Dynamical-System Model Predicts When Social Learners Impair Collective Performance

TL;DR

This paper presents a dynamical system model that predicts when social learning impairs collective decision-making, showing that high proportions of social learners can lead to suboptimal choices depending on initial conditions and conformity responses.

Contribution

It introduces a novel mathematical framework integrating cognitive strategies, task properties, and social influence to analyze collective decisions in social systems.

Findings

Bi-stable states emerge when social learners exceed a critical threshold.

Below the threshold, the majority favors the higher-merit option.

The critical threshold depends on conformity response and option merits.

Abstract

A key question concerning collective decisions is whether a social system can settle on the best available option when some members learn from others instead of evaluating the options on their own. This question is challenging to study, and previous research has reached mixed conclusions, because collective decision outcomes depend on the insufficiently understood complex system of cognitive strategies, task properties, and social influence processes. This study integrates these complex interactions together in one general yet partially analytically tractable mathematical framework using a dynamical system model. In particular, it investigates how the interplay of the proportion of social learners, the relative merit of options, and the type of conformity response affect collective decision outcomes in a binary choice. The model predicts that when the proportion of social learners exceeds a critical threshold, a bi-stable state appears in which the majority can end up favoring either the higher- or lower-merit option, depending on fluctuations and initial conditions. Below this threshold, the high-merit option is chosen by the majority. The critical threshold is determined by the conformity response function and the relative merits of the two options. The study helps reconcile disagreements about the effect of social learners on collective performance and proposes a mathematical framework that can be readily adapted to extensions investigating a wider variety of dynamics.