Collective problem decomposition improves the wisdom of deliberative crowds

Abstract

Abstract Understanding when and why social interaction improves human judgment is a central question in the behavioural sciences. We examine whether collective accuracy improves when groups break complex estimation problems into simpler components and generate approximate intermediate estimates, a reasoning strategy we call Collective Fermi Estimation. Across three studies analysing 1140 online group deliberations in text chatrooms we study its causal effects and linguistic signatures. In Study 1 (N = 500), spontaneous use of problem decomposition predicts lower collective estimation error. Study 2 (N = 240) provides causal evidence: groups instructed to apply problem decomposition outperform groups instructed to combine their initial guesses. Study 3 (N = 160) shows that the benefits are larger when the strategy is applied collectively rather than individually. Altogether, we show that problem decomposition constitutes a key mechanism behind the wisdom of deliberative crowds and we provide tools to detect and promote it.