Abstract
We don't learn about each person we meet from scratch: Our knowledge of social groups (e.g., cognitive scientists) shapes our expectations about new individuals (e.g., the reader). Here we explore how 4- and 5-year-old children and adults use minimal statistical evidence about social groups to support inductive inferences about individuals. Overall, we find that both children and adults readily infer the preferences and group membership of new individuals when they have appropriate evidence to support these inferences. However, our results also suggest that children and adults interpret this information in different ways. Adults' responses align closely with a Bayesian model that assumes that each group's preferences are independent of one another. By contrast, we find preliminary evidence that children's inferences about the preferences of new group members are sensitive to the composition (Experiment 1) and size (Experiment 2) of the opposing group. Our work provides insights into how people form structured, generalizable representations of social groups from sparse data.
Original language | English (US) |
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Pages | 227-233 |
Number of pages | 7 |
State | Published - 2020 |
Externally published | Yes |
Event | 42nd Annual Meeting of the Cognitive Science Society: Developing a Mind: Learning in Humans, Animals, and Machines, CogSci 2020 - Virtual, Online Duration: Jul 29 2020 → Aug 1 2020 |
Conference
Conference | 42nd Annual Meeting of the Cognitive Science Society: Developing a Mind: Learning in Humans, Animals, and Machines, CogSci 2020 |
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City | Virtual, Online |
Period | 7/29/20 → 8/1/20 |
All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Computer Science Applications
- Human-Computer Interaction
- Cognitive Neuroscience
Keywords
- cognitive development
- social groups
- statistical reasoning