Naïve realism and capturing the “wisdom of dyads”

a r t i c l e i n f o Two studies provided evidence for the role of naïve realism in the failure of individuals to give adequate weight to peer input, and explored two strategies for reducing the impact of this inferential bias. Study 1 demonstrated that dyad members see their own estimates as more " objective " than those of their partners and that this difference in perceived objectivity predicts the degree of underweighting. Compelling participants to assess their own versus their partners' objectivity prior to revising estimates decreased under-weighting, an effect that was mediated by differences in perceived objectivity. Study 2 showed that the increase in accuracy that results from requiring dyad members to offer joint estimates via discussion is largely retained in subsequent individual estimates. Both studies showed that underweighting is greater when dyad members disagree on the issue about which they are making consensus estimates—a finding that further supports a " naïve realism " interpretation of the phenomenon. Introduction In making important life decisions people are often required to decide how much weight to give to the input of colleagues, friends, or family members. However, there is mounting evidence that individuals typically fail to give due weight to the input of others, and consequently fail to reap the full benefits of collaboration (for a recent review see Bonaccio & Dalal, 2006). The present studies were designed to explore the role of " naïve realism "—the conviction that we see matters " objectively " and that insofar as others disagree, it is due to error or " bias " —in producing this underweighting phenomenon. We propose that the fundamental belief in our own objectivity is one of the reasons why individuals consistently give too much weight to their own judgments relative to the weight that they give to the judgments of others. The history of work on individual versus aggregated numerical judgments is a long one. Early studies, reviewed by Lorge, Fox, Davitz, and Brenner (1958), showed that the error associated with the average of a large number of estimates (whether of room temperature , the number of jelly beans in a jar, or the date of the forthcoming World War II armistice), was inevitably smaller than the average individual error. It was these findings, and the underlying statistical insight, that were rediscovered by Surowiecki (2004) in The Wisdom of Crowds. Despite the well-documented benefits …