Learning Whom to Trust : Decision-Generated Credibility in Social Learning
How people's confidence in their own choices shapes whom others trust.
When people learn from each other, they naturally pay more attention to confident sources—but this can backfire. A mathematical model of learning agents reveals a dangerous pattern: moderate information sharing helps groups correct early mistakes, but strong social influence can trap entire populations in a shared wrong belief. The model also identifies a paradox: confidence helps people learn better when making private decisions, yet the same confidence makes false ideas spread faster among groups.
Online platforms and social networks amplify the voices of confident speakers, often regardless of accuracy. This work predicts exactly when that amplification helps versus harms collective understanding—and suggests that limiting how widely confident wrong ideas travel could prevent communities from locking into large-scale false consensus.