Perspectives on Psychological Science最新文献

Understanding language requires readers and listeners to cull meaning from fast-unfolding messages that often contain conflicting cues pointing to incompatible ways of interpreting the input (e.g., "The cat was chased by the mouse"). This article reviews mounting evidence from multiple methods demonstrating that cognitive control plays an essential role in resolving conflict during language comprehension. How does cognitive control accomplish this task? Psycholinguistic proposals have conspicuously failed to address this question. We introduce an account in which cognitive control aids language processing when cues conflict by sending top-down biasing signals that strengthen the interpretation supported by the most reliable evidence available. We also provide a computationally plausible model that solves the critical problem of how cognitive control "knows" which way to direct its biasing signal by allowing linguistic knowledge itself to issue crucial guidance. Such a mental architecture can explain a range of experimental findings, including how moment-to-moment shifts in cognitive-control state-its level of activity within a person-directly impact how quickly and successfully language comprehension is achieved.

Loneliness is an important health risk, which is why it is important to understand what can cause persistent or severe loneliness. Previous research has identified numerous personal or relational risk factors for loneliness. Cultural predictors, however, have been considered less. The new framework of norm deviations and loneliness (NoDeL) proposes that social norms, which are defining features of culture, can help explain loneliness within and across cultural contexts. Specifically, people who deviate from social norms are suggested to be at an increased risk for feeling lonely because they are more likely to experience alienation, inauthenticity, lower self-worth, social rejection, relationship dissatisfaction, and/or unfulfilled relational needs. Given that social norms vary by social, geographical, and temporal context, they can furthermore be considered cultural moderators between individual-level risk factors and loneliness: Personal or relational characteristics, such as shyness or being single, may increase the risk for loneliness particularly if they do not fit social norms in a specific environment. Integrating previous quantitative and qualitative findings, I hence offer a framework (NoDeL) to predict loneliness and cultural differences in risk factors for it. Thus, the NoDeL framework may help prepare culture-sensitive interventions against loneliness.

Many mechanisms of social bonding are common to all primates, but humans seemingly have developed some that are unique to the species. These involve various kinds of interactive experiences-from taking a walk together to having a conversation-whose common feature is the triadic sharing of experience. Current theories of social bonding have no explanation for why humans should have these unique bonding mechanisms. Here we propose a shared intentionality account of uniquely human social bonding. Humans evolved to participate with others in unique forms of cooperative and communicative activities that both depend on and create shared experience. Sharing experience in these activities causes partners to feel closer because it allows them to assess their partner's cooperative competence and motivation toward them and because the shared representations created during such interactions make subsequent cooperative interactions easier and more effective.

There is growing interest in the field of cooperative artificial intelligence (AI), that is, settings in which humans and machines cooperate. By now, more than 160 studies from various disciplines have reported on how people cooperate with machines in behavioral experiments. Our systematic review of the experimental instructions reveals that the implementation of the machine payoffs and the information participants receive about them differ drastically across these studies. In an online experiment (N = 1,198), we compare how these different payoff implementations shape people's revealed social preferences toward machines. When matched with machine partners, people reveal substantially stronger social preferences and reciprocity when they know that a human beneficiary receives the machine payoffs than when they know that no such "human behind the machine" exists. When participants are not informed about machine payoffs, we found weak social preferences toward machines. Comparing survey answers with those from a follow-up study (N = 150), we conclude that people form their beliefs about machine payoffs in a self-serving way. Thus, our results suggest that the extent to which humans cooperate with machines depends on the implementation and information about the machine's earnings.

Humans now understand the world as multilevel in nature. For example, societies emerge from individuals, and general experiences of life consist of specific aspects and momentary episodes. A critical feature of multilevel phenomena is between-level incongruences. Applied to human positivity, this means that positive higher-level units are not simply composed of positive lower-level units and that what is good for lower-level units may not be good for higher-level units (and vice versa). For example, killjoys may improve societal well-being, personal achievement may require giving up on certain goals, and a happy life may not arise from simply happy moments. In this article, I provide examples (organized by the positive outcome of well-being and performance and by the social, structural, and temporal forms of multilevel phenomena) to show that such between-level incongruences are ubiquitous. Next, I analyze a few mechanisms that may govern the diverse instantiations of between-level incongruences in positivity. Finally, I discuss implications of this perspective, such as why positivity claims should always qualify their level of analysis; how psychological science may benefit from a multilevel, dynamical, and computational perspective; and how to improve human positivity in light of between-level incongruences.

Political polarization is a barrier to enacting policy solutions to global issues. Social psychology has a rich history of studying polarization, and there is an important opportunity to define and refine its contributions to the present political realities. We do so in the context of one of the most pressing modern issues: climate change. We synthesize the literature on political polarization and its applications to climate change, and we propose lines of further research and intervention design. We focus on polarization in the United States, examining other countries when literature was available. The polarization literature emphasizes two types of mechanisms of political polarization: (1) individual-level psychological processes related to political ideology and (2) group-level psychological processes related to partisan identification. Interventions that address group-level processes can be more effective than those that address individual-level processes. Accordingly, we emphasize the promise of interventions leveraging superordinate identities, correcting misperceived norms, and having trusted leaders communicate about climate change. Behavioral interventions like these that are grounded in scientific research are one of our most promising tools to achieve the behavioral wedge that we need to address climate change and to make progress on other policy issues.

We propose an account of individual differences in risk preferences called "reference-point theory" for choices between sure things and gambles. Like most descriptive theories of risky choice, preferences depend on two drivers-hedonic sensitivities to change and beliefs about risk. But unlike most theories, these drivers are estimated from judged feelings about choice options and gamble outcomes. Furthermore, the reference point is assumed to be the less risky option (i.e., sure thing). Loss aversion (greater impact of negative change than positive change) and pessimism (belief the worst outcome is likelier) predict risk aversion. Gain seeking (greater impact of positive change than negative change and optimism (belief the best outcome is likelier) predict risk seeking. But other combinations of hedonic sensitivities and beliefs are possible, and they also predict risk preferences. Finally, feelings about the reference point predict hedonic sensitivities. When decision makers feel good about the reference point, they are frequently loss averse. When they feel bad about it, they are often gain seeking. Three studies show that feelings about reference points, feelings about options and feelings about outcomes predict risky choice and help explain why individuals differ in their risk preferences.

Embodied cognition-the idea that mental states and processes should be understood in relation to one's bodily constitution and interactions with the world-remains a controversial topic within cognitive science. Recently, however, increasing interest in predictive processing theories among proponents and critics of embodiment alike has raised hopes of a reconciliation. This article sets out to appraise the unificatory potential of predictive processing, focusing in particular on embodied formulations of active inference. Our analysis suggests that most active-inference accounts invoke weak, potentially trivial conceptions of embodiment; those making stronger claims do so independently of the theoretical commitments of the active-inference framework. We argue that a more compelling version of embodied active inference can be motivated by adopting a diachronic perspective on the way rhythmic physiological activity shapes neural development in utero. According to this visceral afferent training hypothesis, early-emerging physiological processes are essential not only for supporting the biophysical development of neural structures but also for configuring the cognitive architecture those structures entail. Focusing in particular on the cardiovascular system, we propose three candidate mechanisms through which visceral afferent training might operate: (a) activity-dependent neuronal development, (b) periodic signal modeling, and (c) oscillatory network coordination.

Suspicion probes are the traditional tool employed to assess the extent to which participants suspect intentional misdirection or deception within the research context. A primary reason psychologists use deception in research settings is to prevent participants from altering their behavior in light of knowing what is being studied, which could undermine internal validity as well as threaten the generalizability of findings to the real world (i.e., external validity). The present article elucidates a number of challenges with suspicion probes. A definition and framework for conceptualizing the construct of suspicion in research settings are proposed. Following a literature review, an analysis of existing evidence, and new data on the prevalence of using and reporting suspicion probes, we conclude that suspicion is a likely problem in research practice. We provide a decision guide to help researchers navigate the numerous choices involved in addressing potential suspicion and call for a combination of (a) renewed research leading to empirically supported tools and best practices and (b) systemic changes to editorial policies, funding practices, professional standards, and research training that would increase rigor and focus on this aspect of research methodology.

Faces are socially important surfaces of the body on which various meanings are attached. The widespread physiognomic belief that faces inherently contain socially predictive value is why they make a generative stimulus for perception research. However, critical problems arise in studies that simultaneously investigate faces and race. Researchers studying race and racism inadvertently engage in various research practices that transform faces with specific phenotypes into straightforward representatives of their presumed race category, thereby taking race and its phenotypic associations for granted. I argue that research practices that map race categories onto faces using bioessentialist ideas of racial phenotypes constitute a form of racecraft ideology, the dubious reasoning of which presupposes the reality of race and mystifies the causal relation between race and racism. In considering how to study racism without reifying race in face studies, this article places these practices in context, describes how they reproduce racecraft ideology and impair theoretical inferences, and then suggests counterpractices for minimizing this problem.