The evolution of distorted beliefs vs. mistaken choices under asymmetric error costs.
Cultural evolution
error management theory
herding
hyperactive agency detection
social learning
Journal
Evolutionary human sciences
ISSN: 2513-843X
Titre abrégé: Evol Hum Sci
Pays: England
ID NLM: 101773423
Informations de publication
Date de publication:
2020
2020
Historique:
medline:
20
5
2020
pubmed:
20
5
2020
entrez:
17
8
2023
Statut:
epublish
Résumé
Why do people sometimes hold unjustified beliefs and make harmful choices? Three hypotheses include (a) contemporary incentives in which some errors cost more than others, (b) cognitive biases evolved to manage ancestral incentives with variation in error costs and (c) social learning based on choice frequencies. With both modelling and a behavioural experiment, we examined all three mechanisms. The model and experiment support the conclusion that contemporary cost asymmetries affect choices by increasing the rate of cheap errors to reduce the rate of expensive errors. Our model shows that a cognitive bias can distort the evolution of beliefs and in turn behaviour. Unless the bias is strong, however, beliefs often evolve in the correct direction. This suggests limitations on how cognitive biases shape choices, which further indicates that detecting the behavioural consequences of biased cognition may sometimes be challenging. Our experiment used a prime intended to activate a bias called 'hyperactive agency detection', and the prime had no detectable effect on choices. Finally, both the model and experiment show that frequency-dependent social learning can generate choice dynamics in which some populations converge on widespread errors, but this outcome hinges on the other two mechanisms being neutral with respect to choice.
Identifiants
pubmed: 37588359
doi: 10.1017/ehs.2020.25
pii: S2513843X20000250
pmc: PMC10427456
doi:
Types de publication
Journal Article
Langues
eng
Pagination
e27Informations de copyright
© The Author(s) 2020.
Déclaration de conflit d'intérêts
CE is a member of the editorial board at Evolutionary Human Sciences.
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