Toyokawa W, and Gaissmaier W. (2021) Conformist social learning leads to self-organised prevention against adverse bias in risky decision making. bioRxiv. https://doi.org/10.1101/2021.02.22.432286 [Code: https://github.com/WataruToyokawa/ToyokawaGaissmaier2021]

Given the ubiquity of potentially adverse behavioural bias owing to myopic trial-and-error learning, it seems paradoxical that improvements in decision-making performance through conformist social learning, a process widely considered to be bias amplification, still prevail in animal collective behaviour. Here we show, through model analyses and large-scale interactive behavioural experiments with 467 human subjects, that conformist influence can indeed promote favourable risk taking in repeated risky decision making, even though many individuals are systematically biased towards adverse risk aversion. Although strong positive feedback conferred by copying the majority’s behaviour could result in unfavourable informational cascades, our dynamic model of collective behaviour identified a key role for increasing exploration by negative feedback arising when a weak minority influence undermines the inherent behavioural bias. This ‘collective behavioural rescue’, emerging through coordination of positive and negative feedback, highlights a benefit of collective learning in a broader range of environmental conditions than previously assumed and resolves the ostensible paradox of adaptive collective flexibility under conformist influences.