Cognition, Behavior, and Memory
Author: Federico Barrera-Lemarchand | Email: fedex192@gmail.com
Federico Barrera-Lemarchand1°2°3°, Joaquín Navajas1°3°4°
1° Laboratorio de Neurociencia – Escuela de Negocios – Universidad Torcuato Di Tella
2° Departamento de Física – FCEN – Universidad de Buenos Aires
3° Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET)
4° Escuela de Negocios – Universidad Torcuato Di Tella
The aggregation of many lay judgments can lead to surprisingly accurate estimates. This phenomenon, called the “wisdom of crowds,” has been employed successfully in various domains, such as medical decision-making, predicting geo-political events, and financial forecasting. Previous research identified two key 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 behavioral experiments (N =1,362) provide converging evidence of the efficacy of the proposed method for both estimation and forecasting tasks. Beyond practical implications, these findings offer new theoretical insights into the epistemic value of collective decision-making.