Modeling Cross-Domain Causal Learning in Preschoolers as Bayesian Inference

Modeling Cross-Domain Causal Learning in Preschoolers as Bayesian Inference Elizabeth Baraff Bonawitz (liz_b@mit.edu) Department of Brain and Cognitive Sciences Massachusetts Institute of Technology Cambridge, MA 02139 USA Thomas L. Griffiths (tom_griffiths@brown.edu) Laura Schulz (lschulz@mit.edu) Department of Cognitive and Linguistic Sciences Brown University Providence, RI 02912 USA Department of Brain and Cognitive Sciences Massachusetts Institute of Technology Cambridge, MA 02139 USA Abstract might interact. In this paper, we provide a formal account of this interaction as rational Bayesian inference and then present two experiments in support of this account suggesting that preschoolers can integrate domain- appropriate prior knowledge with domain-general patterns of evidence. This study investigates the interaction between preschoolers’ initial theories and their ability to learn causal relations from patterns of data. Children observed ambiguous evidence in which sets of two candidate causes co-occurred with an effect (e.g. AB in another condition, the recurring candidate cause, A, crossed domains (a psychological cause for a biological effect). When all causes were domain- appropriate, children were able to use the data to identify A as a cause. When the recurring cause crossed domains, children were less likely to endorse A. However, preschoolers were significantly more willing to accept cross-domain causes after seeing the evidence than at baseline. A Bayesian model is proposed to explain this interaction. Theories and Evidence In the literature on causal learning in children, some studies seem to suggest the relative strength of domain- specific knowledge over domain general learning mechanisms while other findings suggest the opposite. Of the few studies that have directly compared domain- specific and domain-general causal learning, some have suggested that both adults and children privilege domain- specific information over domain-general evidence (e.g., Ahn, Kalish, Medin, & Gelman, 1995; Bullock, Gelman & Baillargeon, 1982; Shultz, 1982). Shultz (1982) for instance, suggests that preschoolers base their causal judgments on knowledge about domain-appropriate mechanisms of transmission rather than evidence of temporal covariation. By contrast, other research suggests that children can use domain general learning mechanisms (such as the conditional probability of events) to override domain boundaries (Schulz & Gopnik, 2004). For example, children can use patterns of evidence to determine that a psychological rather than a physical cause produces a physical effect (Schulz & Gopnik, 2004). Though see Andersson (1986) and Boo and Watson (2001) for examples of over-generalizations of domain general causal notions. It has been difficult to evaluate the interaction between domain-specific knowledge and domain-general learning mechanisms, because previous work has focused on extreme points. For example, in the Shultz (1982) studies, children were asked to make a judgment after a single instance of temporal co-occurrence, thus there was little room for covariation evidence to affect children’s naive theories. By contrast, in the Schulz and Gopnik (2004) studies, the covariation data unambiguously supported the domain-inappropriate cause so there was Very young children have remarkably sophisticated causal knowledge about the world. Children reason about the causes of mental states (e.g., Meltzoff, 1995), physical systems (e.g., Bullock, Gelman, & Baillargeon, 1982; Shultz, 1982), and biological events (e.g., Gelman & Wellman, 1991; Kalish, 1996). Preschoolers can even make predictions about hidden variables and explain events in terms of unobservable causes (Schulz & Sommerville, in press). Many researchers have suggested that children’s causal knowledge can be characterized as intuitive theories: abstract, coherent, defeasible representations of causal structure (Carey, 1985; Gopnik & Meltzoff, 1997; Wellman, 1990; Keil, 1989). However, relatively little is known about the process of causal learning. While some researchers have suggested that children’s naive theories might be instantiated in domain-specific modules (Leslie, 1994; Scholl & Leslie, 1999) or innate concepts in core domains (Carey & Spelke, 1994; Keil, 1995), other researchers have emphasized the role of domain-general learning mechanisms (Gopnik et al., 2004; Schulz & Gopnik, 2004). Very little research (though see Sobel, Tenenbaum, & Gopnik, 2004) has looked at how domain- specific beliefs and domain-general learning mechanisms