Hostname: page-component-586b7cd67f-dlnhk Total loading time: 0 Render date: 2024-11-23T05:48:56.106Z Has data issue: false hasContentIssue false
  • English
  • Français

Representational exchange in social learning: Blurring the lines between the ritual and instrumental

Published online by Cambridge University Press:  10 November 2022

Natalia Vélez Open the ORCID record for Natalia Vélez [Opens in a new window] ,
Charley M. Wu Open the ORCID record for Charley M. Wu [Opens in a new window]  and
Fiery A. Cushman Open the ORCID record for Fiery A. Cushman [Opens in a new window]
Natalia Vélez
Affiliation:
Department of Psychology, Harvard University, Cambridge, MA 02138, USA [email protected], [email protected] nataliavelez.org, cushmanlab.fas.harvard.edu
Charley M. Wu
Affiliation:
Human and Machine Cognition Lab, University of Tübingen, 72076 Tübingen, Germany, [email protected], hmc-lab.com
Fiery A. Cushman
Affiliation:
Department of Psychology, Harvard University, Cambridge, MA 02138, USA [email protected], [email protected] nataliavelez.org, cushmanlab.fas.harvard.edu
Get access Rights & Permissions [Opens in a new window]

Abstract

We propose that human social learning is subject to a trade-off between the cost of performing a computation and the flexibility of its outputs. Viewing social learning through this lens sheds light on cases that seem to violate bifocal stance theory (BST) – such as high-fidelity imitation in instrumental action – and provides a mechanism by which causal insight can be bootstrapped from imitation of cultural practices.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 45 , 2022 , e271
Check for updates
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Achan, J., Talisuna, A. O., Erhart, A., Yeka, A., Tibenderana, J. K., Baliraine, F. N., … D'Alessandro, U. (2011). Quinine, an old anti-malarial drug in a modern world: Role in the treatment of malaria. Malaria Journal, 10, 144.CrossRefGoogle Scholar
Cushman, F. (2020). Rationalization is rational. The Behavioral and Brain Sciences, 43, e28.CrossRefGoogle Scholar
Henrich, J. (2015). The secret of our success. Princeton University Press.CrossRefGoogle Scholar
Kool, W., Gershman, S. J., & Cushman, F. A. (2018). Planning complexity registers as a cost in metacontrol. Journal of Cognitive Neuroscience, 30(10), 1391–1404.CrossRefGoogle Scholar
Leach, K. (2022). Unpublished doctoral thesis. Harvard University.Google Scholar
Lewry, C., Curtis, K., Vasilyeva, N., Xu, F., & Griffiths, T. L. (2021). Intuitions about magic track the development of intuitive physics. Cognition, 214, 104762.CrossRefGoogle ScholarPubMed
Lieder, F., & Griffiths, T. L. (2020). Resource-rational analysis: Understanding human cognition as the optimal use of limited computational resources. Behavioral and Brain Sciences, 43, e1.CrossRefGoogle Scholar
Luft, D. (2020). Medieval Welsh medical texts: Volume one: The recipes. University of Wales Press.Google ScholarPubMed
McCoy, J., & Ullman, T. (2019). Judgments of effort for magical violations of intuitive physics. PLoS ONE, 14(5), e0217513.CrossRefGoogle ScholarPubMed
Shenhav, A., Musslick, S., Lieder, F., Kool, W., Griffiths, T. L., Cohen, J. D., & Botvinick, M. M. (2017). Toward a rational and mechanistic account of mental effort. Annual Review of Neuroscience, 40, 99–124.CrossRefGoogle Scholar
Wu, C. M., Vélez, N., & Cushman, F. A. (2022). Representational exchange in human social learning: Balancing efficiency and flexibility. In Dezza, I. C., Schulz, E., & Wu, C. M. (Eds.), The drive for knowledge: The science of human information-seeking (pp. 169–192). Cambridge University Press.CrossRefGoogle Scholar