Four experiments examined the locus of impact of causal knowledge on consideration of alternative hypotheses in judgments under uncertainty. Two possible loci were examined; overcoming neglect of the alternative when developing a representation of a judgment problem and improving utilization of statistics associated with the alternative hypothesis. In Experiment 1, participants could search for information about the various components of Bayes's rule in a diagnostic problem. A majority failed to spontaneously search for information about an alternative hypothesis, but this bias was reduced when a specific alternative hypothesis was mentioned before search. No change in search patterns was found when a generic alternative cause was mentioned. Experiments 2a and 2b broadly replicated these patterns when participants rated or made binary judgments about the relevance of each of the Bayesian components. In contrast, Experiment 3 showed that when participants were given the likelihood of the data given a focal hypothesis p(D|H) and an alternative hypothesis p(D|¬H), they gave estimates of p(H|D) that were consistent with Bayesian principles. Additional causal knowledge had relatively little impact on such judgments. These results show that causal knowledge primarily affects neglect of the alternative hypothesis at the initial stage of problem representation.