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Little Bayesians or little Einsteins? Probability and explanatory virtue in children's inferences
Author(s) -
Johnston Angie M.,
Johnson Samuel G.B.,
Koven Marissa L.,
Keil Frank C.
Publication year - 2017
Publication title -
developmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.801
H-Index - 127
eISSN - 1467-7687
pISSN - 1363-755X
DOI - 10.1111/desc.12483
Subject(s) - psychology , odds , bayesian probability , scope (computer science) , bayesian inference , normative , cognitive psychology , inference , posterior probability , econometrics , epistemology , statistics , logistic regression , artificial intelligence , computer science , mathematics , philosophy , programming language
Like scientists, children seek ways to explain causal systems in the world. But are children scientists in the strict Bayesian tradition of maximizing posterior probability? Or do they attend to other explanatory considerations, as laypeople and scientists – such as Einstein – do? Four experiments support the latter possibility. In particular, we demonstrate in four experiments that 4‐ to 8‐year‐old children, like adults, have a robust latent scope bias that leads to inferences that do not maximize posterior probability. When faced with two explanations equally consistent with observed data, where one explanation makes an unverified prediction, children consistently preferred the explanation that does not make this prediction (Experiment 1), even if the prior probabilities are identical (Experiment 3). Additional evidence suggests that this latent scope bias may result from the same explanatory strategies used by adults (Experiments 1 and 2), and can be attenuated by strong prior odds (Experiment 4). We argue that children, like adults, rely on ‘explanatory virtues’ in inference – a strategy that often leads to normative responses, but can also lead to systematic error.