Previous studies indicated that conditional predictions--the assessed probability that a certain outcome will occur given a certain condition--tend to be markedly inflated. Five experiments tested the effects of manipulations that were expected to alleviate this inflation by inducing participants to engage in analytic processing. Rewarding participants for accurate predictions proved ineffective. A training procedure in which participants assessed the likelihood of each of several outcomes before assessing the probability of a target outcome was partly effective in reducing overestimation. Most effective was the requirement to work in dyads and to come to an agreement about the assessed likelihood. Working in dyads helped alleviate prediction inflation even after participants made their individual predictions alone, and its debiasing effect also transferred to the estimates that were made individually on a new set of stimuli. The results were discussed in terms of the factors that make prediction inflation resistant to change.
