Government policies can be productive tools for protecting citizens while simultaneously forging more egalitarian societies. At the same time, history has shown that well-intentioned governmental actions, such as those m...Government policies can be productive tools for protecting citizens while simultaneously forging more egalitarian societies. At the same time, history has shown that well-intentioned governmental actions, such as those meant to quell pandemics (e.g., blood-donation restrictions), can single out members of marginalized groups (e.g., men who have sex with men). How did government actions shape intergroup outcomes during the COVID-19 pandemic? Here, we draw from emerging research to provide informed conjectures regarding whether and how government actions affected stereotypes (e.g., beliefs about gender), prejudice (e.g., anti-Asian bias), and intergroup violence (e.g., hate crimes against Asian individuals) during the COVID-19 pandemic. We discuss research examining the impact of policies intended to curb the spread of the disease, and we consider possible effects of the strategies used to communicate about the virus. Furthermore, we highlight open questions regarding how and why pandemic policies and communication shape intergroup outcomes, propose key directions for future research, and note possible implications for future development of policy and communication strategies.
When people experience emotions in a group, their emotions tend to have stronger intensity and to last longer. Why is that? This question has occupied thinkers throughout history, and with the use of digital media it is...When people experience emotions in a group, their emotions tend to have stronger intensity and to last longer. Why is that? This question has occupied thinkers throughout history, and with the use of digital media it is even more pressing today. Historically, attention has mainly focused on processes driven by the way emotions are shared between people via emotional interactions. Although interactions are a major driver of group emotionality, I review empirical findings that suggest that understanding group emotionality requires a broader view that integrates two additional processes: how emotions unfold within the social infrastructure in which they are shared and how these processes are affected by people's cognition about emotions. I propose to summarize the literature using an infrastructure-cognition-interaction framework that contributes to a broader understanding of group emotionality, which should improve our ability to predict group emotionality and to change these emotions when they are undesired.
Perspect Psychol Sci
· 2024 Jan · PMID 37493140
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Culture is typically studied as socialized and learned. Yet lay intuitions may hold that culture is associated with biology via perceptions of race, presenting a problem for those who study culture: There may be a mismat...Culture is typically studied as socialized and learned. Yet lay intuitions may hold that culture is associated with biology via perceptions of race, presenting a problem for those who study culture: There may be a mismatch between how psychologists study culture and how their research is interpreted by lay audiences. This article is a call to researchers to recognize this mismatch as a problem and to critically evaluate the way we study culture. We first describe evidence that laypeople tend to associate culture with notions of folk biology. Next, we propose three suggestions for researchers: explicitly address whether biological processes are, or are not, relevant for studying culture in their work; consider using multiple methods because different methods for studying culture may come with assumptions about culture as more tied to socialization or biology; and represent all people as cultural by studying multiple forms of culture and by contextualizing all psychological research. Last, we provide an example for how researchers can implement these suggestions to encourage more accurate interpretations of findings.
Changing entrenched beliefs to alter people's behavior and increase societal welfare has been at the forefront of behavioral-science research, but with limited success. Here, we propose a new framework of characterizing...Changing entrenched beliefs to alter people's behavior and increase societal welfare has been at the forefront of behavioral-science research, but with limited success. Here, we propose a new framework of characterizing beliefs as a multidimensional system of interdependent mental representations across three cognitive structures (e.g., beliefs, evidence, and perceived norms) that are dynamically influenced by complex informational landscapes: the BENDING (Beliefs, Evidence, Norms, Dynamic Information Networked Graphs) model. This account of individual and collective beliefs helps explain beliefs' resilience to interventions and suggests that a promising avenue for increasing the effectiveness of misinformation-reduction efforts might involve graph-based representations of communities' belief systems. This framework also opens new avenues for future research with meaningful implications for some of the most critical challenges facing modern society, from the climate crisis to pandemic preparedness.
Decades of research on how to improve intergroup relations have primarily examined ways to change prejudiced attitudes. However, this focus on negative intergroup attitudes has yielded few effective solutions. Because in...Decades of research on how to improve intergroup relations have primarily examined ways to change prejudiced attitudes. However, this focus on negative intergroup attitudes has yielded few effective solutions. Because intergroup relations are shaped by behavior during intergroup interactions, it is necessary to identify constructs that have a strong causal impact on intergroup behavior change. In this article, I will discuss evidence showing that intergroup attitude change is neither a sufficient nor necessary cause for intergroup behavior change. Empirical research suggests that intergroup attitudes are difficult to change and have a limited effect on intergroup behavior. I also distinguish between constructs that primarily affect intergroup attitude change (e.g., counterstereotypical exemplars, evaluative conditioning) and constructs that primarily affect intergroup behavior change (e.g., social norms, self-efficacy). Further, suggestions for future research will also be provided to advance understanding of the various psychological constructs that influence intergroup behavior change, which will help us develop effective methods of improving intergroup relations.
The successful introduction of public policies to prompt behavior change hinges on the degree to which citizens endorse the proposed policies. Although there is a large body of research on psychological determinants of p...The successful introduction of public policies to prompt behavior change hinges on the degree to which citizens endorse the proposed policies. Although there is a large body of research on psychological determinants of public policy acceptance, these determinants have not yet been synthesized into an integrative framework that proposes hypotheses about their interplay. In this article, we develop a review-based, integrative public-policy-acceptance framework that introduces the desire for governmental support as a motivational foundation in public-policy acceptance. The framework traces the route from problem awareness to policy acceptance and, ultimately, policy compliance. We propose this relationship to be mediated by a desire for governmental support. We integrate numerous key variables assumed to qualify the relationship between problem awareness and the desire for governmental support, such as control attributions, trust, and value fit, as well as the relationship between the desire for governmental support and policy acceptance, such as perceived policy effectiveness, intrusiveness, and fairness. We exemplify the use of the proposed framework by applying it to climate policies.
Perspect Psychol Sci
· 2024 Jan · PMID 37470498
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This article addresses a paradox between self-perceptions of psychology as a liberal, progressive, antiracist discipline and profession and the persistent criticisms of racism and calls for decolonization. It builds on t...This article addresses a paradox between self-perceptions of psychology as a liberal, progressive, antiracist discipline and profession and the persistent criticisms of racism and calls for decolonization. It builds on the criticisms of epistemic exclusion and White centering, arguing that White supremacy is maintained by "conversational silencing" in which the focus on doing good psychology systematically draws attention away from the realities of racism and the operation of power. The process is illustrated by investigations of disciplinary discourse around non-Western, educated, industrialized, rich, and democratic psychology and on stereotyping, racism, and prejudice reduction, which constitute the vanguard of liberal scholarship in the discipline. This progressive scholarship nurtures "White ignorance," an absence of belief about systemic racism that psychology plays a part in upholding.
Perspect Psychol Sci
· 2024 Sep · PMID 37466493
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On digital media, algorithms that process data and recommend content have become ubiquitous. Their fast and barely regulated adoption has raised concerns about their role in well-being both at the individual and collecti...On digital media, algorithms that process data and recommend content have become ubiquitous. Their fast and barely regulated adoption has raised concerns about their role in well-being both at the individual and collective levels. Algorithmic mechanisms on digital media are powered by social drivers, creating a feedback loop that complicates research to disentangle the role of algorithms and already existing social phenomena. Our brief overview of the current evidence on how algorithms affect well-being, misinformation, and polarization suggests that the role of algorithms in these phenomena is far from straightforward and that substantial further empirical research is needed. Existing evidence suggests that algorithms mostly reinforce existing social drivers, a finding that stresses the importance of reflecting on algorithms in the larger societal context that encompasses individualism, populist politics, and climate change. We present concrete ideas and research questions to improve algorithms on digital platforms and to investigate their role in current problems and potential solutions. Finally, we discuss how the current shift from social media to more algorithmically curated media brings both risks and opportunities if algorithms are designed for individual and societal flourishing rather than short-term profit.
Davis-Stober CP, Dana J, Kellen D
… +2 more, McMullin SD, Bonifay W
Perspect Psychol Sci
· 2024 Jan · PMID 37466102
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Conducting research with human subjects can be difficult because of limited sample sizes and small empirical effects. We demonstrate that this problem can yield patterns of results that are practically indistinguishable...Conducting research with human subjects can be difficult because of limited sample sizes and small empirical effects. We demonstrate that this problem can yield patterns of results that are practically indistinguishable from flipping a coin to determine the direction of treatment effects. We use this idea of random conclusions to establish a baseline for interpreting effect-size estimates, in turn producing more stringent thresholds for hypothesis testing and for statistical-power calculations. An examination of recent meta-analyses in psychology, neuroscience, and medicine confirms that, even if all considered effects are real, results involving small effects are indeed indistinguishable from random conclusions.
Technological innovations have become a key driver of societal advancements. Nowhere is this more evident than in the field of machine learning (ML), which has developed algorithmic models that shape our decisions, behav...Technological innovations have become a key driver of societal advancements. Nowhere is this more evident than in the field of machine learning (ML), which has developed algorithmic models that shape our decisions, behaviors, and outcomes. These tools have widespread use, in part, because they can synthesize massive amounts of data to make seemingly objective recommendations. Yet, in the past few years, the ML community has been drawing attention to the need for caution when interpreting and using these models. This is because these models are created by humans, from data generated by humans, whose psychology allows for various biases that impact how the models are developed, trained, tested, and interpreted. As psychologists, we thus face a fork in the road: Down the first path, we can continue to use these models without examining and addressing these critical flaws and rely on computer scientists to try to mitigate them. Down the second path, we can turn our expertise in bias toward this growing field, collaborating with computer scientists to reduce the models' deleterious outcomes. This article serves to light the way down the second path by identifying how extant psychological research can help examine and curtail bias in ML models.
The cultural transmission of technical know-how has proven vital to the success of our species. The broad diversity of learning contexts and social configurations, as well as the various kinds of coordinated interactions...The cultural transmission of technical know-how has proven vital to the success of our species. The broad diversity of learning contexts and social configurations, as well as the various kinds of coordinated interactions they involve, speaks to our capacity to flexibly adapt to and succeed in transmitting vital knowledge in various learning contexts. Although often recognized by ethnographers, the flexibility of cultural learning has so far received little attention in terms of cognitive mechanisms. We argue that a key feature of the flexibility of cultural learning is that both the models and learners recruit cognitive mechanisms of action coordination to modulate their behavior contingently on the behavior of their partner, generating a process of mutual adaptation supporting the successful transmission of technical skills in diverse and fluctuating learning environments. We propose that the study of cultural learning would benefit from the experimental methods, results, and insights of joint-action research and, complementarily, that the field of joint-action research could expand its scope by integrating a learning and cultural dimension. Bringing these two fields of research together promises to enrich our understanding of cultural learning, its contextual flexibility, and joint action coordination.
Perspect Psychol Sci
· 2024 Mar · PMID 37450408
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Humans operate in groups that are oftentimes nested in multilayered collectives such as work units within departments and companies, neighborhoods within cities, and regions within nation states. With psychological scien...Humans operate in groups that are oftentimes nested in multilayered collectives such as work units within departments and companies, neighborhoods within cities, and regions within nation states. With psychological science mostly focusing on proximate reasons for individuals to join existing groups and how existing groups function, we still poorly understand why groups form ex nihilo, how groups evolve into complex multilayered social structures, and what explains fission-fusion dynamics. Here we address group formation and the evolution of social organization at both the proximate and ultimate level of analysis. Building on models of fitness interdependence and cooperation, we propose that socioecologies can create positive interdependencies among strangers and pave the way for the formation of stable coalitions and groups through reciprocity and reputation-based partner selection. Such groups are marked by in-group bounded, parochial cooperation together with an array of social institutions for managing the commons, allowing groups to scale in size and complexity while avoiding the breakdown of cooperation. Our analysis reveals how distinct group cultures can endogenously emerge from reciprocal cooperation, shows that social identification and group commitment are likely consequences rather than causes of group cooperation, and explains when intergroup relations gravitate toward peaceful coexistence, integration, or conflict.
Perspect Psychol Sci
· 2024 Jan · PMID 37439763
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Norms permeate human life. Most of people's activities can be characterized by rules about what is appropriate, allowed, required, or forbidden-rules that are crucial in making people hyper-cooperative animals. In this a...Norms permeate human life. Most of people's activities can be characterized by rules about what is appropriate, allowed, required, or forbidden-rules that are crucial in making people hyper-cooperative animals. In this article, I examine the current cognitive-evolutionary account of "norm psychology" and propose an alternative that is better supported by evidence and better placed to promote interdisciplinary dialogue. The incumbent theory focuses on rules and claims that humans genetically inherit cognitive and motivational mechanisms specialized for processing these rules. The cultural-evolutionary alternative defines normativity in relation to behavior-compliance, enforcement, and commentary-and suggests that it depends on implicit and explicit processes. The implicit processes are genetically inherited and domain-general; rather than being specialized for normativity, they do many jobs in many species. The explicit processes are culturally inherited and domain-specific; they are constructed from mentalizing and reasoning by social interaction in childhood. The cultural-evolutionary, or "cognitive gadget," perspective suggests that people alive today-parents, educators, elders, politicians, lawyers-have more responsibility for sustaining normativity than the nativist view implies. People's actions not only shape and transmit the rules, but they also create in each new generation mental processes that can grasp the rules and put them into action.
Perspect Psychol Sci
· 2024 Sep · PMID 37439761
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Artificial intelligence (AI) has the potential to improve human decision-making by providing decision recommendations and problem-relevant information to assist human decision-makers. However, the full realization of the...Artificial intelligence (AI) has the potential to improve human decision-making by providing decision recommendations and problem-relevant information to assist human decision-makers. However, the full realization of the potential of human-AI collaboration continues to face several challenges. First, the conditions that support complementarity (i.e., situations in which the performance of a human with AI assistance exceeds the performance of an unassisted human or the AI in isolation) must be understood. This task requires humans to be able to recognize situations in which the AI should be leveraged and to develop new AI systems that can learn to complement the human decision-maker. Second, human mental models of the AI, which contain both expectations of the AI and reliance strategies, must be accurately assessed. Third, the effects of different design choices for human-AI interaction must be understood, including both the timing of AI assistance and the amount of model information that should be presented to the human decision-maker to avoid cognitive overload and ineffective reliance strategies. In response to each of these three challenges, we present an interdisciplinary perspective based on recent empirical and theoretical findings and discuss new research directions.
Global climate change, the COVID-19 pandemic, and the spread of misinformation on social media are just a handful of highly consequential problems affecting society. We argue that the rough contours of many societal prob...Global climate change, the COVID-19 pandemic, and the spread of misinformation on social media are just a handful of highly consequential problems affecting society. We argue that the rough contours of many societal problems can be framed within a "wisdom of crowds" perspective. Such a framing allows researchers to recast complex problems within a simple conceptual framework and leverage known results on crowd wisdom. To this end, we present a simple "toy" model of the strengths and weaknesses of crowd wisdom that easily maps to many societal problems. Our model treats the judgments of individuals as random draws from a distribution intended to represent a heterogeneous population. We use a weighted mean of these individuals to represent the crowd's collective judgment. Using this setup, we show that subgroups have the potential to produce substantively different judgments and we investigate their effect on a crowd's ability to generate accurate judgments about societal problems. We argue that future work on societal problems can benefit from more sophisticated, domain-specific theory and models based on the wisdom of crowds.
Hohm I, Wormley AS, Schaller M
… +1 more, Varnum MEW
Perspect Psychol Sci
· 2024 Jan · PMID 37428561
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Many animal species exhibit seasonal changes in their physiology and behavior. Yet despite ample evidence that humans are also responsive to seasons, the impact of seasonal changes on human psychology is underappreciated...Many animal species exhibit seasonal changes in their physiology and behavior. Yet despite ample evidence that humans are also responsive to seasons, the impact of seasonal changes on human psychology is underappreciated relative to other sources of variation (e.g., personality, culture, development). This is unfortunate because seasonal variation has potentially profound conceptual, empirical, methodological, and practical implications. Here, we encourage a more systematic and comprehensive collective effort to document and understand the many ways in which seasons influence human psychology. We provide an illustrative summary of empirical evidence showing that seasons impact a wide range of affective, cognitive, and behavioral phenomena. We then articulate a conceptual framework that outlines a set of causal mechanisms through which seasons can influence human psychology-mechanisms that reflect seasonal changes not only in meteorological variables but also in ecological and sociocultural variables. This framework may be useful for integrating many different seasonal effects that have already been empirically documented and for generating new hypotheses about additional seasonal effects that have not yet received empirical attention. The article closes with a section that provides practical suggestions to facilitate greater appreciation for, and systematic study of, seasons as a fundamental source of variation in human psychology.