In standard decision theory, rational agents are objective, keeping their beliefs independent from their desires (Berger, 1985). Such agents are the basis for current computational models of Theory of Mind (ToM), but this fundamental as- sumption of the theory remains untested. Do people think that others’ beliefs are objective, or do they think that others’ de- sires color their beliefs? We describe a Bayesian framework for exploring this relationship and its implications. Motivated by this analysis, we conducted two experiments testing the a priori independence of beliefs and desires in people’s ToM and find that, contrary to fully-normative accounts, people think that others engage in wishful thinking. In the first ex- periment, we found that people think others believe both that desirable events are more likely to happen, and that undesir- able ones are less likely to happen. In the second experiment, we found that social learning leverages this intuitive under- standing of wishful thinking: participants learned more from the beliefs of an informant whose desires were contrary to his beliefs. People’s ToM therefore appears to be more nuanced than the current rational accounts, but consistent with a model in which desire directly affects the subjective probability of an event.

What constitutes good teaching, and what factors do learners consider when evaluating teachers? Prior developmental work suggests that even young children accurately recognize and evaluate under-informativeness. Building on prior work, we propose a Bayesian model of teacher evaluation that infers the teacher’s quality from how carefully he selected demonstrations given what he knew. We test the predictions of our model across 15 conditions in which participants saw a teacher who demonstrated all or a subset of functions of a novel device and rated his helpfulness. Our results suggest that human adults seamlessly integrate information about the number of functions taught, their values, as well as what the teacher knew, to make nuanced judgments about the quality of teaching; the quantitative pattern is well predicted by our model