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Conformist social learning leads to self-organised prevention against adverse bias in risky decision making
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 beha...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9090329/ https://www.ncbi.nlm.nih.gov/pubmed/35535494 http://dx.doi.org/10.7554/eLife.75308 |
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author | Toyokawa, Wataru Gaissmaier, Wolfgang |
author_facet | Toyokawa, Wataru Gaissmaier, Wolfgang |
author_sort | Toyokawa, Wataru |
collection | PubMed |
description | 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 585 human subjects, that conformist influence can indeed promote favourable risk taking in repeated experience-based 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 differential equation model of collective behavioural dynamics 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 behavioural flexibility under conformist influences. |
format | Online Article Text |
id | pubmed-9090329 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-90903292022-05-11 Conformist social learning leads to self-organised prevention against adverse bias in risky decision making Toyokawa, Wataru Gaissmaier, Wolfgang eLife Computational and Systems Biology 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 585 human subjects, that conformist influence can indeed promote favourable risk taking in repeated experience-based 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 differential equation model of collective behavioural dynamics 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 behavioural flexibility under conformist influences. eLife Sciences Publications, Ltd 2022-05-10 /pmc/articles/PMC9090329/ /pubmed/35535494 http://dx.doi.org/10.7554/eLife.75308 Text en © 2022, Toyokawa and Gaissmaier https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Computational and Systems Biology Toyokawa, Wataru Gaissmaier, Wolfgang Conformist social learning leads to self-organised prevention against adverse bias in risky decision making |
title | Conformist social learning leads to self-organised prevention against adverse bias in risky decision making |
title_full | Conformist social learning leads to self-organised prevention against adverse bias in risky decision making |
title_fullStr | Conformist social learning leads to self-organised prevention against adverse bias in risky decision making |
title_full_unstemmed | Conformist social learning leads to self-organised prevention against adverse bias in risky decision making |
title_short | Conformist social learning leads to self-organised prevention against adverse bias in risky decision making |
title_sort | conformist social learning leads to self-organised prevention against adverse bias in risky decision making |
topic | Computational and Systems Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9090329/ https://www.ncbi.nlm.nih.gov/pubmed/35535494 http://dx.doi.org/10.7554/eLife.75308 |
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