The refinement paradox and cumulative cultural evolution: Complex products of collective improvement favor conformist outcomes, blind copying, and hyper-credulity.


Journal

PLoS computational biology
ISSN: 1553-7358
Titre abrégé: PLoS Comput Biol
Pays: United States
ID NLM: 101238922

Informations de publication

Date de publication:
Sep 2024
Historique:
received: 25 03 2024
accepted: 21 08 2024
medline: 26 9 2024
pubmed: 26 9 2024
entrez: 26 9 2024
Statut: epublish

Résumé

Social learning is common in nature, yet cumulative culture (where knowledge and technology increase in complexity and diversity over time) appears restricted to humans. To understand why, we organized a computer tournament in which programmed entries specified when to learn new knowledge and when to refine (i.e. improve) existing knowledge. The tournament revealed a 'refinement paradox': refined behavior afforded higher payoffs as individuals converged on a small number of successful behavioral variants, but refining did not generally pay. Paradoxically, entries that refined only in certain conditions did best during behavioral improvement, while simple copying entries thrived when refinement levels were high. Cumulative cultural evolution may be rare in part because sophisticated strategies for improving knowledge and technology are initially advantageous, yet complex culture, once achieved, favors conformity, blind imitation and hyper-credulity.

Identifiants

pubmed: 39325687
doi: 10.1371/journal.pcbi.1012436
pii: PCOMPBIOL-D-24-00507
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e1012436

Informations de copyright

Copyright: © 2024 Miu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

Auteurs

Elena Miu (E)

School of Biology, University of St Andrews, St Andrews, United Kingdom.
School of Human Evolution and Social Change, Arizona State University, Tempe, Arizona, United States of America.
MPI for Evolutionary Anthropology, Leipzig, Germany.
Department of Archaeology and Heritage Studies, Aarhus University, Aarhus, Denmark.

Luke Rendell (L)

School of Biology, University of St Andrews, St Andrews, United Kingdom.

Sam Bowles (S)

The Santa Fe Institute, Santa Fe, New Mexico, United States of America.

Rob Boyd (R)

School of Human Evolution and Social Change, Arizona State University, Tempe, Arizona, United States of America.

Daniel Cownden (D)

Ingrooves Music Group, Victoria, British Columbia, Canada.

Magnus Enquist (M)

University of Stockholm, Stockholm, Sweden.

Kimmo Eriksson (K)

University of Stockholm, Stockholm, Sweden.

Marcus W Feldman (MW)

Department of Biology, Stanford University, Stanford, California, United States of America.

Timothy Lillicrap (T)

Google DeepMind, London, United Kingdom.

Richard McElreath (R)

MPI for Evolutionary Anthropology, Leipzig, Germany.

Stuart Murray (S)

School of Biology, University of St Andrews, St Andrews, United Kingdom.
School of Medicine, University of St Andrews, St Andrews, United Kingdom.

James Ounsley (J)

School of Biology, University of St Andrews, St Andrews, United Kingdom.
Marine Scotland Science, Freshwater Fisheries Laboratory, Pitlochry, United Kingdom.

Kevin N Lala (KN)

School of Biology, University of St Andrews, St Andrews, United Kingdom.

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Classifications MeSH