Perspect Psychol Sci
· 2024 Nov · PMID 37603076
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Human language permits us to call to mind objects, events, and ideas that we cannot witness directly, either because they are absent or because they have no physical form (e.g., people we have not met, concepts like just...Human language permits us to call to mind objects, events, and ideas that we cannot witness directly, either because they are absent or because they have no physical form (e.g., people we have not met, concepts like justice). What enables language to transmit such knowledge? We propose that a referential link between words, referents, and mental representations of those referents is key. This link enables us to form, access, and modify mental representations even when the referents themselves are absent ("absent reference"). In this review we consider the developmental and evolutionary origins of absent reference, integrating previously disparate literatures on absent reference in language and gesture in very young humans and gesture in nonhuman primates. We first evaluate when and how infants acquire absent reference during the process of language acquisition. With this as a foundation, we consider the evidence for absent reference in gesture in infants and in nonhuman primates. Finally, having woven these literatures together, we highlight new lines of research that promise to sharpen our understanding of the development of reference and its role in learning about the absent and the abstract.
Identifying successful approaches for reducing the belief and spread of online misinformation is of great importance. Social media companies currently rely largely on professional fact-checking as their primary mechanism...Identifying successful approaches for reducing the belief and spread of online misinformation is of great importance. Social media companies currently rely largely on professional fact-checking as their primary mechanism for identifying falsehoods. However, professional fact-checking has notable limitations regarding coverage and speed. In this article, we summarize research suggesting that the "wisdom of crowds" can be harnessed successfully to help identify misinformation at scale. Despite potential concerns about the abilities of laypeople to assess information quality, recent evidence demonstrates that aggregating judgments of groups of laypeople, or crowds, can effectively identify low-quality news sources and inaccurate news posts: Crowd ratings are strongly correlated with fact-checker ratings across a variety of studies using different designs, stimulus sets, and subject pools. We connect these experimental findings with recent attempts to deploy crowdsourced fact-checking in the field, and we close with recommendations and future directions for translating crowdsourced ratings into effective interventions.
History counts and cannot be overlooked. As a case in point, the origins of major theoretical tensions in the field of developmental psychology are traced back to Piaget (1896-1980), who paved the way to major discoverie...History counts and cannot be overlooked. As a case in point, the origins of major theoretical tensions in the field of developmental psychology are traced back to Piaget (1896-1980), who paved the way to major discoveries regarding the origins and development of cognition. His theory framed much of the new ideas on early cognitive development that emerged in the 1970s, in the footsteps of the 1960s' cognitive revolution. Here, I retrace major conceptual changes since Piaget and provide a metaview on empirical findings that may have triggered the call for such changes. Nine theoretical views and intuitions are identified, all in strong reaction to some or all of the four cornerstone assumptions of Piaget's developmental account (i.e., action realism, domain generality, stages, and late representation). As a result, new and more extreme stances are now taken in the nature-versus-nurture debate. These stances rest on profoundly different, often clashing theoretical intuitions that keep shaping developmental research since Piaget.
In the past decade, various recommendations have been published to enhance the methodological rigor and publication standards in psychological science. However, adhering to these recommendations may have limited impact o...In the past decade, various recommendations have been published to enhance the methodological rigor and publication standards in psychological science. However, adhering to these recommendations may have limited impact on the reproducibility of causal effects as long as psychological phenomena continue to be viewed as decomposable into separate and additive statistical structures of causal relationships. In this article, we show that (a) psychological phenomena are patterns emerging from nondecomposable and nonisolable complex processes that obey idiosyncratic nonlinear dynamics, (b) these processual features jeopardize the chances of standard reproducibility of statistical results, and (c) these features call on researchers to reconsider what can and should be reproduced, that is, the psychological processes per se, and the signatures of their complexity and dynamics. Accordingly, we argue for a greater consideration of of psychological phenomena reflected by key properties of complex dynamical systems (CDSs). This implies developing and testing formal models of psychological dynamics, which can be implemented by computer simulation. The scope of the CDS paradigm and its convergences with other paradigms are discussed regarding the reproducibility issue. Ironically, the CDS approach could account for reproducibility and nonreproducibility of the statistical effects usually sought in mainstream psychological science.
Lehmann K, Bolis D, Friston KJ
… +3 more, Schilbach L, Ramstead MJD, Kanske P
Perspect Psychol Sci
· 2024 Nov · PMID 37565656
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Social neuroscience has often been criticized for approaching the investigation of the neural processes that enable social interaction and cognition from a passive, detached, third-person perspective, without involving a...Social neuroscience has often been criticized for approaching the investigation of the neural processes that enable social interaction and cognition from a passive, detached, third-person perspective, without involving any real-time social interaction. With the emergence of , investigators have uncovered the unique complexity of neural-activation patterns in actual, real-time interaction. Social cognition that occurs during social interaction is fundamentally different from that unfolding during social observation. However, it remains unclear how the neural correlates of social interaction are to be interpreted. Here, we leverage the active-inference framework to shed light on the mechanisms at play during social interaction in second-person neuroscience studies. Specifically, we show how counterfactually rich mutual predictions, real-time bodily adaptation, and policy selection explain activation in components of the default mode, salience, and frontoparietal networks of the brain, as well as in the basal ganglia. We further argue that these processes constitute the crucial neural processes that underwrite bona fide social interaction. By placing the experimental approach of second-person neuroscience on the theoretical foundation of the active-inference framework, we inform the field of social neuroscience about the mechanisms of real-life interactions. We thereby contribute to the theoretical foundations of empirical second-person neuroscience.
The community-of-knowledge framework explains the extraordinary success of the human species, despite individual members' demonstrably shallow understanding of many topics, by appealing to outsourcing. People follow the...The community-of-knowledge framework explains the extraordinary success of the human species, despite individual members' demonstrably shallow understanding of many topics, by appealing to outsourcing. People follow the cues of members of their community because understanding of phenomena is generally distributed across the group. Typically, communities do possess the relevant knowledge, but it is possible in principle for communities to send cues despite lacking knowledge-a weakness in the system's design. COVID-19 in the United States offered a natural experiment in collective-knowledge development because a novel phenomenon arrived at a moment of intense division in political partisanship. We review evidence from the pandemic showing that the thought leaders of the two partisan groups sent radically different messages about COVID, which were, in turn, reinforced by close community members (family, friends, etc.). We show that although actual understanding of the individual plays a role in a key COVID-mitigation behavior (vaccination), it plays a smaller role than perceived understanding of thought leaders and beliefs about COVID-related behaviors of close community members. We discuss implications for theory and practice when all communities are in the same epistemic circumstance-relying on the testimony of others.
Achieving global sustainability in the face of climate change, pandemics, and other global systemic threats will require collective intelligence and collective action beyond what we are currently experiencing. Increasing...Achieving global sustainability in the face of climate change, pandemics, and other global systemic threats will require collective intelligence and collective action beyond what we are currently experiencing. Increasing polarization within nations and populist trends that undercut international cooperation make the problem even harder. Allegiance within groups is often strengthened because of conflict among groups, leading to a form of polarization termed "affective." Hope for addressing these global problems will require recognition of the commonality in threats facing all groups collective intelligence that integrates relevant inputs from all sources but fights misinformation and coordinated, cooperative collective action. Elinor Ostrom's notion of polycentric governance, involving centers of decision-making from the local to the global in a complex interacting framework, may provide a possible pathway to achieve these goals.
Warren WH, Falandays JB, Yoshida K
… +2 more, Wirth TD, Free BA
Perspect Psychol Sci
· 2024 Mar · PMID 37526132
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A ubiquitous type of collective behavior and decision-making is the coordinated motion of bird flocks, fish schools, and human crowds. Collective decisions to move in the same direction, turn right or left, or split into...A ubiquitous type of collective behavior and decision-making is the coordinated motion of bird flocks, fish schools, and human crowds. Collective decisions to move in the same direction, turn right or left, or split into subgroups arise in a self-organized fashion from local interactions between individuals without central plans or designated leaders. Strikingly similar phenomena of consensus (collective motion), clustering (subgroup formation), and bipolarization (splitting into extreme groups) are also observed in opinion formation. As we developed models of crowd dynamics and analyzed crowd networks, we found ourselves going down the same path as models of opinion dynamics in social networks. In this article, we draw out the parallels between human crowds and social networks. We show that models of crowd dynamics and opinion dynamics have a similar mathematical form and generate analogous phenomena in multiagent simulations. We suggest that they can be unified by a common collective dynamics, which may be extended to other psychological collectives. Models of collective dynamics thus offer a means to account for collective behavior and collective decisions without appealing to a priori mental structures.
Tiokhin L, Panchanathan K, Smaldino PE
… +1 more, Lakens D
Perspect Psychol Sci
· 2024 Nov · PMID 37526118
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Criteria for recognizing and rewarding scientists primarily focus on individual contributions. This creates a conflict between what is best for scientists' careers and what is best for science. In this article, we show h...Criteria for recognizing and rewarding scientists primarily focus on individual contributions. This creates a conflict between what is best for scientists' careers and what is best for science. In this article, we show how the theory of multilevel selection provides conceptual tools for modifying incentives to better align individual and collective interests. A core principle is the need to account for indirect effects by shifting the level at which selection operates from individuals to the groups in which individuals are embedded. This principle is used in several fields to improve collective outcomes, including animal husbandry, team sports, and professional organizations. Shifting the level of selection has the potential to ameliorate several problems in contemporary science, including accounting for scientists' diverse contributions to knowledge generation, reducing individual-level competition, and promoting specialization and team science. We discuss the difficulties associated with shifting the level of selection and outline directions for future development in this domain.
Perspect Psychol Sci
· 2024 Sep · PMID 37522323
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Psychological artificial intelligence (AI) applies insights from psychology to design computer algorithms. Its core domain is decision-making under uncertainty, that is, ill-defined situations that can change in unexpect...Psychological artificial intelligence (AI) applies insights from psychology to design computer algorithms. Its core domain is decision-making under uncertainty, that is, ill-defined situations that can change in unexpected ways rather than well-defined, stable problems, such as chess and Go. Psychological theories about heuristic processes under uncertainty can provide possible insights. I provide two illustrations. The first shows how recency-the human tendency to rely on the most recent information and ignore base rates-can be built into a simple algorithm that predicts the flu substantially better than did Google Flu Trends's big-data algorithms. The second uses a result from memory research-the paradoxical effect that making numbers less precise increases recall-in the design of algorithms that predict recidivism. These case studies provide an existence proof that psychological AI can help design efficient and transparent algorithms.
Perspect Psychol Sci
· 2024 Jan · PMID 37506338
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Norms are the rules about what is allowed or forbidden by social groups. A key debate for norm psychology is whether these rules arise from mechanisms that are domain-specific and genetically inherited or domain-general...Norms are the rules about what is allowed or forbidden by social groups. A key debate for norm psychology is whether these rules arise from mechanisms that are domain-specific and genetically inherited or domain-general and deployed for many other nonnorm processes. Here we argue for the importance of assessing and testing domain-specific and domain-general processes at multiple levels of explanation, from algorithmic (psychological) to implementational (neural). We also critically discuss findings from cognitive neuroscience supporting that social and nonsocial learning processes, essential for accounts of cultural evolution, can be dissociated at these two levels. This multilevel framework can generate new hypotheses and empirical tests of cultural evolution accounts of norm processing against purely domain-specific nativist alternatives.