Does the most common response given by participants presented with Tversky and Kahneman’s famous taxi cab problem amount to a violation of Bayes’ theorem? In other words, do they fall victim to so-called base-rate fallacy? In the present paper, following an earlier suggestion by Crupi and Girotto, we will identify the logical arguments underlying both the original diagnosis of irrationality in this reasoning task under uncertainty and a number of objections that have been raised against such a diagnosis. This will (...) enable us to show firstly that, contrary to the dismissive arguments recently put forward by Elqayam and Evans, empirical evidence turns out to be quite useful in addressing questions of this kind. Therefore, it can make a significant contribution to moving the base-rate fallacy controversy forward. Secondly, the available empirical evidence (though limited and sometimes inconclusive) seems to support the charge of irrationality levelled against the majority of participants presented with the taxi cab problem, and hence suggests that base-rate neglect is a real fallacy − that is the conclusion of our analysis. (shrink)

Bayesian approaches to human cognition have been extensively advocated in the last decades, but sharp objections have been raised too within cognitive science. In this paper, we outline a diagnosis of what has gone wrong with the prevalent strand of Bayesian cognitive science (here labelled pure Bayesian cognitive science), relying on selected illustrations from the psychology of reasoning and tools from the philosophy of science. Bayesians’ reliance on so-called method of rational analysis is a key point of our discussion. We (...) tentatively conclude on a constructive note, though: an appropriately modified variant of Bayesian cognitive science can still be coherently pursued, as some scholars have noted. (shrink)

Inductive reasoning requires exploiting links between evidence and hypotheses. This can be done focusing either on the posterior probability of the hypothesis when updated on the new evidence or on the impact of the new evidence on the credibility of the hypothesis. But are these two cognitive representations equally reliable? This study investigates this question by comparing probability and impact judgments on the same experimental materials. The results indicate that impact judgments are more consistent in time and more accurate than (...) probability judgments. Impact judgments also predict the direction of errors in probability judgments. These findings suggest that human inductive reasoning relies more on estimating evidential impact than on posterior probability. (shrink)