Iterated learning: Intergenerational knowledge transmission reveals inductive biases
Open accessAbstract
Cultural transmission of information plays a central role in shaping human knowledge. Some of the most complex knowledge that people acquire, such as languages or cultural norms, can only be learned from other people, who themselves learned from previous generations. The prevalence of this process of "iterated learning" as a mode of cultural transmission raises the question of how it affects the information being transmitted. Analyses of iterated learning utilizing the assumption that the learners are Bayesian agents predict that this process should converge to an equilibrium that reflects the inductive biases of the learners. An experiment in iterated function learning with human participants confirmed this prediction, providing insight into the consequences of intergenerational knowledge transmission and a method for discovering the inductive biases that guide human inferences.
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Iterated interaction can be considered to generate Markov chains in the long-run, which gives a well-formed framework to analyze the asymptotic effects of local decisions.
“It is known that iterated interaction can be considered to generate Markov chains in the long-run, which gives us a well-formed framework to analyze the asymptotic effects of local decision [72, 74].”
From Evolution and impact of bias in human and machine learning algorithm interaction (2020) · cites this paper as [74]
When encountering similar challenges, human culture might preserve diversity by utilizing biases with counteracting effects, such as endorsing local conformity.
“By contrast, when encountering similar challenges, human culture might preserve diversity by utilizing biases with counteracting effects, such as endorsing local conformity 166 .”
From Machine culture (2023) · cites this paper as [166]
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- Authors
- Kalish, M. L., Griffiths, T. L., & Lewandowsky, S.
- Affiliations
- University of Louisiana at Lafayette (US)
- University of California, Berkeley (US)
- The University of Western Australia (AU)
- Corresponding author
- Kalish, Michael L.
- Venue
- Psychonomic Bulletin & Review
- Published
- 2007-04
- Volume
- 14
- Issue
- 2
- Pages
- 288-294
- ISSN
- 1069-9384 (ISSN-L)
- 1531-5320
- OpenAlex
- W2079988037
- Cited by
- 220
- References
- 52
- Citations by year
- 2026: 2 · 2025: 7 · 2024: 13 · 2023: 13 · 2022: 12 · 2021: 16 · 2020: 16 · 2019: 12 · 2018: 21 · 2017: 10 · 2016: 13 · 2015: 12 · 2014: 14 · 2013: 6 · 2012: 7
- FWCI
- 236.07
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Psychonomic Bulletin & Review (publishedVersion)
- PubMed (publishedVersion)
- UWA Profiles and Research Repository (UWA) (submittedVersion)
- Explore Bristol Research (submittedVersion)
- Topics
- Social Sciences › Cultural Studies › Language and cultural evolution
- Social Sciences › Psychology › Developmental and Educational Psychology › Child and Animal Learning Development
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Categorization, perception, and language
- Keywords
- iterated learning, cultural transmission, intergenerational knowledge transmission, inductive bias, Bayesian agents, human inference, language acquisition
- MeSH terms
- Humans, Learning, Models, Psychological, Periodicity, Intergenerational Relations, Knowledge
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