Modeling false consensus

A relevant component in the research on human reasoning is dominated by demonstrations of the errors people make in various judgment and decision making tasks. In group decision making problems, given the importance of obtaining an accepted solution by the whole group, the consensus has attained a great attention and it is virtually a major goal of these problems. In our study, the main novelty of the consensus model, which is modeled within fuzzy set theory by ordered weighted averaging operators, is that of being guided by both consensus and false consensus effects. False consensus refers to an egocentric bias that occurs when people estimate consensus for their own behaviors. The paper investigates the impact of the subjective contribution that cannot be eliminated: it seems hard that in a pool of experts none tends to overestimate own proper opinions, likely an expert necessarily is egocentric, just because he is an expert. What implies the presence of some false consensus effect.