Year: 2023
Type: preprint
Abstract: The aggregation of many lay judgements generates surprisingly accurate estimates. This phenomenon, called the “wisdom of crowds”, has been demonstrated in domains such as medical decision making and financial forecasting. Previous research identified two factors driving this effect: the accuracy of individual assessments and the diversity of opinions. Most available strategies to enhance the wisdom of crowds have focused on improving individual accuracy while neglecting the potential of increasing opinion diversity. Here, we study a complementary approach to reduce collective error by promoting erroneous divergent opinions. This strategy proposes to anchor half of the crowd to a small value and the other half to a large value before eliciting and averaging all estimates. Consistent with our mathematical modeling, four experiments (N=1362 adults) demonstrate that this method is effective for estimation and forecasting tasks. Beyond practical implications, these findings offer new theoretical insights into the epistemic value of collective decision making.
Institutions: Consejo Nacional de Investigaciones Científicas y Técnicas, Universidad Torcuato Di Tella, Universidad de Buenos Aires, Royal Holloway University of London, Max Planck Institute for Human Development, Ludwig-Maximilians-Universität München, University of London, School of Advanced Study, Institute of Philosophy
Language: English
Subfield: General Decision Sciences
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W4385837464