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Self-organised collective intelligence with consistently risk averse individuals| title | Self-organised collective intelligence with consistently risk averse individuals |
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| start_date | 2023/03/16 |
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| schedule | 14h |
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| online | no |
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| location_info | salle Langevin |
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| summary | Conventional models of collective intelligence rely on individuals making unbiased, at least partially informed decisions. However, animal decision making through repeated experience may often be biassed due to the constraints in information sampling (so-called the hot stove effect). Considering the ubiquity of conformist social learning, a process widely considered to be bias-amplification, it seems paradoxical that improvements in decision-making performance under social influences still prevail. How can animals overcome the potentially suboptimal bias collectively? 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 biassed 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” 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. |
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| responsibles | Palminteri |
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Workflow history| from state (1) | to state | comment | date |
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| submitted | published | | 2023/02/28 13:59 UTC |
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