Causal relational problem solving in toddlers.

We investigate young children's capacity for "causal relational reasoning": the ability to use relational reasoning to design novel interventions and bring about novel outcomes. In two experiments, we show that 24-30-month-old toddlers and three-year-old preschoolers use relational reasoning in a causal problem-solving task. Even toddlers rapidly inferred relational causal rules and applied this knowledge to solve novel problems--thus demonstrating both surprisingly early competence in relational reasoning and sophisticated causal inference. In both experiments, children observed a handful of trials in which a mechanistically opaque machine made objects larger or smaller. When prompted to solve a new problem, they used the machine to change the relative size of a novel object - even though its appearance and absolute size differed from previous observations, and even though subjects had never seen the machine generate objects of the required size before. This suggests that children quickly inferred abstract causal relations and then generalized these relations to determine which intervention would bring about the novel outcome required to solve the problem. These findings suggest a close link between early relational reasoning and active causal learning and inference.

Preschoolers' Comprehension of Functional Metaphors.

Previous work suggests that preschoolers often misunderstand metaphors. However, some recent studies demonstrate that preschoolers can represent abstract relations, suggesting that the cognitive foundations of metaphor comprehension may develop earlier than previously believed. The present experiments used novel paradigms to explore whether preschoolers (N = 200; 4-5 years; 100 males, 100 females; predominantly White) can understand metaphors based on abstract, functional similarities. In Experiment 1, preschoolers and adults (N = 64; 18-41 years; 25 males, 39 females; predominantly White) rated functional metaphors (e.g., "Roofs are hats"; "Tires are shoes") as "smarter" than nonsense statements (e.g., "Boats are skirts"; "Pennies are sunglasses") in a metalinguistic judgment task (d = .42 in preschoolers; d = 3.06 in adults). In Experiment 2, preschoolers preferred functional explanations (e.g., "Both keep you dry") over perceptual explanations (e.g., "Both have pointy tops") when interpreting functional metaphors (e.g., "Roofs are hats") (d = .99). In Experiment 3, preschoolers preferred functional metaphors (e.g., "Roofs are hats") over nonsense statements (e.g., "Roofs are scissors") when prompted to select the "better" utterance (d = 1.25). Moreover, over a quarter of preschoolers in Experiment 1 and half of preschoolers in Experiment 3 explicitly articulated functional similarities when justifying their responses, and the performance of these subsets of children drove the success of the entire sample in both experiments. These findings demonstrate that preschoolers can understand metaphors based on abstract, functional similarities.

Using games to understand the mind.

Board, card or video games have been played by virtually every individual in the world. Games are popular because they are intuitive and fun. These distinctive qualities of games also make them ideal for studying the mind. By being intuitive, games provide a unique vantage point for understanding the inductive biases that support behaviour in more complex, ecological settings than traditional laboratory experiments. By being fun, games allow researchers to study new questions in cognition such as the meaning of 'play' and intrinsic motivation, while also supporting more extensive and diverse data collection by attracting many more participants. We describe the advantages and drawbacks of using games relative to standard laboratory-based experiments and lay out a set of recommendations on how to gain the most from using games to study cognition. We hope this Perspective will lead to a wider use of games as experimental paradigms, elevating the ecological validity, scale and robustness of research on the mind.

Structural explanations lead young children and adults to rectify resource inequalities.

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- to 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.

Preschoolers and adults metonymically extend proper names to owned objects.

Three preregistered experiments, conducted in 2021, investigated whether English-speaking American preschoolers (N = 120; 4-6 years; 54 females, predominantly White) and adults (N = 80; 18-52 years; 59 females, predominantly Asian) metonymically extend owners' names to owned objects-an extension not typically found in English. In Experiment 1, 5- and 6-year-olds and adults extended names to owned objects over duplicates (d = 0.34 in children; d = 1.13 in adults). In Experiment 2, 5- and 6-year-olds and adults extended names to owned over borrowed objects (d = 1.37 in children; d = 4.34 in adults). Experiment 3 replicated this finding with 4-year-olds (d = 0.43). Thus, English-speaking preschoolers can acquire semantic generalizations, even those not present in their language.

Preschoolers search longer when there is more information to be gained.

What drives children to explore and learn when external rewards are uncertain or absent? Across three studies, we tested whether information gain itself acts as an internal reward and suffices to motivate children's actions. We measured 24-56-month-olds' persistence in a game where they had to search for an object (animal or toy), which they never find, hidden behind a series of doors, manipulating the degree of uncertainty about which specific object was hidden. We found that children were more persistent in their search when there was higher uncertainty, and therefore, more information to be gained with each action, highlighting the importance of research on artificial intelligence to invest in curiosity-driven algorithms. RESEARCH HIGHLIGHTS: Across three studies, we tested whether information gain itself acts as an internal reward and suffices to motivate preschoolers' actions. We measured preschoolers' persistence when searching for an object behind a series of doors, manipulating the uncertainty about which specific object was hidden. We found that preschoolers were more persistent when there was higher uncertainty, and therefore, more information to be gained with each action. Our results highlight the importance of research on artificial intelligence to invest in curiosity-driven algorithms.

Transmission Versus Truth, Imitation Versus Innovation: What Children Can Do That Large Language and Language-and-Vision Models Cannot (Yet).

Much discussion about large language models and language-and-vision models has focused on whether these models are intelligent agents. We present an alternative perspective. First, we argue that these artificial intelligence (AI) models are cultural technologies that enhance cultural transmission and are efficient and powerful imitation engines. Second, we explore what AI models can tell us about imitation and innovation by testing whether they can be used to discover new tools and novel causal structures and contrasting their responses with those of human children. Our work serves as a first step in determining which particular representations and competences, as well as which kinds of knowledge or skill, can be derived from particular learning techniques and data. In particular, we explore which kinds of cognitive capacities can be enabled by statistical analysis of large-scale linguistic data. Critically, our findings suggest that machines may need more than large-scale language and image data to allow the kinds of innovation that a small child can produce.

Early adversity and the development of explore-exploit tradeoffs.

Childhood adversity can have wide-ranging and long-lasting effects on later life. But what are the mechanisms that are responsible for these effects? This article brings together the cognitive science literature on explore-exploit tradeoffs, the empirical literature on early adversity, and the literature in evolutionary biology on 'life history' to explain how early experience influences later life. We propose one potential mechanism: early experiences influence 'hyperparameters' that determine the balance between exploration and exploitation. Adversity might accelerate a shift from exploration to exploitation, with broad and enduring effects on the adult brain and mind. These effects may be produced by life-history adaptations that use early experience to tailor development and learning to the likely future states of an organism and its environment.

Preschoolers and Adults Learn From Novel Metaphors.

Although adults use metaphors to guide their thinking and reasoning, less is known about whether metaphors might facilitate cognition earlier in development. Previous research shows that preschoolers understand metaphors, but less is known about whether preschoolers can learn from metaphors. The current preregistered experiment investigated whether adults (n = 64) and 3- and 4-year-olds (n = 128) can use metaphors to make new inferences. In a between-subjects design, participants heard information about novel artifacts, conveyed through either only positive metaphors (e.g., "Daxes are suns") or positive and negative metaphors (e.g., "Daxes are suns. Daxes are not clouds."). In both conditions, participants of all ages successfully formed metaphor-consistent inferences about abstract, functional features of the artifacts (e.g., that daxes light up rather than let out water). Moreover, participants frequently provided explanations appealing to the metaphors when justifying their responses. Consequently, metaphors may be a powerful learning mechanism from early childhood onward.

Ask me why, don't tell me why: Asking children for explanations facilitates relational thinking.

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.

Causal learning, counterfactual reasoning and pretend play: a cross-cultural comparison of Peruvian, mixed- and low-socioeconomic status U.S. children.

Pretend play universally emerges during early childhood and may support the development of causal inference and counterfactual reasoning. However, the amount of time spent pretending, the value that adults place on pretence and the scaffolding adults provide vary by both culture and socioeconomic status (SES). In middle class U.S. preschoolers, accuracy on a pretence-based causal reasoning task predicted performance on a similar causal counterfactual task. We explore the relationship between cultural environment, pretence and counterfactual reasoning in low-income Peruvian (N = 62) and low-income U.S. (N = 57) 3- to 4-year olds, and contrast findings against previous findings in an age-matched, mixed-SES U.S. sample (N = 60). Children learned a novel causal relationship, then answered comparable counterfactual and pretence-based questions about the relationship. Children's responses for counterfactual and pretence measures differed across populations, with Peruvian and lower-income U.S. children providing fewer causally consistent responses when compared with middle class U.S. children. Nevertheless, correlations between the two measures emerged in all populations. Across cohorts, children also provided more causally consistent answers during pretence than counterfactually. Our findings strengthen the hypothesis that causal pretend play is related to causal counterfactual reasoning across cultural contexts, while also suggesting a role for systematic environmental differences. This article is part of the theme issue 'Thinking about possibilities: mechanisms, ontogeny, functions and phylogeny'.

Computational ethics.

Technological advances are enabling roles for machines that present novel ethical challenges. The study of 'AI ethics' has emerged to confront these challenges, and connects perspectives from philosophy, computer science, law, and economics. Less represented in these interdisciplinary efforts is the perspective of cognitive science. We propose a framework - computational ethics - that specifies how the ethical challenges of AI can be partially addressed by incorporating the study of human moral decision-making. The driver of this framework is a computational version of reflective equilibrium (RE), an approach that seeks coherence between considered judgments and governing principles. The framework has two goals: (i) to inform the engineering of ethical AI systems, and (ii) to characterize human moral judgment and decision-making in computational terms. Working jointly towards these two goals will create the opportunity to integrate diverse research questions, bring together multiple academic communities, uncover new interdisciplinary research topics, and shed light on centuries-old philosophical questions.

The development of creative search strategies.

How does creativity develop? Creativity is a multi-faceted behavior and thus it is difficult to find measures for creativity that are both precise and comparable across development. Here, we examine the development of creativity using a "creative foraging" task. The task measures different facets of creativity which we compare between 4- to 8-year-old children and adults. We find that compared to adults, children spend a higher percentage of their search exploring, and their exploitation phases are less efficient. Moreover, children orient their search to a different and smaller region of the search space, but within that space they produce more unique creative products. Lastly, as children grow up, their creative products become more adult-like and their uniqueness decreases. Together, these results suggest that creative search changes across development, in the search strategy employed, in how the space of possibilities is navigated, and in what ideas are ultimately chosen.

Children are more exploratory and learn more than adults in an approach-avoid task.

Intuitively, children appear to be more exploratory than adults, and this exploration seems to help children learn,. However, there have been few clear tests of these ideas. We test whether exploration and learning change across development using a task that presents a "learning trap." In this task, exploitation-maximizing immediate reward and avoiding costs-may lead the learner to draw incorrect conclusions, while exploration may lead to better learning but be more costly. In Studies 1, 2, and 3 we find that preschoolers and early school-aged children explore more than adults and learn the true structure of the environment better. Study 3 demonstrates that children explore more than adults even though they, like adults, predict that exploration will be costly, and it shows that exploration and learning are correlated. Study 4 shows that children's and adults' learning depends on the evidence they generate during exploration: children exposed to adult-like evidence learn like adults, and adults exposed to child-like evidence learn like children. Together, these studies support the idea that children may be more exploratory than adults, and this increased exploration influences learning.

How is the hypothesis space represented? Evidence from young children's active search and predictions in a multiple-cue inference task.

To successfully navigate an uncertain world, one has to learn the relationship between cues (e.g., wind speed, atmospheric pressure) and outcomes (e.g., rain). When learning, it is possible to actively manipulate the cue values to test hypotheses about this relationship directly. Across two studies, we investigated how 5- to 7-year-olds actively learned cue-outcome relationships, and what their behavior revealed about how they represented the hypothesis space. Children learned how two cues (color and shape) predicted some monsters' relative speed, by selecting which monster pairs to see racing. We compared two computational models in their ability to capture children's behavior: a cue-abstraction model, which organizes the hypothesis space based on abstracted cue-outcome relationships, and a permutation-based model, which represents the hypothesis space based on the relative speed of individual monsters. The results of Study 1 (26 five-year-olds, 14 female and 25 six-year-olds, 15 female; predominantly White, fluent in English) provided the first evidence that 5- and 6-year-olds can use cue-abstraction hypothesis space representations when provided with scaffolding. However, Study 2 (65 five-year-olds, 33 female; 67 six-year-olds, 33 female; 68 seven-year-olds, 33 female; predominantly White, fluent in German) showed that young children were best described by the permutation-based model, and that only 7-year-olds, when provided with memory aids, were best captured by the cue-abstraction model. Overall, our results highlight the guiding role of the hypothesis space for active search and learning, suggesting that these two phases might trigger different representations, and indicating a developmental shift in how children represent the hypothesis space. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Culture moderates the relationship between self-control ability and free will beliefs in childhood.

We investigate individual, developmental, and cultural differences in self-control in relation to children's changing belief in "free will" - the possibility of acting against and inhibiting strong desires. In three studies, 4- to 8-year-olds in the U.S., China, Singapore, and Peru (N = 441) answered questions to gauge their belief in free will and completed a series of self-control and inhibitory control tasks. Children across all four cultures showed predictable age-related improvements in self-control, as well as changes in their free will beliefs. Cultural context played a role in the timing of these emerging free will beliefs: Singaporean and Peruvian children's beliefs changed at later ages than Chinese and U.S. children. Critically, culture moderated the link between self-control abilities and free will beliefs: Individual differences in self-control behaviors were linked to individual differences in free will beliefs in U.S. children, but not in children from China, Singapore or Peru. There was also evidence of a causal influence of self-control performance on free will beliefs in our U.S. sample. In Study 2, a randomly assigned group of U.S. 4- and 5-year-olds who failed at two self-control tasks showed reduced belief in free will, but a group of children who completed free will questions first did not show changes to self-control. Together these results suggest that culturally-acquired causal-explanatory frameworks for action, along with observations of one's own abilities, might influence children's emerging understanding of free will.

Distinct electrophysiological signatures of task-unrelated and dynamic thoughts.

Humans spend much of their lives engaging with their internal train of thoughts. Traditionally, research focused on whether or not these thoughts are related to ongoing tasks, and has identified reliable and distinct behavioral and neural correlates of task-unrelated and task-related thought. A recent theoretical framework highlighted a different aspect of thinking-how it dynamically moves between topics. However, the neural correlates of such thought dynamics are unknown. The current study aimed to determine the electrophysiological signatures of these dynamics by recording electroencephalogram (EEG) while participants performed an attention task and periodically answered thought-sampling questions about whether their thoughts were 1) task-unrelated, 2) freely moving, 3) deliberately constrained, and 4) automatically constrained. We examined three EEG measures across different time windows as a function of each thought type: stimulus-evoked P3 event-related potentials and non-stimulus-evoked alpha power and variability. Parietal P3 was larger for task-related relative to task-unrelated thoughts, whereas frontal P3 was increased for deliberately constrained compared with unconstrained thoughts. Frontal electrodes showed enhanced alpha power for freely moving thoughts relative to non-freely moving thoughts. Alpha-power variability was increased for task-unrelated, freely moving, and unconstrained thoughts. Our findings indicate distinct electrophysiological patterns associated with task-unrelated and dynamic thoughts, suggesting these neural measures capture the heterogeneity of our ongoing thoughts.