Journal Article

Pacer, M., & Lombrozo, T. (2017). Ockham's razor cuts to the root: Simplicity in causal explanation. Journal of Experimental Psychology: General , 146 (12), 1761-1780. https://doi.org/10.1037/xge0000318Abstract
When evaluating causal explanations, simpler explanations are widely regarded as better explanations. However, little is known about how people assess simplicity in causal explanations or what the consequences of such a preference are. We contrast 2 candidate metrics for simplicity in causal explanations: node simplicity (the number of causes invoked in an explanation) and root simplicity (the number of unexplained causes invoked in an explanation). Across 4 experiments, we find that explanatory preferences track root simplicity, not node simplicity; that a preference for root simplicity is tempered (but not eliminated) by probabilistic evidence favoring a more complex explanation; that committing to a less likely but simpler explanation distorts memory for past observations; and that a preference for root simplicity is greater when the root cause is strongly linked to its effects. We suggest that a preference for root-simpler explanations follows from the role of explanations in highlighting and efficiently representing and communicating information that supports future predictions and interventions. (PsycINFO Database Record
Vasilyeva, N., Wilkenfeld, D., & Lombrozo, T. (2017). Contextual utility affects the perceived quality of explanations. Psychonomic Bulletin & Review , 24 (5), 1436-1450. https://doi.org/10.3758/s13423-017-1275-yAbstract
Are explanations of different kinds (formal, mechanistic, teleological) judged differently depending on their contextual utility, defined as the extent to which they support the kinds of inferences required for a given task? We report three studies demonstrating that the perceived "goodness" of an explanation depends on the evaluator's current task: Explanations receive a relative boost when they support task-relevant inferences, even when all three explanation types are warranted. For example, mechanistic explanations receive higher ratings when participants anticipate making further inferences on the basis of proximate causes than when they anticipate making further inferences on the basis of category membership or functions. These findings shed light on the functions of explanation and support pragmatic and pluralist approaches to explanation.
Walker, C. M., Bonawitz, E., & Lombrozo, T. (2017). Effects of explaining on children's preference for simpler hypotheses. Psychonomic Bulletin & Review , 24 (5), 1538-1547. https://doi.org/10.3758/s13423-016-1144-0Abstract
Research suggests that the process of explaining influences causal reasoning by prompting learners to favor hypotheses that offer "good" explanations. One feature of a good explanation is its simplicity. Here, we investigate whether prompting children to generate explanations for observed effects increases the extent to which they favor causal hypotheses that offer simpler explanations, and whether this changes over the course of development. Children aged 4, 5, and 6 years observed several outcomes that could be explained by appeal to a common cause (the simple hypothesis) or two independent causes (the complex hypothesis). We varied whether children were prompted to explain each observation or, in a control condition, to report it. Children were then asked to make additional inferences for which the competing hypotheses generated different predictions. The results revealed developmental differences in the extent to which children favored simpler hypotheses as a basis for further inference in this task: 4-year-olds did not favor the simpler hypothesis in either condition; 5-year-olds favored the simpler hypothesis only when prompted to explain; and 6-year-olds favored the simpler hypothesis whether or not they explained.
Walker, C. M., & Lombrozo, T. (2017). Explaining the moral of the story. Cognition , 167, 266-281. https://doi.org/10.1016/j.cognition.2016.11.007Abstract
Although storybooks are often used as pedagogical tools for conveying moral lessons to children, the ability to spontaneously extract "the moral" of a story develops relatively late. Instead, children tend to represent stories at a concrete level - one that highlights surface features and understates more abstract themes. Here we examine the role of explanation in 5- and 6-year-old children's developing ability to learn the moral of a story. Two experiments demonstrate that, relative to a control condition, prompts to explain aspects of a story facilitate children's ability to override salient surface features, abstract the underlying moral, and generalize that moral to novel contexts. In some cases, generating an explanation is more effective than being explicitly told the moral of the story, as in a more traditional pedagogical exchange. These findings have implications for moral comprehension, the role of explanation in learning, and the development of abstract reasoning in early childhood.
Walker, C. M., Lombrozo, T., Williams, J. J., Rafferty, A. N., & Gopnik, A. (2017). Explaining constrains causal learning in childhood. Child Development , 88 (1), 229-246. https://doi.org/10.1111/cdev.12590Abstract
Three experiments investigate how self-generated explanation influences children's causal learning. Five-year-olds (N = 114) observed data consistent with two hypotheses and were prompted to explain or to report each observation. In Study 1, when making novel generalizations, explainers were more likely to favor the hypothesis that accounted for more observations. In Study 2, explainers favored a hypothesis that was consistent with prior knowledge. Study 3 pitted a hypothesis that accounted for more observations against a hypothesis consistent with prior knowledge. Explainers were more likely to base generalizations on prior knowledge. Findings suggest that attempts to explain drive children to evaluate hypotheses using features of "good" explanations, or those supporting generalizations with broad scope, as informed by children's prior knowledge and observations.
Giffin, C., & Lombrozo, T. (2016). Wrong or merely prohibited: Special treatment of strict liability in intuitive moral judgment. Law and Human Behavior , 40 (6), 707-720.Abstract
Most crimes in America require that the defendant have mens rea, Latin for "guilty mind." However, mens rea is not legally required for strict liability crimes, such as speeding, for which someone is guilty even if ignorant or deceived about her speed. In 3 experiments involving participants responding to descriptive vignettes, we investigated whether the division of strict liability crimes in the law reflects an aspect of laypeople's intuitive moral cognition. Experiment 1 (N = 396; 236 male, 159 female, 1 other; M = 30) found evidence that it does: ignorance and deception were less mitigating for strict liability crimes than for "mens rea" crimes. Experiments 2 (N = 413; 257 male, 154 female, 2 other; M = 31) and 3 (N = 404; 183 male, 221 female, M = 35) revealed that strict liability crimes are not treated as pure moral violations, but additionally as violations of convention. We found that for strict liability crimes, ratings of moral wrongness and punishment were influenced to a greater extent by the fact that a rule had been violated, even when harm was kept constant, mirroring the legal distinction of malum prohibitum (wrong as prohibited) versus malum in se (wrong in itself). Further, we found that rules prohibiting strict liability crimes were judged more arbitrary than corresponding rules for "mens rea" crimes, and that this judgment was related to the role of mental states. Jointly, the findings suggest a surprising correspondence between the law and laypeople's intuitive judgments. (PsycINFO Database Record
Lombrozo, T. (2016). Explanatory preferences shape learning and inference. Trends in Cognitive Sciences , 20 (10), 748-759. https://doi.org/10.1016/j.tics.2016.08.001Abstract
Explanations play an important role in learning and inference. People often learn by seeking explanations, and they assess the viability of hypotheses by considering how well they explain the data. An emerging body of work reveals that both children and adults have strong and systematic intuitions about what constitutes a good explanation, and that these explanatory preferences have a systematic impact on explanation-based processes. In particular, people favor explanations that are simple and broad, with the consequence that engaging in explanation can shape learning and inference by leading people to seek patterns and favor hypotheses that support broad and simple explanations. Given the prevalence of explanation in everyday cognition, understanding explanation is therefore crucial to understanding learning and inference.
Ruggeri, A., Lombrozo, T., Griffiths, T. L., & Xu, F. (2016). Sources of developmental change in the efficiency of information search. Developmental Psychology , 52 (12), 2159-2173. http://dx.doi.org/10.1037/dev0000240Abstract
Children are active learners: they learn not only from the information people offer and the evidence they happen to observe, but by actively seeking information. However, children's information search strategies are typically less efficient than those of adults. In two studies, we isolate potential sources of developmental change in how children (7- and 10-year-olds) and adults search for information. To do so, we develop a hierarchical version of the 20-questions game, in which participants either ask questions (Study 1) or test individual objects (Study 2) to discover which category of objects within a nested structure (e.g., animals, birds, or owls) has a novel property. We also develop a computational model of the task, which allows us to evaluate performance in quantitative terms. As expected, we find developmental improvement in the efficiency of information search. In addition, we show that participants' performance exceeds random search, but falls short of optimal performance. We find mixed support for the idea that children's inefficiency stems from difficulty thinking beyond the level of individual objects or hypotheses. Instead, we reveal a previously undocumented source of developmental change: Children are significantly more likely than adults to continue their search for information beyond the point at which a single hypothesis remains, and thus to ask questions and select objects associated with zero information gain. This suggests that one crucial source of developmental change in information search efficiency lies in children's "stopping rules." (PsycINFO Database Record
Wilkenfeld, D. A., Plunkett, D., & Lombrozo, T. (2016). Depth and deference: When and why we attribute understanding. Philosophical studies , 173 (2), 373–393 . Springer. https://doi.org/10.1007/s11098-015-0497-yAbstract
Four experiments investigate the folk concept of ‘‘understanding,’’ in particular when and why it is deployed differently from the concept of knowledge. We argue for the positions that (1) people have higher demands with respect to explanatory depth when it comes to attributing understanding, and (2) that this is true, in part, because understanding attributions play a functional role in identifying experts who should be heeded with respect to the general field in question. These claims are supported by our findings that people differentially withhold attributions of understanding (rather than knowledge) when the object of attribution has minimal explanatory information. We also show that this tendency significantly correlates with people’s willingness to defer to others as potential experts. This work bears on a pressing issue in epistemology concerning the place and value of understanding. Our results also provide reason against positing a simple equation of knowledge(- why) and understanding(-why). We contend that, because deference plays a crucial role in many aspects of everyday reasoning, the fact that we use understanding attributions to demarcate experts reveals a potential mechanism for achieving our epistemic aims in many domains.
Ruggeri, A., & Lombrozo, T. (2015). Children adapt their questions to achieve efficient search. Cognition , 143, 203-216. https://doi.org/10.1016/j.cognition.2015.07.004Abstract
One way to learn about the world is by asking questions. We investigate how younger children (7- to 8-year-olds), older children (9- to 11-year-olds), and young adults (17- to 18-year-olds) ask questions to identify the cause of an event. We find a developmental shift in children's reliance on hypothesis-scanning questions (which test hypotheses directly) versus constraint-seeking questions (which reduce the space of hypotheses), but also that all age groups ask more constraint-seeking questions when hypothesis-scanning questions are least likely to pay off: When the solution is one among equally likely alternatives (Study 1) or when the problem is difficult (Studies 1 and 2). These findings are the first to demonstrate that even young children dynamically adapt their strategies for inquiry to increase the efficiency of information search.
Wilkenfeld, D. A., & Lombrozo, T. (2015). Inference to the best explanation (IBE) versus explaining for the best inference (EBI). Science & Education , 24 (9-10), 1059–1077 . Springer. https://doi.org/10.1007/s11191-015-9784-4Abstract
In pedagogical contexts and in everyday life, we often come to believe something because it would best explain the data. What is it about the explanatory endeavor that makes it essential to everyday learning and to scientific progress? There are at least two plausible answers. On one view, there is something special about having true explanations. This view is highly intuitive: it’s clear why true explanations might improve one’s epistemic position. However, there is another possibility—it could be that the process of seeking, generating, or evaluating explanations itself puts one in a better epistemic position, even when the outcome of the process is not a true explanation. In other words, it could be that accurate explanations are beneficial, or it could be that high-quality explaining is beneficial, where there is something about the activity of looking for an explanation that improves our epistemic standing. The main goal of this paper is to tease apart these two possibilities, both theoretically and empirically, which we align with ‘‘Inference to the Best Explanation’’ (IBE) and ‘‘Explaining for the Best Inference’’ (EBI), respectively. We also provide some initial support for EBI and identify promising directions for future research.
Legare, C. H., & Lombrozo, T. (2014). Selective effects of explanation on learning during early childhood. Journal of Experimental Child Psychology , 126, 198-212. https://doi.org/10.1016/j.jecp.2014.03.001Abstract
Two studies examined the specificity of effects of explanation on learning by prompting 3- to 6-year-old children to explain a mechanical toy and comparing what they learned about the toy's causal and non-causal properties with children who only observed the toy, both with and without accompanying verbalization. In Study 1, children were experimentally assigned to either explain or observe the mechanical toy. In Study 2, children were classified according to whether the content of their response to an undirected prompt involved explanation. Dependent measures included whether children understood the toy's functional-mechanical relationships, remembered perceptual features of the toy, effectively reconstructed the toy, and (for Study 2) generalized the function of the toy when constructing a new one. Results demonstrate that across age groups, explanation promotes causal learning and generalization but does not improve (and in younger children can even impair) memory for causally irrelevant perceptual details.
Lombrozo, T., & Gwynne, N. Z. (2014). Explanation and inference: mechanistic and functional explanations guide property generalization. Frontiers in Human Neuroscience , 8 700. https://doi.org/10.3389/fnhum.2014.00700Abstract
The ability to generalize from the known to the unknown is central to learning and inference. Two experiments explore the relationship between how a property is explained and how that property is generalized to novel species and artifacts. The experiments contrast the consequences of explaining a property mechanistically, by appeal to parts and processes, with the consequences of explaining the property functionally, by appeal to functions and goals. The findings suggest that properties that are explained functionally are more likely to be generalized on the basis of shared functions, with a weaker relationship between mechanistic explanations and generalization on the basis of shared parts and processes. The influence of explanation type on generalization holds even though all participants are provided with the same mechanistic and functional information, and whether an explanation type is freely generated (Experiment 1), experimentally provided (Experiment 2), or experimentally induced (Experiment 2). The experiments also demonstrate that explanations and generalizations of a particular type (mechanistic or functional) can be experimentally induced by providing sample explanations of that type, with a comparable effect when the sample explanations come from the same domain or from a different domains. These results suggest that explanations serve as a guide to generalization, and contribute to a growing body of work supporting the value of distinguishing mechanistic and functional explanations.
Walker, C. M., Lombrozo, T., Legare, C. H., & Gopnik, A. (2014). Explaining prompts children to privilege inductively rich properties. Cognition , 133 (2), 343-57. https://doi.org/10.1016/j.cognition.2014.07.008Abstract
Four experiments with preschool-aged children test the hypothesis that engaging in explanation promotes inductive reasoning on the basis of shared causal properties as opposed to salient (but superficial) perceptual properties. In Experiments 1a and 1b, 3- to 5-year-old children prompted to explain during a causal learning task were more likely to override a tendency to generalize according to perceptual similarity and instead extend an internal feature to an object that shared a causal property. Experiment 2 replicated this effect of explanation in a case of label extension (i.e., categorization). Experiment 3 demonstrated that explanation improves memory for clusters of causally relevant (non-perceptual) features, but impairs memory for superficial (perceptual) features, providing evidence that effects of explanation are selective in scope and apply to memory as well as inference. In sum, our data support the proposal that engaging in explanation influences children's reasoning by privileging inductively rich, causal properties.
Harvey, A. G., Soehner, A., Lombrozo, T., Bélanger, L., Rifkin, J., & Morin, C. M. (2013). 'Folk theories' about the causes of insomnia. Cognitive Therapy and Research , 37 (5). https://doi.org/10.1007/s10608-013-9543-2Abstract
The present study investigates 'folk theories' about the causes of insomnia. Participants with insomnia ( = 69) completed a qualitative and quantitative assessment of their folk theories. The qualitative assessment was to speak aloud for 1 minute in response to: 'What do you think causes your insomnia?'. The quantitative assessment involved completing the 'Causal Attributions of My Insomnia Questionnaire' (CAM-I), developed for this study. The three most common folk theories for both the causes of one's own insomnia as well as insomnia in others were 'emotions', 'thinking patterns' and 'sleep-related emotions'. Interventions targeting these factors were also perceived as most likely to be viable treatments. Seventy-five percent of the folk theories of insomnia investigated with the CAM-I were rated as more likely to be alleviated by a psychological versus a biological treatment. The results are consistent with research highlighting that folk theories are generally coherent and inform a range of judgments. Future research should focus on congruence of 'folk theories' between treatment providers and patients, as well as the role of folk theories in treatment choice, engagement, compliance and outcome.

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