenario. These findings show that children's reasoning about similarity is not wholly based on homophily. Instead, by reasoning about shared utility - how each person values the goals of others - children engage in flexible inferences regarding whether others' similar preferences and behaviors have positive or negative social meaning.

Community-level explicit racial prejudice potentiates whites' neural responses to black faces: A spatial meta-analysis.

We evaluated the hypothesis that neural responses to racial out-group members vary systematically based on the level of racial prejudice in the surrounding community. To do so, we conducted a spatial meta-analysis, which included a comprehensive set of studies (k = 22; N = 481). Specifically, we tested whether community-level racial prejudice moderated neural activation to Black (vs. White) faces in primarily White participants. Racial attitudes, obtained from Project Implicit, were aggregated to the county (k = 17; N = 10,743) in which each study was conducted. Multi-level kernel density analysis demonstrated that significant differences in neural activation to Black (vs. White) faces in right amygdala, dorsal anterior cingulate cortex, and dorsolateral prefrontal cortex were detected more often in communities with higher (vs. lower) levels of explicit (but not implicit) racial prejudice. These findings advance social-cognitive neuroscience by identifying aspects of macro-social contexts that may alter neural responses to out-group members.

Hate crime towards minoritized groups increases as they increase in sized-based rank.

People are on the move in unprecedented numbers within and between countries. How does demographic change affect local intergroup dynamics? Complementing accounts that emphasize stereotypical features of groups as determinants of their treatment, we propose the group reference dependence hypothesis: violence and negative attitudes towards each minoritized group will depend on the number and size of other minoritized groups in a community. Specifically, as groups increase or decrease in rank in terms of their size (for example, to the largest minority within a community), discriminatory behaviour and attitudes towards them should change accordingly. We test this hypothesis for hate crimes in US counties between 1990 and 2010 and attitudes in the United States and United Kingdom over the past two decades. Consistent with this prediction, we find that as Black, Hispanic/Latinx, Asian and Arab populations increase in rank relative to one another, they become more likely to be targeted with hate crimes and more negative attitudes. The rank effect holds above and beyond group size/proportion, growth rate and many other alternative explanations. This framework makes predictions about how demographic shifts may affect coalitional structures in the coming years and helps explain previous findings in the literature. Our results also indicate that attitudes and behaviours towards social categories are not intransigent or driven only by features associated with those groups, such as stereotypes.

Latent structure learning as an alternative computation for group inference.

In contrast to Pietraszewski's account, latent structure learning neither requires conflict nor relies on observation of explicit coalitional behavior to support group inference. This alternative addresses how even non-conflict-based groups may be defined and is supported by experimental evidence in human behavior.

Understanding and combating misperceived polarization.

By many accounts politics is becoming more polarized, yielding dire consequences for democracy and trust in government. Yet a growing body of research on so-called false polarization finds that perceptions of 'what the other side believes' are inaccurate-specifically, overly pessimistic-and that these inaccuracies exacerbate intergroup conflict. Through a review of existing work and a reanalysis of published data, we (i) develop a typology of the disparate phenomena that are labelled 'polarization', (ii) use that typology to distinguish actual from (mis)perceived polarization, and (iii) identify when misperceived polarization gives rise to actual polarization (e.g. extreme issue attitudes and prejudice). We further suggest that a specific psychological domain is ideal for developing corrective interventions: meta-perception, one's judgement of how they are perceived by others. We review evidence indicating that correcting meta-perception inaccuracies is effective at reducing intergroup conflict and discuss methods for precisely measuring meta-perception accuracy. We argue that the reputational nature of meta-perception provides a motivational mechanism by which individuals are sensitive to the truth, even when those truths pertain to the 'other side'. We conclude by discussing how these insights can be integrated into existing research seeking to understand polarization and its negative consequences. This article is part of the theme issue 'The political brain: neurocognitive and computational mechanisms'.

The Crowd-Emotion-Amplification Effect.

How do people go about reading a room or taking the temperature of a crowd? When people catch a brief glimpse of an array of faces, they can focus their attention on only some of the faces. We propose that perceivers preferentially attend to faces exhibiting strong emotions and that this generates a crowd-emotion-amplification effect-estimating a crowd's average emotional response as more extreme than it actually is. Study 1 (N = 50) documented the crowd-emotion-amplification effect. Study 2 (N = 50) replicated the effect even when we increased exposure time. Study 3 (N = 50) used eye tracking to show that attentional bias to emotional faces drives amplification. These findings have important implications for many domains in which individuals must make snap judgments regarding a crowd's emotionality, from public speaking to controlling crowds.

Activating episodic simulation increases affective empathy.

Affective empathy, feeling what others feel, is a powerful emotion that binds us to one another. Here we ask whether how we mentally represent the scene in which another suffers informs our emotions. For example, when we learn about someone suffering outside of the here and now, such as a refugee devastated by violence or famine, does a manipulation potentiating our ability to simulate the scene around the victim heighten our empathic response? Expanding recent advances in the memory literature, we investigate the link between activating our ability to imagine events-episodic simulation-and empathy for in-group and out-group members in a series of online and laboratory studies (N = 1010). Incidental manipulations of episodic simulation, unrelated in content and structure to the empathy judgment task, increased overall empathy for both in-group as well as out-group members. This relationship was mediated by participant-generated episodic detail of the victim's surroundings.

Strategic Regulation of Empathy.

Empathy is an integral part of socioemotional well-being, but recent research has highlighted some of its downsides. Here we examine literature that establishes when, how much, and what aspects of empathy promote specific outcomes. After reviewing a theoretical framework that characterizes empathy as a suite of separable components, we examine evidence showing how dissociations of these components affect important socioemotional outcomes and describe emerging evidence suggesting that these components can be independently and deliberately regulated. Finally, we advocate for an approach to a multicomponent view of empathy that accounts for the interrelations among components. This perspective advances scientific conceptualization of empathy and offers suggestions for tailoring empathy to help people realize their social, emotional, and occupational goals.

Narratives Shape Cognitive Representations of Immigrants and Immigration-Policy Preferences.

Scholars from across the social and media sciences have issued a clarion call to address a recent resurgence in criminalized characterizations of immigrants. Do these characterizations meaningfully impact individuals' beliefs about immigrants and immigration? Across two online convenience samples (total N = 1,054 adult U.S. residents), we applied a novel analytic technique to test how different narratives-achievement, criminal, and struggle-oriented-impacted cognitive representations of German, Russian, Syrian, and Mexican immigrants and the concept of immigrants in general. All stories featured male targets. Achievement stories homogenized individual immigrant representations, whereas both criminal and struggle-oriented stories racialized them along a White/non-White axis: Germany clustered with Russia, and Syria clustered with Mexico. However, criminal stories were unique in making our most egalitarian participants' representations as differentiated as our least egalitarian participants'. Narratives about individual immigrants also generalized to update representations of nationality groups. Most important, narrative-induced representations correlated with immigration-policy preferences: Achievement narratives and corresponding homogenized representations promoted preferences for less restriction, and criminal narratives promoted preferences for more.

The Social Neuroscience of Prejudice.

The social neuroscience approach to prejudice investigates the psychology of intergroup bias by integrating models and methods of neuroscience with the social psychology of prejudice, stereotyping, and discrimination. Here, we review major contemporary lines of inquiry, including current accounts of group-based categorization; formation and updating of prejudice and stereotypes; effects of prejudice on perception, emotion, and decision making; and the self-regulation of prejudice. In each section, we discuss key social neuroscience findings, consider interpretational challenges and connections with the behavioral literature, and highlight how they advance psychological theories of prejudice. We conclude by discussing the next-generation questions that will continue to guide the social neuroscience approach toward addressing major societal issues of prejudice and discrimination.

Reasoning supports utilitarian resolutions to moral dilemmas across diverse measures.

Sacrificial moral dilemmas elicit a strong conflict between the motive to not personally harm someone and the competing motive to achieving the greater good, which is often described as the "utilitarian" response. Some prior research suggests that reasoning abilities and deliberative cognitive style are associated with endorsement of utilitarian solutions, but, as has more recently been emphasized, both conceptual and methodological issues leave open the possibility that utilitarian responses are due instead to a reduced emotional response to harm. Across 8 studies, using self-report, behavioral performance, and neuroanatomical measures, we show that individual differences in reasoning ability and cognitive style of thinking are positively associated with a preference for utilitarian solutions, but bear no relationship to harm-relevant concerns. These findings support the dual-process model of moral decision making and highlight the utility of process dissociation methods. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Deliberately prejudiced self-driving vehicles elicit the most outrage.

Should self-driving vehicles be prejudiced, e.g., deliberately harm the elderly over young children? When people make such forced-choices on the vehicle's behalf, they exhibit systematic preferences (e.g., favor young children), yet when their options are unconstrained they favor egalitarianism. So, which of these response patterns should guide AV programming and policy? We argue that this debate is missing the public reaction most likely to threaten the industry's life-saving potential: moral outrage. We find that people are more outraged by AVs that kill discriminately than indiscriminately. Crucially, they are even more outraged by an AV that deliberately kills a less preferred group (e.g., an elderly person over a child) than by one that indiscriminately kills a more preferred group (e.g., a child). Thus, at least insofar as the public is concerned, there may be more reason to depict and program AVs as egalitarian.