Abstract
Causal understanding is a defining characteristic of human cognition. Like many animals, human children learn to control their bodily movements and act effectively in the environment. Like a smaller subset of animals, children intervene: they learn to change the environment in targeted ways. Unlike other animals, children grow into adults with the causal reasoning skills to develop abstract theories, invent sophisticated technologies and imagine alternate pasts, distant futures and fictional worlds. In this Review, we explore the development of human-unique causal learning and reasoning from evolutionary and ontogenetic perspectives. We frame our discussion using an ‘interventionist’ approach. First, we situate causal understanding in relation to cognitive abilities shared with non-human animals. We argue that human causal understanding is distinguished by its depersonalized (objective) and decontextualized (general) representations. Using this framework, we next review empirical findings on early human causal learning and reasoning and consider the naturalistic contexts that support its development. Then we explore connections to related abilities. We conclude with suggestions for ongoing collaboration between developmental, cross-cultural, computational, neural and evolutionary approaches to causal understanding.
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References
Prüfer, K. et al. The bonobo genome compared with the chimpanzee and human genomes. Nature 486, 527–531 (2012).
Gopnik, A. & Wellman, H. M. Reconstructing constructivism: causal models, Bayesian learning mechanisms, and the theory theory. Psychol. Bull. 138, 1085–1108 (2012). This paper provides an introduction to the interventionist approach formalized in terms of causal Bayes nets.
Gopnik, A. & Schulz, L. (eds.) Causal Learning: Psychology, Philosophy and Computation (Oxford Univ. Press, 2007). This edited volume provides an interdisciplinary overview of the interventionist approach.
Pearl, J. Causality (Cambridge Univ. Press, 2009).
Penn, D. C. & Povinelli, D. J. Causal cognition in human and nonhuman animals: a comparative, critical review. Annu. Rev. Psychol. 58, 97–118 (2007).
Schölkopf, B. et al. Toward causal representation learning. Proc. IEEE 109, 612–634 (2021).
Spirtes, P., Glymour, C. & Scheines, R. in Causation, Prediction, and Search Lecture Notes in Statistics Vol 81, 103–162 (Springer, 1993).
Gopnik, A. et al. A theory of causal learning in children: causal maps and Bayes nets. Psychol. Rev. 111, 3–32 (2004). This seminal paper reviews the causal Bayes nets approach to causal reasoning and suggests that children construct mental models that help them understand and predict causal relations.
Pearl, J. & Mackenzie, D. The Book of Why: The New Science of Cause and Effect (Basic Books, 2018). This book provides a high-level overview of approaches to causal inference from theoretical computer science for a general audience.
Lombrozo, T. & Vasil, N. in Oxford Handbook of Causal Reasoning (ed. Waldmann, M.) 415–432 (Oxford Univ. Press, 2017).
Woodward, J. Making Things Happen: A Theory of Causal Explanation (Oxford Univ. Press, 2005). This book outlines the ‘interventionist’ approach to causation and causal explanation in philosophy.
Shanks, D. R. & Dickinson, A. Associative accounts of causality judgment. Psychol. Learn. Motiv. 21, 229–261 (Elsevier, 1988).
Carey, S. The Origin of Concepts (Oxford Univ. Press, 2009).
Michotte, A. The Perception of Causality (Routledge, 2017).
Leslie, A. M. The perception of causality in infants. Perception 11, 173–186 (1982). This canonical study shows that 4.5-month-old and 8-month-old infants are sensitive to spatiotemporal event configurations and contingencies that adults also construe as causal.
Leslie, A. M. Spatiotemporal continuity and the perception of causality in infants. Perception 13, 287–305 (1984).
Danks, D. Unifying the Mind: Cognitive Representations as Graphical Models (MIT Press, 2014).
Godfrey‐Smith, P. in The Oxford Handbook of Causation (eds Beebee, H., Hitchcock, C. & Menzies, P.) 326–338 (Oxford Academic, 2009).
Gweon, H. & Schulz, L. 16-month-olds rationally infer causes of failed actions. Science 332, 1524–1524 (2011).
Woodward, J. Causation with a Human Face: Normative Theory and Descriptive Psychology (Oxford Univ. Press, 2021). This book integrates philosophical and psychological literatures on causal reasoning to provide both normative and descriptive accounts of causal reasoning.
Rozenblit, L. & Keil, F. The misunderstood limits of folk science: an illusion of explanatory depth. Cogn. Sci. 26, 521–562 (2002).
Ismael, J. How Physics Makes us Free (Oxford Univ. Press, 2016).
Woodward, J. in Causal Learning: Psychology, Philosophy, and Computation (eds Gopnik, A. & Schulz, L.) Oxford Series in Cognitive Development 19–36 (Oxford Academic, 2007).
Godfrey-Smith, P. Other Minds: The Octopus, the Sea, and the Deep Origins of Consciousness (Farrar, Straus and Giroux, 2016).
Körding, K. P. et al. Causal inference in multisensory perception. PLoS One 2, e943 (2007).
Wei, K. & Körding, K. P. in Sensory Cue Integration (eds Trommershäuser, J., Kording, K. & Landy, M. S.) Computational Neuroscience Series 30–45 (Oxford Academic, 2011).
Haith, A. M. & Krakauer, J. W. in Progress in Motor Control: Neural, Computational and Dynamic Approaches (eds Richardson, M. J., Riley, M. A. & Shockley, K.) 1–21 (Springer, 2013).
Krakauer, J. W. & Mazzoni, P. Human sensorimotor learning: adaptation, skill, and beyond. Curr. Opin. Neurobiol. 21, 636–644 (2011).
Adolph, K. E. An ecological approach to learning in (not and) development. Hum. Dev. 63, 180–201 (2020).
Adolph, K. E., Hoch, J. E. & Ossmy, O. in Perception as Information Detection (eds Wagman, J. B. & Blau, J. J. C.) 222–236 (Routledge, 2019).
Riesen, A. H. The development of visual perception in man and chimpanzee. Science 106, 107–108 (1947).
Spelke, E. S. What Babies Know: Core Knowledge and Composition Vol. 1 (Oxford Univ. Press, 2022).
Pearce, J. M. & Bouton, M. E. Theories of associative learning in animals. Annu. Rev. Psychol. 52, 111–139 (2001).
Wasserman, E. A. & Miller, R. R. What’s elementary about associative learning? Annu. Rev. Psychol. 48, 573–607 (1997).
Sutton, R. S. & Barto, A. G. Reinforcement learning: an introduction. Robotica 17, 229–235 (1999).
Gershman, S. J., Markman, A. B. & Otto, A. R. Retrospective revaluation in sequential decision making: a tale of two systems. J. Exp. Psychol. Gen. 143, 182–194 (2014).
Gershman, S. J. Reinforcement learning and causal models. In Oxford Handbook of Causal Reasoning (ed. Waldmann, M.) 295 (Oxford Univ. Press, 2017).
Taylor, A. H. et al. Of babies and birds: complex tool behaviours are not sufficient for the evolution of the ability to create a novel causal intervention. Proc. R. Soc. B 281, 20140837 (2014). This study shows that complex tool use does not entail the ability to understand and create novel causal interventions: crows do not learn causal interventions from observing the effects of their own accidental behaviours.
Povinelli, D. J. & Penn, D. C. in Tool Use and Causal Cognition (eds McCormack, T., Hoerl, C. & Butterfill, S.) 69–88 (Oxford Univ. Press, 2011).
Povinelli, D. J. & Henley, T. More rope tricks reveal why more task variants will never lead to strong inferences about higher-order causal reasoning in chimpanzees. Anim. Behav. Cogn. 7, 392–418 (2020).
Tomasello, M. & Call, J. Primate Cognition (Oxford Univ. Press, 1997).
Visalberghi, E. & Tomasello, M. Primate causal understanding in the physical and psychological domains. Behav. Process. 42, 189–203 (1998).
Völter, C. J., Sentís, I. & Call, J. Great apes and children infer causal relations from patterns of variation and covariation. Cognition 155, 30–43 (2016).
Tennie, C., Call, J. & Tomasello, M. Untrained chimpanzees (Pan troglodytes schweinfurthii) fail to imitate novel actions. Plos One 7, e41548 (2012).
Whiten, A., Horner, V., Litchfield, C. A. & Marshall-Pescini, S. How do apes ape? Anim. Learn. Behav. 32, 36–52 (2004).
Moore, R. Imitation and conventional communication. Biol. Phil. 28, 481–500 (2013).
Meltzoff, A. N. & Marshall, P. J. Human infant imitation as a social survival circuit. Curr. Opin. Behav. Sci. 24, 130–136 (2018).
Boesch, C. & Boesch, H. Optimisation of nut-cracking with natural hammers by wild chimpanzees. Behaviour 83, 265–286 (1983).
Chappell, J. & Kacelnik, A. Tool selectivity in a non-primate, the New Caledonian crow (Corvus moneduloides). Anim. Cogn. 5, 71–78 (2002).
Weir, A. A., Chappell, J. & Kacelnik, A. Shaping of hooks in New Caledonian crows. Science 297, 981–981 (2002).
Wimpenny, J. H., Weir, A. A., Clayton, L., Rutz, C. & Kacelnik, A. Cognitive processes associated with sequential tool use in New Caledonian crows. PLoS One 4, e6471 (2009).
Manrique, H. M., Gross, A. N.-M. & Call, J. Great apes select tools on the basis of their rigidity. J. Exp. Psychol. Anim. Behav. Process. 36, 409–422 (2010).
Mulcahy, N. J., Call, J. & Dunbar, R. I. Gorillas (Gorilla gorilla) and orangutans (Pongo pygmaeus) encode relevant problem features in a tool-using task. J. Comp. Psychol. 119, 23–32 (2005).
Sanz, C., Call, J. & Morgan, D. Design complexity in termite-fishing tools of chimpanzees (Pan troglodytes). Biol. Lett. 5, 293–296 (2009).
Visalberghi, E. et al. Selection of effective stone tools by wild bearded capuchin monkeys. Curr. Biol. 19, 213–217 (2009).
Seed, A., Hanus, D. & Call, J. in Tool Use and Causal Cognition (eds McCormack, T., Hoerl, C. & Butterfill, S.) 89–110 (Oxford Univ. Press, 2011).
Völter, C. J. & Call, J. in APA Handbook of Comparative Psychology: Perception, Learning, and Cognition (eds Call, J. et al.) 643–671 (American Psychological Association, 2017). This chapter provides a comprehensive overview of causal and inferential reasoning in non-human animals, highlighting (1) the difference between prediction versus causal knowledge and (2) the organization of non-human animals’ knowledge (stimulus- and/or context-specific versus general and structured).
Völter, C. J., Lambert, M. L. & Huber, L. Do nonhumans seek explanations? Anim. Behav. Cogn. 7, 445–451 (2020).
Call, J. Inferences about the location of food in the great apes (Pan paniscus, Pan troglodytes, Gorilla gorilla, and Pongo pygmaeus). J. Comp. Psychol. 118, 232–241 (2004).
Call, J. Apes know that hidden objects can affect the orientation of other objects. Cognition 105, 1–25 (2007).
Hanus, D. & Call, J. Chimpanzees infer the location of a reward on the basis of the effect of its weight. Curr. Biol. 18, R370–R372 (2008).
Hanus, D. & Call, J. Chimpanzee problem-solving: contrasting the use of causal and arbitrary cues. Anim. Cogn. 14, 871–878 (2011).
Petit, O. et al. Inferences about food location in three cercopithecine species: an insight into the socioecological cognition of primates. Anim. Cogn. 18, 821–830 (2015).
Heimbauer, L. A., Antworth, R. L. & Owren, M. J. Capuchin monkeys (Cebus apella) use positive, but not negative, auditory cues to infer food location. Anim. Cogn. 15, 45–55 (2012).
Schloegl, C., Schmidt, J., Boeckle, M., Weiß, B. M. & Kotrschal, K. Grey parrots use inferential reasoning based on acoustic cues alone. Proc. R. Soc. B 279, 4135–4142 (2012).
Schloegl, C., Waldmann, M. R. & Fischer, J. Understanding of and reasoning about object–object relationships in long-tailed macaques? Anim. Cogn. 16, 493–507 (2013).
Schmitt, V., Pankau, B. & Fischer, J. Old world monkeys compare to apes in the primate cognition test battery. PLoS One 7, e32024 (2012).
Völter, C. J. & Call, J. Great apes (Pan paniscus, Pan troglodytes, Gorilla gorilla, Pongo abelii) follow visual trails to locate hidden food. J. Comp. Psychol. 128, 199–208 (2014).
Blaisdell, A. P., Sawa, K., Leising, K. J. & Waldmann, M. R. Causal reasoning in rats. Science 311, 1020–1022 (2006).
Leising, K. J., Wong, J., Waldmann, M. R. & Blaisdell, A. P. The special status of actions in causal reasoning in rats. J. Exp. Psychol. Gen. 137, 514–527 (2008).
Flavell, J. H. The Developmental Psychology Of Jean Piaget (Van Nostrand, 1963).
Piaget, J. The Construction of Reality in the Child (Routledge, 2013).
Henrich, J., Heine, S. J. & Norenzayan, A. Most people are not WEIRD. Nature 466, 29–29 (2010).
Ayzenberg, V. & Behrmann, M. Development of visual object recognition. Nat. Rev. Psychol. 3, 73–90 (2023).
Bronson, G. W. Changes in infants’ visual scanning across the 2- to 14-week age period. J. Exp. Child. Psychol. 49, 101–125 (1990).
Aslin, R. Ν. in Eye Movements. Cognition and Visual Perception (eds Fisher, D. F., Monty, R. A. & Senders, J. W.) 31–51 (Routledge, 2017).
Miranda, S. B. Visual abilities and pattern preferences of premature infants and full-term neonates. J. Exp. Child. Psychol. 10, 189–205 (1970).
Haith, M. M., Hazan, C. & Goodman, G. S. Expectation and anticipation of dynamic visual events by 3.5-month-old babies. Child Dev. 59, 467–479 (1988).
Harris, P. & MacFarlane, A. The growth of the effective visual field from birth to seven weeks. J. Exp. Child. Psychol. 18, 340–348 (1974).
Cohen, L. B. & Amsel, G. Precursors to infants’ perception of the causality of a simple event. Infant. Behav. Dev. 21, 713–731 (1998).
Leslie, A. M. & Keeble, S. Do six-month-old infants perceive causality? Cognition 25, 265–288 (1987).
Oakes, L. M. & Cohen, L. B. Infant perception of a causal event. Cogn. Dev. 5, 193–207 (1990). This canonical study shows that 10-month-olds, but not 6-month-olds, discriminate between causal versus non-causal events.
Kotovsky, L. & Baillargeon, R. Calibration-based reasoning about collision events in 11-month-old infants. Cognition 51, 107–129 (1994).
Kominsky, J. F. et al. Categories and constraints in causal perception. Psychol. Sci. 28, 1649–1662 (2017).
Spelke, E. S., Breinlinger, K., Macomber, J. & Jacobson, K. Origins of knowledge. Psychol. Rev. 99, 605 (1992).
Baillargeon, R. in Language, Brain, and Cognitive Development: Essays in Honor of Jacques Mehler (ed. Dupoux, E.) 341–361 (MIT Press, 2001).
Hespos, S. J. & Baillargeon, R. Infants’ knowledge about occlusion and containment events: a surprising discrepancy. Psychol. Sci. 12, 141–147 (2001).
Spelke, E. S. Principles of object perception. Cogn. Sci. 14, 29–56 (1990).
Sobel, D. M. & Kirkham, N. Z. Blickets and babies: the development of causal reasoning in toddlers and infants. Dev. Psychol. 42, 1103–1115 (2006).
Sobel, D. M. & Kirkham, N. Z. Bayes nets and babies: infants’ developing statistical reasoning abilities and their representation of causal knowledge. Dev. Sci. 10, 298–306 (2007).
Bell, S. M. & Ainsworth, M. D. S. Infant crying and maternal responsiveness. Child Dev. 43, 1171–1190 (1972).
Jordan, G. J., Arbeau, K., McFarland, D., Ireland, K. & Richardson, A. Elimination communication contributes to a reduction in unexplained infant crying. Med. Hypotheses 142, 109811 (2020).
Nakayama, H. Emergence of amae crying in early infancy as a possible social communication tool between infants and mothers. Infant. Behav. Dev. 40, 122–130 (2015).
Meltzoff, A. N. & Moore, M. K. in The Body and the Self (eds Bermúdez, J. L., Marcel, A. J. & Eilan, N.) 3–69 (MIT Press, 1995).
Rovee, C. K. & Rovee, D. T. Conjugate reinforcement of infant exploratory behavior. J. Exp. Child. Psychol. 8, 33–39 (1969).
Hillman, D. & Bruner, J. S. Infant sucking in response to variations in schedules of feeding reinforcement. J. Exp. Child. Psychol. 13, 240–247 (1972).
DeCasper, A. J. & Spence, M. J. Prenatal maternal speech influences newborns’ perception of speech sounds. Infant. Behav. Dev. 9, 133–150 (1986).
Watson, J. S. & Ramey, C. T. Reactions to response-contingent stimulation in early infancy. Merrill-Palmer Q. Behav. Dev. 18, 219–227 (1972).
Rovee-Collier, C. in Handbook of Infant Development 2nd edn (ed. Osofsky, J. D.) 98–148 (John Wiley & Sons, 1987).
Twitchell, T. E. The automatic grasping responses of infants. Neuropsychologia 3, 247–259 (1965).
Wallace, P. S. & Whishaw, I. Q. Independent digit movements and precision grip patterns in 1–5-month-old human infants: hand-babbling, including vacuous then self-directed hand and digit movements, precedes targeted reaching. Neuropsychologia 41, 1912–1918 (2003).
Von Hofsten, C. Mastering reaching and grasping: the development of manual skills in infancy. Adv. Psychol. 61, 223–258 (1989).
Witherington, D. C. The development of prospective grasping control between 5 and 7 months: a longitudinal study. Infancy 7, 143–161 (2005).
Needham, A., Barrett, T. & Peterman, K. A pick-me-up for infants’ exploratory skills: early simulated experiences reaching for objects using ‘sticky mittens’ enhances young infants’ object exploration skills. Infant. Behav. Dev. 25, 279–295 (2002).
van den Berg, L. & Gredebäck, G. The sticky mittens paradigm: a critical appraisal of current results and explanations. Dev. Sci. 24, e13036 (2021).
Keen, R. The development of problem solving in young children: a critical cognitive skill. Annu. Rev. Psychol. 62, 1–21 (2011). This paper provides an overview of the developmental trajectory of ‘problem-solving’skills in young children, integrating findings from perception and motor development studies with cognitive problem-solving studies.
Claxton, L. J., McCarty, M. E. & Keen, R. Self-directed action affects planning in tool-use tasks with toddlers. Infant. Behav. Dev. 32, 230–233 (2009).
McCarty, M. E., Clifton, R. K. & Collard, R. R. The beginnings of tool use by infants and toddlers. Infancy 2, 233–256 (2001).
Gopnik, A. & Meltzoff, A. N. Semantic and cognitive development in 15- to 21-month-old children. J. Child. Lang. 11, 495–513 (1984).
Gopnik, A. & Meltzoff, A. N. in The Development of Word Meaning: Progress in Cognitive Development Research (eds Kuczaj, S. A. & Barrett, M. D.) 199–223 (Springer, 1986).
Gopnik, A. & Meltzoff, A. N. Words, Thoughts, and Theories (Mit Press, 1997).
Tomasello, M. in Early Social Cognition: Understanding Others in the First Months of Life (ed. Rochat, P.) 301–314 (Lawrence Erlbaum Associates, 1999).
Tomasello, M. & Farrar, M. J. Joint attention and early language. Child Dev. 57, 1454–1463 (1986).
Gopnik, A. Words and plans: early language and the development of intelligent action. J. Child. Lang. 9, 303–318 (1982). This paper proposes that language acquisition tracks with conceptual developments in infants’ and toddlers’ abilities in goal-directed action and planning.
Meltzoff, A. N. Infant imitation and memory: nine-month-olds in immediate and deferred tests. Child. Dev. 59, 217–225 (1988).
Meltzoff, A. N. Infant imitation after a 1-week delay: long-term memory for novel acts and multiple stimuli. Dev. Psychol. 24, 470–476 (1988).
Gergely, G., Bekkering, H. & Király, I. Rational imitation in preverbal infants. Nature 415, 755–755 (2002).
Meltzoff, A. N., Waismeyer, A. & Gopnik, A. Learning about causes from people: observational causal learning in 24-month-old infants. Dev. Psychol. 48, 1215–1228 (2012). This study demonstrates that 2-year-old and 3-year-old children learn novel causal relations from observing other agents’ interventions (observational causal learning).
Waismeyer, A., Meltzoff, A. N. & Gopnik, A. Causal learning from probabilistic events in 24‐month‐olds: an action measure. Dev. Sci. 18, 175–182 (2015).
Stahl, A. E. & Feigenson, L. Observing the unexpected enhances infants’ learning and exploration. Science 348, 91–94 (2015). This study demonstrates that 11-month-old children pay special visual and exploratory attention to objects that appear to violate the laws of physics as the result of an agent’s intervention.
Perfors, A., Tenenbaum, J. B., Griffiths, T. L. & Xu, F. A tutorial introduction to Bayesian models of cognitive development. Cognition 120, 302–321 (2011).
Gopnik, A. & Bonawitz, E. Bayesian models of child development. Wiley Interdiscip. Rev. Cognit. Sci. 6, 75–86 (2015). This paper is a technical introduction and tutorial in the Bayesian framework.
Gopnik, A., Sobel, D. M., Schulz, L. E. & Glymour, C. Causal learning mechanisms in very young children: two-, three-, and four-year-olds infer causal relations from patterns of variation and covariation. Dev. Psychol. 37, 620–629 (2001).
Schulz, L. E. & Bonawitz, E. B. Serious fun: preschoolers engage in more exploratory play when evidence is confounded. Dev. Psychol. 43, 1045–1050 (2007).
Gopnik, A. & Sobel, D. M. Detecting blickets: how young children use information about novel causal powers in categorization and induction. Child. Dev. 71, 1205–1222 (2000).
Schulz, L. E., Gopnik, A. & Glymour, C. Preschool children learn about causal structure from conditional interventions. Dev. Sci. 10, 322–332 (2007).
Walker, C. M., Gopnik, A. & Ganea, P. A. Learning to learn from stories: children’s developing sensitivity to the causal structure of fictional worlds. Child. Dev. 86, 310–318 (2015).
Schulz, L. E., Bonawitz, E. B. & Griffiths, T. L. Can being scared cause tummy aches? Naive theories, ambiguous evidence, and preschoolers’ causal inferences. Dev. Psychol. 43, 1124–1139 (2007).
Kushnir, T. & Gopnik, A. Young children infer causal strength from probabilities and interventions. Psychol. Sci. 16, 678–683 (2005).
Walker, C. M. & Gopnik, A. Toddlers infer higher-order relational principles in causal learning. Psychol. Sci. 25, 161–169 (2014). This paper shows that 18–30-month-old infants can learn relational causal rules and generalize them to novel stimuli.
Sobel, D. M., Yoachim, C. M., Gopnik, A., Meltzoff, A. N. & Blumenthal, E. J. The blicket within: preschoolers’ inferences about insides and causes. J. Cogn. Dev. 8, 159–182 (2007).
Schulz, L. E. & Sommerville, J. God does not play dice: causal determinism and preschoolers’ causal inferences. Child. Dev. 77, 427–442 (2006).
Schulz, L. E. & Gopnik, A. Causal learning across domains. Dev. Psychol. 40, 162–176 (2004).
Seiver, E., Gopnik, A. & Goodman, N. D. Did she jump because she was the big sister or because the trampoline was safe? Causal inference and the development of social attribution. Child. Dev. 84, 443–454 (2013).
Vasilyeva, N., Gopnik, A. & Lombrozo, T. The development of structural thinking about social categories. Dev. Psychol. 54, 1735–1744 (2018).
Kushnir, T., Xu, F. & Wellman, H. M. Young children use statistical sampling to infer the preferences of other people. Psychol. Sci. 21, 1134–1140 (2010).
Kushnir, T. & Gopnik, A. Conditional probability versus spatial contiguity in causal learning: preschoolers use new contingency evidence to overcome prior spatial assumptions. Dev. Psychol. 43, 186–196 (2007).
Kimura, K. & Gopnik, A. Rational higher‐order belief revision in young children. Child. Dev. 90, 91–97 (2019).
Goddu, M. K. & Gopnik, A. Learning what to change: young children use “difference-making” to identify causally relevant variables. Dev. Psychol. 56, 275–284 (2020).
Gopnik, A. et al. Changes in cognitive flexibility and hypothesis search across human life history from childhood to adolescence to adulthood. Proc. Natl Acad. Sci. USA 114, 7892–7899 (2017).
Lucas, C. G., Bridgers, S., Griffiths, T. L. & Gopnik, A. When children are better (or at least more open-minded) learners than adults: developmental differences in learning the forms of causal relationships. Cognition 131, 284–299 (2014). This paper shows that young children learn and generalize unusual causal relationships more readily than adults do.
Goddu, M. K., Lombrozo, T. & Gopnik, A. Transformations and transfer: preschool children understand abstract relations and reason analogically in a causal task. Child. Dev. 91, 1898–1915 (2020).
Magid, R. W., Sheskin, M. & Schulz, L. E. Imagination and the generation of new ideas. Cogn. Dev. 34, 99–110 (2015).
Liquin, E. G. & Gopnik, A. Children are more exploratory and learn more than adults in an approach–avoid task. Cognition 218, 104940 (2022).
Erickson, J. E., Keil, F. C. & Lockhart, K. L. Sensing the coherence of biology in contrast to psychology: young children’s use of causal relations to distinguish two foundational domains. Child Dev. 81, 390–409 (2010).
Keil, F. C. Concepts, Kinds, and Cognitive Development (MIT Press, 1992).
Carey, S. Conceptual Change in Childhood (MIT Press, 1987).
Gelman, S. A. The Essential Child: Origins of Essentialism in Everyday Thought (Oxford Univ. Press, 2003).
Ahl, R. E., DeAngelis, E. & Keil, F. C. “I know it’s complicated”: children detect relevant information about object complexity. J. Exp. Child. Psychol. 222, 105465 (2022).
Chuey, A. et al. No guts, no glory: underestimating the benefits of providing children with mechanistic details. npj Sci. Learn. 6, 30 (2021).
Keil, F. C. & Lockhart, K. L. Beyond cause: the development of clockwork cognition. Curr. Dir. Psychol. Sci. 30, 167–173 (2021).
Chuey, A., Lockhart, K., Sheskin, M. & Keil, F. Children and adults selectively generalize mechanistic knowledge. Cognition 199, 104231 (2020).
Lockhart, K. L., Chuey, A., Kerr, S. & Keil, F. C. The privileged status of knowing mechanistic information: an early epistemic bias. Child Dev. 90, 1772–1788 (2019).
Kominsky, J. F., Zamm, A. P. & Keil, F. C. Knowing when help is needed: a developing sense of causal complexity. Cogn. Sci. 42, 491–523 (2018).
Mills, C. M. & Keil, F. C. Knowing the limits of one’s understanding: the development of an awareness of an illusion of explanatory depth. J. Exp. Child Psychol. 87, 1–32 (2004).
Goldwater, M. B. & Gentner, D. On the acquisition of abstract knowledge: structural alignment and explication in learning causal system categories. Cognition 137, 137–153 (2015).
Rottman, B. M., Gentner, D. & Goldwater, M. B. Causal systems categories: differences in novice and expert categorization of causal phenomena. Cogn. Sci. 36, 919–932 (2012).
Bonawitz, E. B. et al. Just do it? Investigating the gap between prediction and action in toddlers’ causal inferences. Cognition 115, 104–117 (2010). This study demonstrates that the ability to infer causal relations from observations of correlational information without an agent’s involvement or the use of causal language develops at around the age of four years.
Herrmann, E., Call, J., Hernández-Lloreda, M. V., Hare, B. & Tomasello, M. Humans have evolved specialized skills of social cognition: the cultural intelligence hypothesis. Science 317, 1360–1366 (2007).
Tomasello, M. Becoming Human: A Theory of Ontogeny (Harvard Univ. Press, 2019).
Henrich, J. The Secret of our Success (Princeton Univ. Press, 2015).
Hesslow, G. in Contemporary Science and Natural Explanation: Commonsense Conceptions of Causality (ed. Hilton, D. J.) 11–32 (New York Univ. Press, 1988).
Woodward, J. The problem of variable choice. Synthese 193, 1047–1072 (2016).
Khalid, S., Khalil, T. & Nasreen, S. A survey of feature selection and feature extraction techniques in machine learning. In 2014 Science and Information Conf. 372–378 (IEEE, 1988).
Bonawitz, E., Denison, S., Griffiths, T. L. & Gopnik, A. Probabilistic models, learning algorithms, and response variability: sampling in cognitive development. Trends Cogn. Sci. 18, 497–500 (2014).
Bonawitz, E., Denison, S., Gopnik, A. & Griffiths, T. L. Win–stay, lose–sample: a simple sequential algorithm for approximating Bayesian inference. Cogn. Psychol. 74, 35–65 (2014).
Denison, S., Bonawitz, E., Gopnik, A. & Griffiths, T. L. Rational variability in children’s causal inferences: the sampling hypothesis. Cognition 126, 285–300 (2013).
Samland, J., Josephs, M., Waldmann, M. R. & Rakoczy, H. The role of prescriptive norms and knowledge in children’s and adults’ causal selection. J. Exp. Psychol. Gen. 145, 125–130 (2016).
Samland, J. & Waldmann, M. R. How prescriptive norms influence causal inferences. Cognition 156, 164–176 (2016).
Phillips, J., Morris, A. & Cushman, F. How we know what not to think. Trends Cogn. Sci. 23, 1026–1040 (2019).
Gureckis, T. M. & Markant, D. B. Self-directed learning: a cognitive and computational perspective. Perspect. Psychol. Sci. 7, 464–481 (2012).
Saylor, M. & Ganea, P. Active Learning from Infancy to Childhood (Springer, 2018).
Goddu, M. K. & Gopnik, A. in The Cambridge Handbook of Cognitive Development (eds Houdé, O. & Borst, G.) 299–317 (Cambridge Univ. Press, 2022).
Gopnik, A. Scientific thinking in young children: theoretical advances, empirical research, and policy implications. Science 337, 1623–1627 (2012).
Weisberg, D. S. & Sobel, D. M. Constructing Science: Connecting Causal Reasoning to Scientific Thinking in Young Children (MIT Press, 2022).
Xu, F. Towards a rational constructivist theory of cognitive development. Psychol. Rev. 126, 841 (2019).
Xu, F. & Kushnir, T. Infants are rational constructivist learners. Curr. Dir. Psychol. Sci. 22, 28–32 (2013).
Lapidow, E. & Bonawitz, E. What’s in the box? Preschoolers consider ambiguity, expected value, and information for future decisions in explore-exploit tasks. Open. Mind 7, 855–878 (2023).
Kidd, C., Piantadosi, S. T. & Aslin, R. N. The Goldilocks effect: human infants allocate attention to visual sequences that are neither too simple nor too complex. PLoS One 7, e36399 (2012).
Ruggeri, A., Swaboda, N., Sim, Z. L. & Gopnik, A. Shake it baby, but only when needed: preschoolers adapt their exploratory strategies to the information structure of the task. Cognition 193, 104013 (2019).
Sim, Z. L. & Xu, F. Another look at looking time: surprise as rational statistical inference. Top. Cogn. Sci. 11, 154–163 (2019).
Sim, Z. L. & Xu, F. Infants preferentially approach and explore the unexpected. Br. J. Dev. Psychol. 35, 596–608 (2017).
Siegel, M. H., Magid, R. W., Pelz, M., Tenenbaum, J. B. & Schulz, L. E. Children’s exploratory play tracks the discriminability of hypotheses. Nat. Commun. 12, 3598 (2021).
Schulz, E., Wu, C. M., Ruggeri, A. & Meder, B. Searching for rewards like a child means less generalization and more directed exploration. Psychol. Sci. 30, 1561–1572 (2019).
Schulz, L. Infants explore the unexpected. Science 348, 42–43 (2015).
Perez, J. & Feigenson, L. Violations of expectation trigger infants to search for explanations. Cognition 218, 104942 (2022).
Cook, C., Goodman, N. D. & Schulz, L. E. Where science starts: spontaneous experiments in preschoolers’ exploratory play. Cognition 120, 341–349 (2011). This study demonstrates that preschoolers spontaneously perform causal interventions that are relevant to disambiguating multiple possible causal structures in their free play.
Lapidow, E. & Walker, C. M. Learners’ causal intuitions explain behavior in control of variables tasks. Dev. Psychol. (in the press).
Lapidow, E. & Walker, C. M. Rethinking the “gap”: self‐directed learning in cognitive development and scientific reasoning. Wiley Interdiscip. Rev. Cogn. Sci. 13, e1580 (2022). This theory paper provides a complementary viewpoint to ‘child-as-scientist’, or Bayesian ‘rational constructivist’, account, arguing that children seek to identify and generate evidence for causal relations that are robust across contexts (and thus will be reliable for causal intervention).
Lapidow, E. & Walker, C. M. Informative experimentation in intuitive science: children select and learn from their own causal interventions. Cognition 201, 104315 (2020).
Moeller, A., Sodian, B. & Sobel, D. M. Developmental trajectories in diagnostic reasoning: understanding data are confounded develops independently of choosing informative interventions to resolve confounded data. Front. Psychol. 13, 800226 (2022).
Fernbach, P. M., Macris, D. M. & Sobel, D. M. Which one made it go? The emergence of diagnostic reasoning in preschoolers. Cogn. Dev. 27, 39–53 (2012).
Buchanan, D. W. & Sobel, D. M. Mechanism‐based causal reasoning in young children. Child. Dev. 82, 2053–2066 (2011).
Sobel, D. M., Benton, D., Finiasz, Z., Taylor, Y. & Weisberg, D. S. The influence of children’s first action when learning causal structure from exploratory play. Cogn. Dev. 63, 101194 (2022).
Lapidow, E. & Walker, C. M. The Search for Invariance: Repeated Positive Testing Serves the Goals of Causal Learning (Springer, 2020).
Klayman, J. Varieties of confirmation bias. Psychol. Learn. Motiv. 32, 385–418 (1995).
Zimmerman, C. The development of scientific thinking skills in elementary and middle school. Dev. Rev. 27, 172–223 (2007).
Rule, J. S., Tenenbaum, J. B. & Piantadosi, S. T. The child as hacker. Trends Cogn. Sci. 24, 900–915 (2020).
Burghardt, G. M. The Genesis of Animal Play: Testing the Limits (MIT Press, 2005).
Chu, J. & Schulz, L. E. Play, curiosity, and cognition. Annu. Rev. Dev. Psychol. 2, 317–343 (2020).
Schulz, L. The origins of inquiry: inductive inference and exploration in early childhood. Trends Cogn. Sci. 16, 382–389 (2012).
Harris, P. L., Kavanaugh, R. D., Wellman, H. M. & Hickling, A. K. in Monographs of the Society for Research in Child Development https://doi.org/10.2307/1166074 (Society for Research in Child Development, 1993).
Weisberg, D. S. in The Oxford Handbook of the Development of Imagination (ed. Taylor, M.) 75–93 (Oxford Univ. Press, 2013).
Gopnik, A. & Walker, C. M. Considering counterfactuals: the relationship between causal learning and pretend play. Am. J. Play. 6, 15–28 (2013).
Weisberg, D. S. & Gopnik, A. Pretense, counterfactuals, and Bayesian causal models: why what is not real really matters. Cogn. Sci. 37, 1368–1381 (2013).
Root-Bernstein, M. M. in The Oxford Handbook of the Development of Imagination (ed. Taylor, M.) 417–437 (Oxford Univ. Press, 2013).
Buchsbaum, D., Bridgers, S., Skolnick Weisberg, D. & Gopnik, A. The power of possibility: causal learning, counterfactual reasoning, and pretend play. Phil. Trans. R. Soc. B 367, 2202–2212 (2012).
Wente, A., Gopnik, A., Fernández Flecha, M., Garcia, T. & Buchsbaum, D. Causal learning, counterfactual reasoning and pretend play: a cross-cultural comparison of Peruvian, mixed-and low-socioeconomic status US children. Phil. Trans. R. Soc. B 377, 20210345 (2022).
Buchsbaum, D., Gopnik, A., Griffiths, T. L. & Shafto, P. Children’s imitation of causal action sequences is influenced by statistical and pedagogical evidence. Cognition 120, 331–340 (2011).
Csibra, G. & Gergely, G. ‘Obsessed with goals’: functions and mechanisms of teleological interpretation of actions in humans. Acta Psychol. 124, 60–78 (2007).
Kelemen, D. The scope of teleological thinking in preschool children. Cognition 70, 241–272 (1999).
Casler, K. & Kelemen, D. Young children’s rapid learning about artifacts. Dev. Sci. 8, 472–480 (2005).
Casler, K. & Kelemen, D. Reasoning about artifacts at 24 months: the developing teleo-functional stance. Cognition 103, 120–130 (2007).
Ruiz, A. M. & Santos, L. R. 6. in Tool Use in Animals: Cognition and Ecology 119–133 (Cambridge Univ. Press, 2013).
Walker, C. M., Rett, A. & Bonawitz, E. Design drives discovery in causal learning. Psychol. Sci. 31, 129–138 (2020).
Butler, L. P. & Markman, E. M. Finding the cause: verbal framing helps children extract causal evidence embedded in a complex scene. J. Cogn. Dev. 13, 38–66 (2012).
Callanan, M. A. et al. Exploration, explanation, and parent–child interaction in museums. Monogr. Soc. Res. Child. Dev. 85, 7–137 (2020).
McHugh, S. R., Callanan, M., Jaeger, G., Legare, C. H. & Sobel, D. M. Explaining and exploring the dynamics of parent–child interactions and children’s causal reasoning at a children’s museum exhibit. Child Dev. https://doi.org/10.1111/cdev.14035 (2023).
Sobel, D. M., Letourneau, S. M., Legare, C. H. & Callanan, M. Relations between parent–child interaction and children’s engagement and learning at a museum exhibit about electric circuits. Dev. Sci. 24, e13057 (2021).
Willard, A. K. et al. Explain this, explore that: a study of parent–child interaction in a children’s museum. Child Dev. 90, e598–e617 (2019).
Daubert, E. N., Yu, Y., Grados, M., Shafto, P. & Bonawitz, E. Pedagogical questions promote causal learning in preschoolers. Sci. Rep. 10, 20700 (2020).
Yu, Y., Landrum, A. R., Bonawitz, E. & Shafto, P. Questioning supports effective transmission of knowledge and increased exploratory learning in pre‐kindergarten children. Dev. Sci. 21, e12696 (2018).
Walker, C. M. & Nyhout, A. in The Questioning Child: Insights From Psychology and Education (eds Butler, L. P., Ronfard, S. & Corriveau, K. H.) 252–280 (Cambridge Univ. Press, 2020).
Weisberg, D. S. & Hopkins, E. J. Preschoolers’ extension and export of information from realistic and fantastical stories. Infant. Child. Dev. 29, e2182 (2020).
Tillman, K. A. & Walker, C. M. You can’t change the past: children’s recognition of the causal asymmetry between past and future events. Child. Dev. 93, 1270–1283 (2022).
Rottman, B. M., Kominsky, J. F. & Keil, F. C. Children use temporal cues to learn causal directionality. Cogn. Sci. 38, 489–513 (2014).
Tecwyn, E. C., Mazumder, P. & Buchsbaum, D. One- and two-year-olds grasp that causes must precede their effects. Dev. Psychol. 59, 1519–1531 (2023).
Liquin, E. G. & Lombrozo, T. Explanation-seeking curiosity in childhood. Curr. Opin. Behav. Sci. 35, 14–20 (2020).
Mills, C. M., Legare, C. H., Bills, M. & Mejias, C. Preschoolers use questions as a tool to acquire knowledge from different sources. J. Cogn. Dev. 11, 533–560 (2010).
Ruggeri, A., Sim, Z. L. & Xu, F. “Why is Toma late to school again?” Preschoolers identify the most informative questions. Dev. Psychol. 53, 1620–1632 (2017).
Ruggeri, A. & Lombrozo, T. Children adapt their questions to achieve efficient search. Cognition 143, 203–216 (2015).
Legare, C. H. & Lombrozo, T. Selective effects of explanation on learning during early childhood. J. Exp. Child. Psychol. 126, 198–212 (2014).
Legare, C. H. Exploring explanation: explaining inconsistent evidence informs exploratory, hypothesis‐testing behavior in young children. Child Dev. 83, 173–185 (2012).
Walker, C. M., Lombrozo, T., Legare, C. H. & Gopnik, A. Explaining prompts children to privilege inductively rich properties. Cognition 133, 343–357 (2014).
Vasil, N., Ruggeri, A. & Lombrozo, T. When and how children use explanations to guide generalizations. Cogn. Dev. 61, 101144 (2022).
Walker, C. M., Bonawitz, E. & Lombrozo, T. Effects of explaining on children’s preference for simpler hypotheses. Psychon. Bull. Rev. 24, 1538–1547 (2017).
Walker, C. M. & Lombrozo, T. Explaining the moral of the story. Cognition 167, 266–281 (2017).
Walker, C. M., Lombrozo, T., Williams, J. J., Rafferty, A. N. & Gopnik, A. Explaining constrains causal learning in childhood. Child. Dev. 88, 229–246 (2017).
Gopnik, A. Childhood as a solution to explore–exploit tensions. Phil. Trans. R. Soc. B 375, 20190502 (2020).
Wente, A. O. et al. Causal learning across culture and socioeconomic status. Child. Dev. 90, 859–875 (2019).
Carstensen, A. et al. Context shapes early diversity in abstract thought. Proc. Natl Acad. Sci. USA 116, 13891–13896 (2019). This study provides evidence for developmentally early emerging cross-cultural differences in learning ‘individual’ versus ‘relational’ causal rules in children from individualist versus collectivist societies.
Ross, N., Medin, D., Coley, J. D. & Atran, S. Cultural and experiential differences in the development of folkbiological induction. Cogn. Dev. 18, 25–47 (2003).
Inagaki, K. The effects of raising animals on children’s biological knowledge. Br. J. Dev. Psychol. 8, 119–129 (1990).
Cole, M. & Bruner, J. S. Cultural differences and inferences about psychological processes. Am. Psychol. 26, 867–876 (1971).
Rogoff, B. & Morelli, G. Perspectives on children’s development from cultural psychology. Am. Psychol. 44, 343–348 (1989).
Rogoff, B. Adults and peers as agents of socialization: a highland Guatemalan profile. Ethos 9, 18–36 (1981).
Shneidman, L., Gaskins, S. & Woodward, A. Child‐directed teaching and social learning at 18 months of age: evidence from Yucatec Mayan and US infants. Dev. Sci. 19, 372–381 (2016).
Callanan, M., Solis, G., Castañeda, C. & Jipson, J. in The Questioning Child: Insights From Psychology and Education (eds Butler, L. P., Ronfard, S. & Corriveau, K. H.) 73–88 (Cambridge Univ. Press, 2020).
Gauvain, M., Munroe, R. L. & Beebe, H. Children’s questions in cross-cultural perspective: a four-culture study. J. Cross-Cult. Psychol. 44, 1148–1165 (2013).
Adolph, K. E. & Hoch, J. E. Motor development: embodied, embedded, enculturated, and enabling. Annu. Rev. Psychol. 70, 141–164 (2019).
Schleihauf, H., Herrmann, E., Fischer, J. & Engelmann, J. M. How children revise their beliefs in light of reasons. Child. Dev. 93, 1072–1089 (2022).
Vasil, N. et al. Structural explanations lead young children and adults to rectify resource inequalities. J. Exp. Child Psychol. 242, 105896 (2024).
Koskuba, K., Gerstenberg, T., Gordon, H., Lagnado, D. & Schlottmann, A. What’s fair? How children assign reward to members of teams with differing causal structures. Cognition 177, 234–248 (2018).
Bowlby, J. The Bowlby–Ainsworth attachment theory. Behav. Brain Sci. 2, 637–638 (1979).
Tottenham, N., Shapiro, M., Flannery, J., Caldera, C. & Sullivan, R. M. Parental presence switches avoidance to attraction learning in children. Nat. Hum. Behav. 3, 1070–1077 (2019).
Frankenhuis, W. E. & Gopnik, A. Early adversity and the development of explore–exploit tradeoffs. Trends Cogn. Sci. 27, 616–630 (2023).
Van IJzendoorn, M. H. & Kroonenberg, P. M. Cross-cultural patterns of attachment: a meta-analysis of the strange situation. Child Dev. 59, 147–156 (1988).
Gopnik, A. Explanation as orgasm. Minds Mach. 8, 101–118 (1998).
Gottlieb, S., Keltner, D. & Lombrozo, T. Awe as a scientific emotion. Cogn. Sci. 42, 2081–2094 (2018).
Valdesolo, P., Shtulman, A. & Baron, A. S. Science is awe-some: the emotional antecedents of science learning. Emot. Rev. 9, 215–221 (2017).
Keil, F. C. Wonder: Childhood and the Lifelong Love of Science (MIT Press, 2022).
Perez, J. & Feigenson, L. Stable individual differences in infants’ responses to violations of intuitive physics. Proc. Natl Acad. Sci. USA 118, e2103805118 (2021).
Goddu, M. K., Sullivan, J. N. & Walker, C. M. Toddlers learn and flexibly apply multiple possibilities. Child. Dev. 92, 2244–2251 (2021).
Cisek, P. Resynthesizing behavior through phylogenetic refinement. Atten. Percept. Psychophys. 81, 2265–2287 (2019).
Pezzulo, G. & Cisek, P. Navigating the affordance landscape: feedback control as a process model of behavior and cognition. Trends Cogn. Sci. 20, 414–424 (2016).
Cisek, P. Cortical mechanisms of action selection: the affordance competition hypothesis. Phil. Trans. R. Soc. B 362, 1585–1599 (2007).
Tomasello, M. The Evolution of Agency: Behavioral Organization From Lizards to Humans (MIT Press, 2022).
Beck, S. R., Robinson, E. J., Carroll, D. J. & Apperly, I. A. Children’s thinking about counterfactuals and future hypotheticals as possibilities. Child. Dev. 77, 413–426 (2006).
Robinson, E. J., Rowley, M. G., Beck, S. R., Carroll, D. J. & Apperly, I. A. Children’s sensitivity to their own relative ignorance: handling of possibilities under epistemic and physical uncertainty. Child. Dev. 77, 1642–1655 (2006).
Leahy, B. P. & Carey, S. E. The acquisition of modal concepts. Trends Cogn. Sci. 24, 65–78 (2020).
Mody, S. & Carey, S. The emergence of reasoning by the disjunctive syllogism in early childhood. Cognition 154, 40–48 (2016).
Shtulman, A. & Carey, S. Improbable or impossible? How children reason about the possibility of extraordinary events. Child Dev. 78, 1015–1032 (2007).
Redshaw, J. & Suddendorf, T. Children’s and apes’ preparatory responses to two mutually exclusive possibilities. Curr. Biol. 26, 1758–1762 (2016).
Phillips, J. S. & Kratzer, A. Decomposing modal thought. Psychol. Rev. (in the press).
Vetter, B. Abilities and the epistemology of ordinary modality. Mind (in the press).
Kahneman, D. & Tversky, A. Variants of uncertainty. Cognition 11, 143–157 (1982).
Rafetseder, E., Schwitalla, M. & Perner, J. Counterfactual reasoning: from childhood to adulthood. J. Exp. Child Psychol. 114, 389–404 (2013).
Beck, S. R. & Riggs, K. J. Developing thoughts about what might have been. Child Dev. Perspect. 8, 175–179 (2014).
Kominsky, J. F. et al. The trajectory of counterfactual simulation in development. Dev. Psychol. 57, 253 (2021). This study uses a physical collision paradigm to demonstrate that the content of children’s counterfactual judgements changes over development.
Gerstenberg, T. What would have happened? Counterfactuals, hypotheticals and causal judgements. Phil. Trans. R. Soc. B 377, 20210339 (2022).
Gerstenberg, T., Goodman, N. D., Lagnado, D. A. & Tenenbaum, J. B. A counterfactual simulation model of causal judgments for physical events. Psychol. Rev. 128, 936 (2021).
Nyhout, A. & Ganea, P. A. The development of the counterfactual imagination. Child Dev. Perspect. 13, 254–259 (2019).
Nyhout, A. & Ganea, P. A. Mature counterfactual reasoning in 4- and 5-year-olds. Cognition 183, 57–66 (2019).
Moll, H., Meltzoff, A. N., Merzsch, K. & Tomasello, M. Taking versus confronting visual perspectives in preschool children. Dev. Psychol. 49, 646–654 (2013).
Moll, H. & Tomasello, M. Three-year-olds understand appearance and reality — just not about the same object at the same time. Dev. Psychol. 48, 1124–1132 (2012).
Moll, H. & Meltzoff, A. N. How does it look? Level 2 perspective‐taking at 36 months of age. Child. Dev. 82, 661–673 (2011).
Gopnik, A., Slaughter, V. & Meltzoff, A. in Children’s Early Understanding of Mind: Origins and Development (eds Lewis, C. & Mitchell, P.) 157–181 (Routledge, 1994).
Gopnik, A. & Astington, J. W. Children’s understanding of representational change and its relation to the understanding of false belief and the appearance–reality distinction. Child Dev. 59, 26–37 (1988).
Doherty, M. & Perner, J. Metalinguistic awareness and theory of mind: just two words for the same thing? Cogn. Dev. 13, 279–305 (1998).
Wimmer, H. & Perner, J. Beliefs about beliefs: representation and constraining function of wrong beliefs in young children’s understanding of deception. Cognition 13, 103–128 (1983).
Flavell, J. H., Speer, J. R., Green, F. L., August, D. L. & Whitehurst, G. J. in Monographs of the Society for Research in Child Development 1–65 (Society for Research in Child Development, 1981).
Wellman, H. M., Cross, D. & Watson, J. Meta‐analysis of theory‐of‐mind development: the truth about false belief. Child. Dev. 72, 655–684 (2001).
Kelemen, D. & DiYanni, C. Intuitions about origins: purpose and intelligent design in children’s reasoning about nature. J. Cogn. Dev. 6, 3–31 (2005).
Kelemen, D. Why are rocks pointy? Children’s preference for teleological explanations of th natural world. Dev. Psychol. 35, 1440 (1999).
Vihvelin, K. Causes, Laws, and Free Will: Why Determinism Doesn’t Matter (Oxford Univ. Press, 2013).
Yiu, E., Kosoy, E. & Gopnik, A. Transmission versus truth, imitation versus innovation: what children can do that large language and language-and-vision models cannot (yet). Persp. Psychol. Sci. https://doi.org/10.1177/17456916231201401 (2023).
Kosoy, E. et al. Towards understanding how machines can learn causal overhypotheses. Preprint at arXiv https://doi.org/10.48550/arXiv.2206.08353 (2022).
Frank, M. C. Baby steps in evaluating the capacities of large language models. Nat. Rev. Psychol. 2, 451–452 (2023).
Frank, M. C. Bridging the data gap between children and large language models. Trends Cogn. Sci. 27, https://doi.org/10.1016/j.tics.2023.08.007 (2023).
Schmidhuber, J. A possibility for implementing curiosity and boredom in model-building neural controllers. In Proc. Int. Conf. on Simulation of Adaptive Behavior: From Animals to Animats 222–227 (MIT Press, 1991).
Volpi, N. C. & Polani, D. Goal-directed empowerment: combining intrinsic motivation and task-oriented behaviour. IEEE Trans. Cogn. Dev. Syst. 15, 361–372 (2020).
Salge, C., Glackin, C. & Polani, D. in Guided Self-Organization: Inception. Emergence, Complexity and Computation Vol. 9 (ed. Prokopenko, M.) 67–114 (Springer, 2014).
Klyubin, A. S., Polani, D. & Nehaniv, C. L. Empowerment: a universal agent-centric measure of control. In 2005 IEEE Congr. on Evolutionary Computation 128–135 (IEEE, 2005).
Gopnik, A. Empowerment as causal learning, causal learning as empowerment: a bridge between Bayesian causal hypothesis testing and reinforcement learning. Preprint at https://philsci-archive.pitt.edu/id/eprint/23268 (2024).
Rovee-Collier, C. K., Sullivan, M. W., Enright, M., Lucas, D. & Fagen, J. W. Reactivation of infant memory. Science 208, 1159–1161 (1980).
Kominsky, J. F., Li, Y. & Carey, S. Infants’ attributions of insides and animacy in causal interactions. Cogn. Sci. 46, e13087 (2022).
Lakusta, L. & Carey, S. Twelve-month-old infants’ encoding of goal and source paths in agentive and non-agentive motion events. Lang. Learn. Dev. 11, 152–175 (2015).
Saxe, R., Tzelnic, T. & Carey, S. Knowing who dunnit: infants identify the causal agent in an unseen causal interaction. Dev. Psychol. 43, 149–158 (2007).
Saxe, R., Tenenbaum, J. & Carey, S. Secret agents: inferences about hidden causes by 10- and 12-month-old infants. Psychol. Sci. 16, 995–1001 (2005).
Liu, S., Brooks, N. B. & Spelke, E. S. Origins of the concepts cause, cost, and goal in prereaching infants. Proc. Natl Acad. Sci. USA 116, 17747–17752 (2019).
Liu, S. & Spelke, E. S. Six-month-old infants expect agents to minimize the cost of their actions. Cognition 160, 35–42 (2017).
Nyhout, A. & Ganea, P. A. What is and what never should have been: children’s causal and counterfactual judgments about the same events. J. Exp. Child. Psychol. 192, 104773 (2020).
Legare, C. H. The contributions of explanation and exploration to children’s scientific reasoning. Child. Dev. Perspect. 8, 101–106 (2014).
Denison, S. & Xu, F. Twelve‐to 14‐month‐old infants can predict single‐event probability with large set sizes. Dev. Sci. 13, 798–803 (2010).
Denison, S., Reed, C. & Xu, F. The emergence of probabilistic reasoning in very young infants: evidence from 4.5-and 6-month-olds. Dev. Psychol. 49, 243 (2013).
Alderete, S. & Xu, F. Three-year-old children’s reasoning about possibilities. Cognition 237, 105472 (2023).
Scholl, B. J. & Tremoulet, P. D. Perceptual causality and animacy. Trends Cogn. Sci. 4, 299–309 (2000).
Hood, B., Carey, S. & Prasada, S. Predicting the outcomes of physical events: two‐year‐olds fail to reveal knowledge of solidity and support. Child. Dev. 71, 1540–1554 (2000).
Hood, B. M., Hauser, M. D., Anderson, L. & Santos, L. Gravity biases in a non‐human primate? Dev. Sci. 2, 35–41 (1999).
Hood, B. M. Gravity does rule for falling events. Dev. Sci. 1, 59–63 (1998).
Hood, B. M. Gravity rules for 2-to 4-year olds? Cognit. Dev. 10, 577–598 (1995).
Woodward, A. L. Infants selectively encode the goal object of an actor’s reach. Cognition 69, 1–34 (1998).
Woodward, A. L. Infants’ grasp of others’ intentions. Curr. Dir. Psychol. Sci. 18, 53–57 (2009).
Woodward, A. L., Sommerville, J. A., Gerson, S., Henderson, A. M. & Buresh, J. The emergence of intention attribution in infancy. Psychol. Learn. Motiv. 51, 187–222 (2009).
Meltzoff, A. N. ‘Like me’: a foundation for social cognition. Dev. Sci. 10, 126–134 (2007).
Gerson, S. A. & Woodward, A. L. The joint role of trained, untrained, and observed actions at the origins of goal recognition. Infant. Behav. Dev. 37, 94–104 (2014).
Gerson, S. A. & Woodward, A. L. Learning from their own actions: the unique effect of producing actions on infants’ action understanding. Child. Dev. 85, 264–277 (2014).
Sommerville, J. A., Woodward, A. L. & Needham, A. Action experience alters 3-month-old infants’ perception of others’ actions. Cognition 96, B1–B11 (2005).
Liu, S. & Almeida, M. Knowing before doing: review and mega-analysis of action understanding in prereaching infants. Psychol. Bull. 149, 294–310 (2023).
Acknowledgements
The authors acknowledge their funding sources: the Alexander von Humboldt Foundation, the Templeton World Charity Foundation (0434), the John Templeton Foundation (6145), the Defense Advanced Research Projects Agency (047498-002 Machine Common Sense), the Department of Defense Multidisciplinary University Initiative (Self-Learning perception Through Real World Interaction), and the Canadian Institute for Advanced Research Catalyst Award. For helpful discussions, comments, and other forms of support, the authors thank: S. Boardman, E. Bonawitz, B. Brast-McKie, D. Buchsbaum, M. Deigan, J. Engelmann, T. Friend, T. Gerstenberg, S. Kikkert, A. Kratzer, E. Lapidow, B. Leahy, T. Lombrozo, J. Phillips, H. Rakoczy, L. Schulz, D. Sobel, E. Spelke, H. Steward, B. Vetter, M. Waldmann and E. Yiu.
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M.K.G. wrote the article and created the figures. A.G. contributed substantially to discussion of the content and to multiple revisions. A.G. and M.K.G. together reviewed and edited the manuscript before submission.
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Goddu, M.K., Gopnik, A. The development of human causal learning and reasoning. Nat Rev Psychol (2024). https://doi.org/10.1038/s44159-024-00300-5
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DOI: https://doi.org/10.1038/s44159-024-00300-5
