Egocentric Tendencies in Theory of Mind Reasoning: An Empirical and Computational Analysis

AbstractHumans develop an ability for Theory of Mind (ToM) by the age of six, which enables them to infer another agent's mental state and to differentiate it from one's own. Much evidence suggests that humans can do this in a presumably optimal way and, correspondingly, a Bayesian Theory of Mind (BToM) framework has been shown to match human inferences and attributions. Mostly, this has been investigated with specific, explicit mentalizing tasks. However, other research has shown that humans often deviate from optimal reasoning in various ways. We investigate whether typical BToM models really capture human ToM reasoning in tasks that solicit more intuitive reasoning. We present results of an empirical study where humans deviate from Bayesian optimal reasoning in a ToM task but instead exhibit egocentric tendencies. We also discuss how computational models can better account for such sub-optimal processing.

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