ArticlePLoS computational biology2017
Learning about and from others' prudence, impatience or laziness: The computational bases of attitude alignment.
Article in PLoS computational biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Article
- Social learning dynamically shapes moral decision-making by biasing subjective valuation.PLoS biology · 2026Article
- Self-other generalisation shapes social interaction and is disrupted in borderline personality disorder.eLife · 2025Article
- Older adults are relatively more susceptible to impulsive social influence than young adults.Communications psychology · 2024Article
- Humans can infer social preferences from decision speed alone.PLoS biology · 2024Article
- Learning rules of engagement for social exchange within and between groups.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- The social contagion of work avoidance goals in school and its influence on student (dis)engagement.European journal of psychology of education = Journal europeen de psychologie de l'education · 2022Article
- How conformity can lead to polarised social behaviour.PLoS computational biology · 2021Article
- Improving Self-Control: The Influence of Role Models on Intertemporal Choices.Frontiers in psychology · 2019Article
- The application of computational models to social neuroscience: promises and pitfalls.Social neuroscience · 2018Review
- Accounting for Taste: A Multi-Attribute Neurocomputational Model Explains the Neural Dynamics of Choices for Self and Others.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2018Article
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Authors and funding
2 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Peoples' subjective attitude towards costs such as, e.g., risk, delay or effort are key determinants of inter-individual differences in goal-directed behaviour. Thus, the ability to learn about others' prudent, impatient or lazy attitudes is likely to be critical for social interactions. Conversely, how adaptive such attitudes are in a given environment is highly uncertain. Thus, the brain may be tuned to garner information about how such costs ought to be arbitrated. In particular, observing others' attitude may change one's uncertain belief about how to best behave in related difficult decision contexts. In turn, learning from others' attitudes is determined by one's ability to learn about others' attitudes. We first derive, from basic optimality principles, the computational properties of such a learning mechanism. In particular, we predict two apparent cognitive biases that would arise when individuals are learning about others' attitudes: (i) people should overestimate the degree to which they resemble others (false-consensus bias), and (ii) they should align their own attitudes with others' (social influence bias). We show how these two biases non-trivially interact with each other. We then validate these predictions experimentally by profiling people's attitudes both before and after guessing a series of cost-benefit arbitrages performed by calibrated artificial agents (which are impersonating human individuals).
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.