Consider the following two (hypothetical) generic causal claims: “Living in a neighborhood with many families with children increases purchases of bicycles” and “living in an affluent neighborhood with many families with children increases purchases of bicycles.” These claims not only differ in what they suggest about how bicycle ownership is distributed across different neighborhoods (i.e., “the data”), but also have the potential to communicate something about the speakers’ values: namely, the prominence they accord to affluence in representing and making decisions about the social world. Here, we examine the relationship between the level of granularity with which a cause is described in a generic causal claim (e.g., neighborhood vs. affluent neighborhood) and the value of the information contained in the causal model that generates that claim. We argue that listeners who know any two of the following can make reliable inferences about the third: 1) the level of granularity at which a speaker makes a generic causal claim, 2) the speaker’s values, and 3) the data available to the speaker. We present results of four experiments (N = 1323) in the domain of social categories that provide evidence in keeping with these predictions.

To make sense of the social world, people reason about others’ mental states, including whether and in what ways others can form new mental states. We propose that people’s judgments concerning the dynamics of mental state change invoke a “naive theory of reasoning.” On this theory, people conceptualize reasoning as a rational, semi-autonomous process that individuals can leverage, but not override, to form new rational mental states. Across six experiments, we show that this account of people’s naive theory of reasoning predicts judgments about others’ ability to form rational and irrational beliefs, desires, and intentions, as well as others’ ability to act rationally and irrationally. This account predicts when, and explains why, people judge others as psychologically constrained by coercion and other forms of situational pressure.

Decisions about how to divide resources have profound social and practical consequences. Do explanations regarding the source of existing inequalities influence how children and adults allocate new resources? When 3-6-year-old children (N=201) learned that inequalities were caused by structural forces (stable external constraints affecting access to resources) as opposed to internal forces (effort), they rectified inequalities, overriding previously-documented tendencies to perpetuate inequality or divide resources equally. Adults (N=201) were more likely than children to rectify inequality spontaneously; this was further strengthened by a structural explanation but reversed by an effort-based explanation. Allocation behaviors were mirrored in judgments of which allocation choices by others were appropriate. These findings reveal how explanations powerfully guide social reasoning and action from childhood through adulthood.

People often engage in biased reasoning, favoring some beliefs over others even when the result is a departure from impartial or evidence-based reasoning. Psychologists have long assumed that people are unaware of these biases and operate under an “illusion of objectivity.” We identify an important domain of life in which people harbor little illusion about their biases – when they are biased for moral reasons. For instance, people endorse and feel justified believing morally desirable propositions even when they think they lack evidence for them (Study 1a/1b). Moreover, when people engage in morally desirable motivated reasoning, they recognize the influence of moral biases on their judgment, but nevertheless evaluate their reasoning as ideal (Studies 2–4). These findings overturn longstanding assumptions about motivated reasoning and identify a boundary condition on Naïve Realism and the Bias Blind Spot. People’s tendency to be aware and proud of their biases provides both new opportunities, and new challenges, for resolving ideological conflict and improving reasoning.

Who is more committed to science: the person who learns about a scientific consensus and doesn’t ask questions, or the person who learns about a scientific consensus and decides to pursue further inquiry? Who exhibits greater commitment to religious teachings: the person who accepts doctrine without question, or the person who seeks further evidence and explanations? Across three experiments (N = 801) we investigate the inferences drawn about an individual on the basis of their epistemic behavior – in particular, their decision to pursue or forgo further inquiry (evidence or explanation) about scientific or religious claims. We find that the decision to pursue further inquiry (about science or religion) is taken to signal greater commitment to science and to truth, as well as trustworthiness and good moral character (Studies 1-3). This is true even in the case of claims regarding controversial science topics, such as anthropogenic climate change (Study 3). In contrast, the decision to forgo further inquiry is taken to signal greater commitment to religion, but only when the claim under consideration contains religious content (Study 1-3). These findings shed light on perceived scientific and religious norms in our predominantly American and Christian sample, as well as the rich social inferences drawn on the basis of epistemic behavior.

Curiosity plays a key role in directing learning throughout the lifespan. Prior work finds that violations of expectations can be powerful triggers of curiosity in both children and adults, but it is unclear which expectation-violating events induce the greatest curiosity and how this might vary over development. Some theories have suggested a U-shaped function such that stimuli of moderate extremity pique the greatest curiosity. However, expectation-violations vary not only in degree, but in kind: for example, some things violate an intuitive theory (e.g., an alligator that can talk) and others are merely unlikely (e.g., an alligator hiding under your bed). Combining research on curiosity with distinctions posited in the cognitive science of religion, we test whether minimally counterintuitive (MCI) stimuli, which involve one violation of an intuitive theory, are especially effective at triggering curiosity. We presented adults (N = 77) and 4- and 5-year-olds (N = 36) in the United States with stimuli that were ordinary, unlikely, MCI, and very counterintuitive (VCI) and asked which one they would like to learn more about. Adults and 5-year-olds chose Unlikely over Ordinary and MCI over Unlikely, but not VCI over MCI, more often than chance. Our results suggest that (i) minimally counterintuitive stimuli trigger greater curiosity than merely unlikely stimuli, (ii) surprisingness has diminishing returns, and (iii) sensitivity to surprisingness increases with age, appearing in our task by age 5.

Adults in prior work often endorse explanations appealing to purposes (e.g., “pencils exist so people can write with them”), even when these ‘teleological’ explanations are scientifically unwarranted (e.g., “water exists so life can survive on Earth”). We explore teleological endorsement in a novel domain—human purpose—and its relationship to moral judgments. Across studies conducted online with a sample of US-recruited adults, we ask: (1) Do participants believe the human species exists for a purpose? (2) Do these beliefs predict moral condemnation of individuals who fail to fulfill this purpose? And (3) what explains the link between teleological beliefs and moral condemnation? Study 1 found that participants frequently endorsed teleological claims about humans existence (e.g., humans exist to procreate), and these beliefs correlated with moral condemnation of purpose violations (e.g., condemning those who do not procreate). Study 2 found evidence of a bi-directional causal relationship: stipulating a species’ purpose results in moral condemnation of purpose violations, and stipulating that an action is immoral increases endorsement that the species exists for that purpose. Study 3 found evidence that when participants believe a species exists to perform some action, they infer this action is good for the species, and this in turn supports moral condemnation of individuals who choose not to perform the action. Study 4 found evidence that believing an action is good for the species partially mediates the relationship between human purpose beliefs and moral condemnation. These findings shed light on how our descriptive understanding can shape our prescriptive judgments.

Humans are avid explainers: we ask “why?” and derive satisfaction from a good answer. But humans are also selective explainers: only some observations prompt us to ask “why?”, and only some answers are satisfying. This article reviews recent work on selectivity in explanation-seeking curiosity and explanatory satisfaction, with a focus on how this selectivity makes us effective learners in a complex world. Research finds that curiosity about the answer to a why-question is stronger when it is expected to yield useful learning, and that explanations are judged more satisfying when they are perceived to support useful learning. While such perceptions are imperfect, there is nonetheless evidence that seeking and evaluating explanations – in the selective way humans do – can play an important role in learning.

A growing body of research suggests that scientific and religious beliefs are often held and justified in different ways. In three studies with 707 participants, we examine the distinctive profiles of beliefs in these domains. In Study 1, we find that participants report evidence and explanatory considerations (making sense of things) as dominant reasons for beliefs across domains. However, cuing the religious domain elevates endorsement of non-scientific justifications for belief, such as ethical considerations (e.g., believing it encourages people to be good), affiliation (what loved ones believe) and intuition (what feels true in one’s heart). Study 2 replicates these differences with specific scientific and religious beliefs held with equal confidence, and documents further domain differences in beliefs’ personal importance, openness to revision, and perceived objectivity. Study 3 replicates these differences, further finding that counter-consensus beliefs about contentious science topics (such as climate change and vaccination) often have properties resembling religious beliefs, while counter-religious beliefs about religion (e.g. “There is no God”) have properties that more closely resemble beliefs about science. We suggest that beliefs are held and justified within coherent epistemic frameworks, with individuals using different frameworks in different contexts and domains.

What changes people’s judgments on moral issues, such as the ethics of abortion or eating meat? On some views, moral judgments result from deliberation, such that reasons and reasoning should be primary drivers of moral change. On other views, moral judgments reflect intuition, with reasons offered as post-hoc rationalizations. We test predictions of these accounts by investigating whether exposure to a moral philosophy course (vs. control courses) changes moral judgments, and if so, via what mechanism(s). In line with deliberative accounts of morality, we find that exposure to moral philosophy changes moral views. In line with intuitionist accounts, we find that the mechanism of change is reduced reliance on intuition, not increased reliance on deliberation; in fact, deliberation is related to increased confidence in judgments, not change. These findings suggest a new way to reconcile deliberative and intuitionist accounts: Exposure to reasons and evidence can change moral views, but primarily by discounting intuitions.

Scientific and religious explanations often coexist in the sense that they are both endorsed by the same individuals, and they are sometimes conjoined such that a single explanation draws upon both scientific and religious components. In this chapter we consider the psychology of such explanations, drawing upon recent research in cognitive and social psychology. We argue that scientific and religious explanations often serve different psychological functions, with scientific explanations seen as better serving epistemic functions (such as supporting accurate models of the world), and religious explanations seen as better serving non-epistemic functions (such as offering emotional comfort or supporting moral behavior). This functional differentiation points to a potential benefit of conjunctive explanations: by fulfilling multiple psychological functions, they will sometimes satisfy a broader range of explanatory goals. Generalizing from the case of science and religion, we suggest that conjunctive explanations may be especially appealing when a given explanatory framework faces tradeoffs between different explanatory goals (such as generality versus precision), resulting in an advantage to explanations that draw upon multiple explanatory frameworks instantiating different tradeoffs.

Abstract The notion of belief appears frequently in cognitive science. Yet it has resisted definition of the sort that could clarify inquiry. How then might a cognitive science of belief proceed? Here we propose a form of pluralism about believing. According to this view, there are importantly different ways to believe an idea. These distinct psychological kinds occur within a multi-dimensional property space, with different property clusters within that space constituting distinct varieties of believing. We propose that discovering such property clusters is empirically tractable, and that this approach can help sidestep merely verbal disputes about what constitutes “belief.”

Intuitions play an important role in the debate on the causal status of high-level properties. For instance, Kim has claimed that his “exclusion argument” relies on “a perfectly intuitive ... understanding of the causal relation.” We report the results of three experiments examining whether laypeople really have the relevant intuitions. We find little support for Kim's view and the principles on which it relies. Instead, we find that laypeople are willing to count both a multiply realized property and its realizers as causes, and regard the systematic overdetermination implied by this view as unproblematic.

Identifying abstract relations is essential for commonsense reasoning. Research suggests that even young children can infer relations such as “same” and “different,” but often fail to apply these concepts. Might the process of explaining facilitate the recognition and application of relational concepts? Based on prior work suggesting that explanation can be a powerful tool to promote abstract reasoning, we predicted that children would be more likely to discover and use an abstract relational rule when they were prompted to explain observations instantiating that rule, compared to when they received demonstration alone. Five- and 6-year-olds were given a modified Relational Match to Sample (RMTS) task, with repeated demonstrations of relational (same) matches by an adult. Half of the children were prompted to explain these matches; the other half reported the match they observed. Children who were prompted to explain showed immediate, stable success, while those only asked to report the outcome of the pedagogical demonstration did not. Findings provide evidence that explanation facilitates early abstraction over and above demonstration alone.

How did the universe come to exist? What happens after we die? Answers to existential questions tend to elicit both scientific and religious explanations, offering a unique opportunity to evaluate how these domains differ in their psychological roles. Across 3 studies (N = 1,647), we investigate whether (and by whom) scientific and religious explanations are perceived to have epistemic merits—such as evidential and logical support—versus nonepistemic merits—such as social, emotional, or moral benefits. We find that scientific explanations are attributed more epistemic merits than are religious explanations (Study 1), that an explanation’s perceived epistemic merits are more strongly predicted by endorsement of that explanation for science than for religion (Study 2), and that scientific explanations are more likely to be generated when participants are prompted for an explanation high in epistemic merits (Study 3). By contrast, we find that religious explanations are attributed more nonepistemic merits than are scientific explanations (Study 1), that an explanation’s perceived nonepistemic merits are more strongly predicted by endorsement of that explanation for religion than for science (Study 2), and that religious explanations are more likely to be generated when participants are prompted for an explanation high in nonepistemic merits (Study 3). These findings inform theories of the relationship between religion and science, and they provide insight into accounts of the coexistence of scientific and religious cognition. (PsycInfo Database Record (c) 2021 APA, all rights reserved)

How and why does the moon cause the tides? How and why does God answer prayers? For many, the answer to the former question is unknown; the answer to the latter question is a mystery. Across three studies testing a largely Christian sample within the United States (N = 2,524), we investigate attitudes towards ignorance and inquiry as a window onto scientific versus religious belief. In Experiment 1, we find that science and religion are associated with different forms of ignorance: scientific ignorance is typically expressed as a personal unknown (“it’s unknown to me”), whereas religious ignorance is expressed as a universal mystery (“it’s a mystery”), with scientific unknowns additionally regarded as more viable and valuable targets for inquiry. In Experiment 2, we show that these forms of ignorance are differentially associated with epistemic goals and norms: expressing ignorance in the form of “unknown” (versus “mystery”) more strongly signals epistemic values and achievements. Experiments 2 and 3 additionally show that ignorance is perceived to be a greater threat to science and scientific belief than to religion and religious belief. Together, these studies shed light on the psychological roles of scientific and religious belief in human cognition.

Curiosity is considered essential for learning and sustained engagement, yet stimulating curiosity in educational contexts remains a challenge. Can people’s curiosity about a scientific topic be stimulated by providing evidence that knowledge about the topic has potential value to society? Here, we show that increasing perceptions of ‘social usefulness’ regarding a scientific topic also increases curiosity and subsequent information search. Our results also show that simply presenting interesting facts is not enough to influence curiosity, and that people are more likely to be curious about a scientific topic if they perceive it to be useful personally and socially. Given the link between curiosity and learning, these results have important implications for science communication and education more broadly.

Do people attribute functions to gendered social categories? (For instance, is there something men or mothers are for?) And if so, do such attributions of function have consequences for normative judgments about what members of these social categories ought to do? In the current study, participants (N = 366) rated their agreement with 15 statements about the “true functions” of different social categories, in triads of matched masculine, feminine, and superordinate categories (e.g., fathers, mothers, and parents). Participants endorsed functional claims more for some social categories (e.g., parents) than others (e.g., kids), and their background beliefs about gender predicted variation in functional reasoning. However, across categories, participants judged that fulfilling true functions was ‘natural’ for members of the category, and they judged that category members ought to fulfill their true functions.

Knowing which features are frequent among a biological kind (e.g., that most zebras have stripes) shapes people’s representations of what category members are like (e.g., that typical zebras have stripes) and normative judgments about what they ought to be like (e.g., that zebras should have stripes). In the current work, we ask if people’s inclination to explain why features are frequent is a key mechanism through which what “is” shapes beliefs about what “ought” to be. Across four studies (N = 591), we find that frequent features are often explained by appeal to feature function (e.g., that stripes are for camouflage), that functional explanations in turn shape judgments of typicality, and that functional explanations and typicality both predict normative judgments that category members ought to have functional features. We also identify the causal assumptions that license inferences from feature frequency and function, as well as the nature of the normative inferences that are drawn: by specifying an instrumental goal (e.g., camouflage), functional explanations establish a basis for normative evaluation. These findings shed light on how and why our representations of how the natural world is shape our judgments of how it ought to be.

The same causal system can be accurately described in many ways. What governs the evaluation of these choices? We pro- pose a novel, formal account of causal evaluation according to which evaluations of causal claims reflect the joint demands of maximal informativeness and maximal compression. Across two experiments, we show that evaluations of more and less compressed causal claims are sensitive to the amount of information lost by choosing the more compressed causal claim over a less compressed one, regardless of whether the com- pression is realized by coarsening a single variable or by eliding a background condition. This offers a unified account of two dimensions along which causal claims are evaluated (proportionality and stability), and contributes to a more general picture of human cognition according to which the capacity to create compressed (causal) representations plays a central role.

“Slavery ended in the United States because slavery is morally wrong.” This explanation does not seem to fit the typical criteria for explaining an event, since it appeals to ethics rather than causal factors as the reason for this social change. But do people perceive these ethical claims as explanatory, and if so, why? In Study 1, we find that people accept ethical explanations for social change and that this is predicted by their meta-ethical beliefs in moral progress and moral objectivism, suggesting that they treat morality somewhat akin to a causal force. In Study 2, we find that people recognize this relationship between ethical explanations and meta-ethical commitments, using the former to make inferences about individuals’ beliefs in moral progress and objectivism. Together these studies demonstrate that our moral commitments shape our judgments of explanations and that explanations shape our moral inferences about others.

Many explanations have a distinctive, positive phenomenology: receiving or generating these explanations feels satisfying. Accordingly, we might expect this feeling of explanatory satisfaction to reinforce and motivate inquiry. Across five studies, we investigate how explanatory satisfaction plays this role: by motivating and reinforcing inquiry quite generally (“brute motivation” account), or by selectively guiding inquiry to support useful learning about the target of explanation (“aligned motivation” account). In Studies 1–2, we find that satisfaction with an explanation is related to several measures of perceived useful learning, and that greater satisfaction in turn predicts stronger curiosity about questions related to the explanation. However, in Studies 2–4, we find only tenuous evidence that satisfaction is related to actual learning, measured objectively through multiple-choice or free recall tests. In Study 4, we additionally show that perceptions of learning fully explain one seemingly specious feature of explanatory preferences studied in prior research: the preference for uninformative “reductive” explanations. Finally, in Study 5, we find that perceived learning is (at least in part) causally responsible for feelings of satisfaction. Together, these results point to what we call the “imperfectly aligned motivation” account: explanatory satisfaction selectively motivates inquiry towards learning explanatory information, but primarily through fallible perceptions of learning. Thus, satisfaction is likely to guide individuals towards lines of inquiry that support perceptions of learning, whether or not individuals actually are learning.

Deliberative analysis enables us to weigh features, simulate futures, and arrive at good, tractable decisions. So why do we so often eschew deliberation, and instead rely on more intuitive, gut responses? We propose that intuition might be prescribed for some decisions because people’s folk theory of decision-making accords a special role to authenticity, which is associated with intuitive choice. Five pre-registered experiments find evidence in favor of this claim. In Experiment 1 (N = 654), we show that participants prescribe intuition and deliberation as a basis for decisions differentially across domains, and that these prescriptions predict reported choice. In Experiment 2 (N = 555), we find that choosing intuitively vs. deliberately leads to different inferences concerning the decision-maker’s commitment and authenticity—with only inferences about the decision-maker’s authenticity showing variation across domains that matches that observed for the prescription of intuition in Experiment 1. In Experiment 3 (N = 631), we replicate our prior results and rule out plausible confounds. Finally, in Experiment 4 (N = 177) and Experiment 5 (N = 526), we find that an experimental manipulation of the importance of authenticity affects the prescribed role for intuition as well as the endorsement of expert human or algorithmic advice. These effects hold beyond previously recognized influences on intuitive vs. deliberative choice, such as computational costs, presumed reliability, objectivity, complexity, and expertise.

People have a remarkable ability to remain steadfast in their beliefs in the face of large-scale disagreement. This has important consequences (e.g., societal polarization), yet its psychological underpinnings are poorly understood. In this paper, we answer foundational questions regarding belief persistence, from its prevalence to variability. Across two Experiments (N = 356, N = 354), we find that participants are aware of societal disagreement about controversial issues, yet overwhelmingly (~85%) do not question their views if asked to reflect on this disagreement. Both studies provide evidence that explanations for persistence vary across domains, with epistemic and meta-epistemic explanations among the most prevalent.

Explanations highlight inductively rich relationships that support further generalizations: if a knife is sharp because it is for cutting, we can infer that other things for cutting might also be sharp. Do children see explanations as good guides to generalization? We asked 108 4- to 7-year-old children to evaluate mechanistic, functional, and categorical explanations of object properties, and to generalize those properties to novel objects on the basis of shared mechanisms, functions, or category membership. Children were significantly more likely to generalize when the explanation they had received matched the subsequent basis for generalization (e.g., generalizing on the basis of a shared mechanism after hearing a mechanistic explanation). This effect appeared to be driven by older children. Explanation-to-generalization coordination also appeared to vary across relationships, mirroring the development of corresponding explanatory preferences. These findings fill an important gap in our understanding of how explanations guide young children’s generalization and learning.

Are causal explanations (e.g., “she switched careers because of the COVID pandemic”) treated differently from the corresponding claims that one factor caused another (e.g., “the COVID pandemic caused her to switch careers”)? We examined whether explanatory and causal claims diverge in their responsiveness to two different types of information: covariation strength and mechanism information. We report five experiments with 1,730 participants total, showing that compared to judgments of causal strength, explanatory judgments tend to be more sensitive to mechanism and less sensitive to covariation – even though explanatory judgments respond to both types of information. We also report exploratory comparisons to judgments of understanding, and discuss implications of our findings for theories of explanation, understanding, and causal attribution. These findings shed light on the potentially unique role of explanation in cognition.

People often face the challenge of evaluating competing explanations. One approach is to assess the explanations’ relative probabilities – e.g., applying Bayesian inference to compute their posterior probabilities. Another approach is to consider an explanation’s qualities or ‘virtues’, such as its relative simplicity (i.e., the number of unexplained causes it invokes). The current work investigates how these two approaches are related. Study 1 found that simplicity is used to infer the inputs to Bayesian inference (explanations’ priors and likelihoods). Studies 1 and 2 found that simplicity is also used as a direct cue to the outputs of Bayesian inference (the posterior probability of an explanation), such that simplicity affects estimates of posterior probability even after controlling for elicited (Study 1) or provided (Study 2) priors and likelihoods, with simplicity having a larger effect in Study 1, where posteriors are more uncertain and difficult to compute. Comparing Studies 1 and 2 also suggested that simplicity plays additional roles unrelated to approximating probabilities, as reflected in simplicity’s effect on how ‘satisfying’ (vs. probable) an explanation is, which remained largely unaffected by the difficulty of computing posteriors. Together, these results suggest that the virtue of simplicity is used in multiple ways to approximate probabilities (i.e., serving as a cue to priors, likelihoods, and posteriors) when these probabilities are otherwise uncertain or difficult to compute, but that the influence of simplicity also goes beyond these roles.

Scientific reasoning is characterized by commitments to evidence and objectivity. New research suggests that under some conditions, people are prone to reject these commitments, and instead sanction motivated reasoning and bias. Moreover, people’s tendency to devalue scientific reasoning likely explains the emergence and persistence of many biased beliefs. However, recent work in epistemology has identified ways in which bias might be legitimately incorporated into belief formation. Researchers can leverage these insights to evaluate when commonsense affirmation of bias is justified and when it is unjustified and therefore a good target for intervention. Making reasoning more scientific may require more than merely teaching people what constitutes scientific reasoning; it may require affirming the value of such reasoning in the first place.

When faced with a dilemma between believing what is supported by an impartial assessment of the evidence (e.g., that one's friend is guilty of a crime) and believing what would better fulfill a moral obligation (e.g., that the friend is innocent), people often believe in line with the latter. But is this how people think beliefs ought to be formed? We addressed this question across three studies and found that, across a diverse set of everyday situations, people treat moral considerations as legitimate grounds for believing propositions that are unsupported by objective, evidence-based reasoning. We further document two ways in which moral considerations affect how people evaluate others' beliefs. First, the moral value of a belief affects the evidential threshold required to believe, such that morally beneficial beliefs demand less evidence than morally risky beliefs. Second, people sometimes treat the moral value of a belief as an independent justification for belief, and on that basis, sometimes prescribe evidentially poor beliefs to others. Together these results show that, in the folk ethics of belief, morality can justify and demand motivated reasoning.

In the face of strong evidence that a coin landed heads, can someone simply choose to believe it landed tails? Knowing that a large earthquake could result in personal tragedy, can someone simply choose to desire that it occur? We propose that in the face of strong reasons to adopt a given belief or desire, people are perceived to lack control: they cannot simply believe or desire otherwise. We test this “reason-based constraint” account of mental state change, and find that people reliably judge that evidence constrains belief formation, and utility constrains desire formation, in others. These results were not explained by a heuristic that simply treats irrational mental states as impossible to adopt intentionally. Rather, constraint results from the perceived influence of reasons on reasoning: people judge others as free to adopt irrational attitudes through actions that eliminate their awareness of strong reasons. These findings fill an important gap in our understanding of folk psychological reasoning, with implications for attributions of autonomy and moral responsibility.

Our actions and decisions are regularly influenced by the social environment around us. Can socialcues be leveraged to induce curiosity and affect subsequent behavior? Across two experiments, we show that curiosity is contagious: the social environment can influence people’s curiosity about the answers to scientific questions. Participants were presented with everyday questions about science from a popular on-line forum, and these were shown with a high or low number of up-votes as a social cue to popularity. Participants indicated their curiosity about the answers, and they were given an opportunity to reveal a subset of those answers. Participants reported greater curiosity about the answers to questions when the questions were presented with a high (vs. low) number of up-votes, and they were also more likely to choose to reveal the answers to questions with a high (vs. low) number of up-votes. These effects were partially mediated by surprise and by the inferredusefulness of knowledge, with a more dramatic effect of low up-votes in reducing curiosity than of high up-votes in boosting curiosity. Taken together, these results highlight the important role social information plays in shaping our curiosity.

Folk-biological concepts are sensitive to both statistical information about feature prevalence (Hampton, 1995; Kim & Murphy, 2011; Rosch & Mervis, 1975) and teleological beliefs about function (Atran, 1995; Keil, 1994; Kelemen, Rottman, & Seston, 2013; Lombrozo & Rehder, 2012), but it is unknown how these two types of information interact to shape concepts. In three studies (N = 438) using novel animal kinds, we found that information about prevalence and teleology inform each other: People assume that common features are functional, and they assume that functional features are common. However, people use teleological information to predict the future distribution of features across the category, despite conflicting information about current prevalence. Thus, both information about prevalence and teleological beliefs serve important conceptual functions: Prevalence information encodes the current state of the category, while teleological functions provides a means of predicting future category change.

There has been extensive discussion about gender gaps in representation and career advancement in the sciences. However, psychological science itself has yet to be the focus of discussion or systematic review, despite our field’s investment in questions of equity, status, well-being, gender bias, and gender disparities. In the present article, we consider 10 topics relevant for women’s career advancement in psychological science. We focus on issues that have been the subject of empirical study, discuss relevant evidence within and outside of psychological science, and draw on established psychological theory and social-science research to begin to chart a path forward. We hope that better understanding of these issues within the field will shed light on areas of existing gender gaps in the discipline and areas where positive change has happened, and spark conversation within our field about how to create lasting change to mitigate remaining gender differences in psychological science.

People often endorse explanations that appeal to purpose, even when these ‘teleological’ explanations are scientifically unwarranted (e.g., “water exists so that life can survive on Earth”). In the present research, we explore teleological endorsement in a novel domain—human purpose—and its relationship to moral judgments. Across four studies, we address three questions: (1) Do people believe the human species exists for a purpose? (2) Do these beliefs drive moral condemnation of individuals who fail to fulfill this purpose? And if so, (3) what explains the link between teleological beliefs and moral condemnation? Study 1 (N=188) found that many adults endorsed anthropic teleology (e.g., that humans exist in order to procreate), and that these beliefs correlated with moral condemnation of purpose violations (e.g., judging those who do not procreate immoral). Study 2 (N=199) found evidence of a bi-directional causal relationship: teleological claims about a species resulted in moral condemnation of purpose violations, and stipulating that an action is immoral increased judgments that the species exists for that purpose. Study 3 (N=94) replicated a causal effect of species-level purpose on moral condemnation with novel actions and more implicit character judgments. Study 4 (N=52) found that when a species is believed to exist to perform some action, participants infer that the action is good for the species, and that this belief in turn supports moral condemnation of individuals who choose not to perform the action. Together, these findings shed light on how our descriptive understanding can shape our prescriptive judgments.

Across the lifespan, humans direct their learning towards information they are curious to know. However, it is unclear what elicits curiosity, and whether and how this changes across development. Is curiosity triggered by surprise and uncertainty, as prior research suggests, or by expected learning, which is often confounded with these features? In the present research, we use a Bayesian reinforcement learning model to quantify and disentangle surprise, uncertainty, and expected learning. We use the resulting model-estimated features to predict curiosity ratings from 5- to 9-year-olds and adults in an augmented multi-armed bandit task. Like adults’ curiosity, children’s curiosity was best predicted by expected learning. However, after accounting for expected learning, children (but not adults) were also more curious when uncertainty was higher and surprise lower. This research points to developmental changes in what elicits curiosity and calls for a reexamination of research that confounds these elicitors.

People think they ought to make some decisions on the basis of deliberative analysis, and others on the basis of intuitive, gut feelings. What accounts for this variation in people’s preferences for intuition versus deliberation? We propose that intuition might be prescribed for some decisions because people’s folk theory of decision-making accords a special role to authenticity, where authenticity is uniquely associated with intuitive choice. Two pre-registered experiments find evidence in favor of this claim. In Experiment 1 (N=631), we find that decisions made on the basis of intuition (vs. deliberation) are more likely to be judged authentic, especially in domains where authenticity is plausibly valued. In Experiment 2 (N=177), we find that people are more likely to prescribe intuition as a basis for choice when the value of authenticity is heightened experimentally. These effects hold beyond previously recognized influences, such as computational costs, presumed efficacy, objectivity, complexity, and expertise.

In this paper, we investigate the informativeness of 4- to 6-year-old (N = 125) children’s questions using a combined qualitative and quantitative approach. Children were presented with a hierarchical version of the 20-questions game, in which they were given an array of objects that could be organized into three category levels based on shared features. We then tested whether it is possible to scaffold children’s question-asking abilities without extensive training. In particular, we supported children’s categorization performance by providing the object-related features needed to ask effective constraint-seeking questions. We found that with both age and scaffolding children asked more effective questions, targeting higher category levels and therefore reaching the solution with fewer questions. We discuss the practical and theoretical implications of these results.

Adults have been shown to favor stable causal relationships – those that hold robustly across background contexts –in their actions and causal/explanatory generalizations (Vasilyeva et al, 2018). Here we explore how this preference develops. We present results from one study with 141 4-7-year-olds investigating whether children pay attention to causal stability when they explain observations and design interventions in novel contexts. We report developmental shifts in reliance on causal stability in a range of inferential tasks, highlight the important role of perceived average causal strength in determining children’s causal preferences, and discuss the implications of our findings for theories of early causal learning. To our knowledge, this is the first study exploring the role of stability in children’s causal reasoning.

People often answer why-questions with what we call experiential explanations: narratives or stories with temporal structure and concrete details. In contrast, on most theories of the epistemic function of explanation, explanations should be abstractive: structured by general relationships and lacking extraneous details. We suggest that abstractive and experiential explanations differ not only in level of abstraction, but also in structure, and that each form of explanation contributes to the epistemic goals of individual learners and of science. In particular, experiential explanations support mental simulation and survive transitions across background theories; as a result, they support learning and help us translate between competing frameworks. Experiential explanations play an irreducible role in human cognition—and perhaps in science.

Mental simulation — such as imagining tilting a glass to figure out the angle at which water would spill — can be a way of coming to know the answer to an internally or externally posed query. Is this form of learning a species of inference or a form of observation? We argue that it is neither: learning through simulation is a genuinely distinct form of learning. On our account, simulation can provide knowledge of the answer to a query even when the basis for that answer is opaque to the learner. Moreover, through repeated simulation, the learner can reduce this opacity, supporting self-training and the acquisition of more accurate models of the world. Simulation is thus an essential part of the story of how creatures like us become effective learners and knowers.

A great deal of work argues that people demand impartial, evidence-based reasoning from others. However, recent findings show that moral values occupy a cardinal position in people’s evaluation of others, raising the possibility that people sometimes prescribe morally-good but evidentially-poor beliefs. We report two studies investigating how people evaluate beliefs when these two ideals conflict and find that people regularly endorse motivated reasoning when it can be morally justified. Furthermore, we document two ways that moral considerations result in prescribed motivated reasoning. First, morality can provide an alternative justification for belief, leading people to prescribe evidentially unsupported beliefs to others. And, second, morality can affect how people evaluate the way evidence is weighed by lowering or raising the threshold of required evidence for morally good and bad beliefs, respectively. These results illuminate longstanding questions about the nature of motivated reasoning and the social regulation of belief.

Questions about the origins of life and the universe seem to call out for explanation, with science and religion offering candidate answers. These answers clearly differ in content, but do they also differ in psychological function? In Study 1 (N=501) participants on Amazon Mechanical Turk rated scientific and religious answers to existential questions on dimensions related to epistemic functions (e.g., “This explanation is based on evidence”) as well as moral/social/emotional functions (e.g., “If everyone believed this, the world would be a more moral place”; “This explanation is comforting”). For non-religious participants, only scientific explanations were assigned high values along epistemic dimensions; For religious participants, only religious explanations were assigned high values along non-epistemic dimensions. In Study 2 (N=130), priming a non-epistemic need boosted religious participants’ evaluation of the quality of religious (vs. scientific) explanations. These findings shed light on the functions of scientific and religious cognition and raise new questions about explanatory co-existence and the origins of religious belief.

Previous research suggests that preschoolers struggle with understanding abstract relations andwithreasoning by analogy. Four experiments find, in contrast, that 3-and 4-year-olds (N=168) are surprisingly adept at relational and analogical reasoning within a causal context. In earlier studies preschoolers routinely favoredimagesthat share thematic or perceptual commonalities with a target image(object matches) over choices that match the target along abstract relations (relational matches). The present studies embed suchchoice taskswithin a cause-and-effect framework. Withoutcausal framing, preschoolers strongly favor object matches, replicating the results of previous studies. But withcausal framing, preschoolers succeed at analogical transfer (i.e., choose relational matches). These findings suggest that causal framing facilitates early analogical reasoning.

Curiosity motivates exploration and is beneficial for learning, but curiosity is not always experienced when facing the unknown. In the present research, we address this selectivity: what causes curiosity to be experienced under some circumstances but not others? Using a Bayesian reinforcement learning model, we disentangle four possible influences on curiosity that have typically been confounded in previous research: surprise, local uncertainty/expected information gain, global uncertainty, and global expected information gain. In two experiments, we find that backward-looking influences (concerning beliefs based on prior experience) and forward-looking influences (concerning expectations about future learning) independently predict reported curiosity, and that forward-looking influences explain the most variance. These findings begin to disentangle the complex environmental features that drive curiosity.

Why do some (and only some) observations prompt people to ask “why?” We proposea functional approach to “Explanation-Seeking Curiosity” (ESC): the state that motivates people to seek an explanation. If ESC tends to prompt explanation search when doing so is likely to be beneficial, we can use prior work on the functional consequences of explanation search to derive “forward-looking” candidate triggers of ESC—those that concern expectations about the downstream consequences of pursuing explanation search. Across three studies (N = 877), we test hypotheses derived from this functional approach. In Studies 1-3, we find that ESC is most strongly predicted by expectations about future learningand future utility. We also find thatjudgments of novelty, surprise, and information gap predict ESC,consistent with prior work on curiosity; however, the role for forward-looking considerations is not reducible to these factors. In Studies 2-3, we findthat predictors of ESCform three clusters, expectations about learning(about the target of explanation), expectations aboutexport (to other cases and future contexts), and backward-looking considerations (having to do with the relationship between the target of explanation and prior knowledge). Additionally, these clusters are consistent across stimulus sets that probe ESC,but not fact-seeking curiosity.These findings suggest that explanation-seeking curiosity is aroused in a systematic way, and that people are not only sensitive to the match or mismatch between a given stimulus and their current or former beliefs, but to how they expect an explanation for that stimulus to improve their epistemic state.

Children are known for asking “why?”—a query motivated by their desire for explanations. Research suggests that explanation-seeking curiosity (ESC) is triggered by first person cues (such as novelty or surprise), third-person cues (such as a knowledgeable adults’ surprise or question), and future-oriented cues (such as expectations about information gain or future value). Once triggered, ESC is satisfied by an adequate explanation, typically obtained through causal intervention or question asking, both of which change in efficiency over development. ESC is an important driver of children’s learning because it combines the power of active learning and intrinsic motivation with the value of explanatory content, which can reveal the unobservable and causal structure of the world to support generalizable knowledge.

Some claims (e.g., that the earth goes around the sun) seem to call out for explanation: they make us wonder “why?”. For other claims (e.g., that God exists), one might accept that the explanation is a mystery. In the present research, we investigate “need for explanation” and “mystery acceptability” across the domains of science and religion, as a window onto differences between scientific and religious cognition more broadly. In Study 1, we find that scientific “why” questions are judged to be in greater need of explanation and less adequately answered by appeals to mystery than religious “why” questions. Moreover, this holds for both religious believers and non-believers. In Study 2, we find that these domain differences persist after statistically controlling for confidence in the premises of scientific and religious why questions (e.g., that “the earth goes around the sun” and that “there is a God”). In Study 3, we match levels of confidence within-participants, and we find that domain differences in need for explanation and mystery acceptability are systematically related to domain differences in epistemic commitments (whether an explanation is within human comprehension, whether the same explanation is true for everyone) and explanatory norms (whether an explanation should be pursued), which could signal domain differences in epistemic and social functions, respectively. Together, these studies shed light on the role of explanatory inquiry across domains, and point to different functional roles for scientific and religious cognition.