Considering Psychological Mechanisms Can Change the Interpretation of Bayesian Models

A significant challenge for Bayesian models of cognition is understanding how the abstract assumptions behind these models connect to psychological mechanisms. We examine the consequences of considering one of the psychological processes involved in inductive inference: generating hypotheses. We analyze the predictions of a simple model that separates the processes of generating hypotheses and evaluating those hypotheses. This analysis shows that the ease of generating a hypothesis and its plausibility are confounded if we simply analyze people's behavior in terms of Bayesian inference without taking the underlying mechanisms into account. We then establish through three experiments that the processes of generation and evaluation are separable and that influencing the ease of hypothesis generation has different consequences from simply manipulating the plausibility of a hypothesis. These experiments produce results that could not be accounted for by a Bayesian model that assumes people assign a fixed prior probability to hypotheses.