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Children use algorithm induction to discover patterns in data
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DOI：10.1038/s41467-026-73029-9.png)
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Abstract
En 中文
Humans are unique in our ability to acquire diverse skills and inhabit myriad environments, but the cognitive mechanisms underlying such fast, flexible learning remain unresolved. Inspired by theories of artificial intelligence, here we show evidence for one such learning mechanism - program induction - in US American and indigenous Tsimane’ children in the Bolivian Amazon. Participants viewed novel patterns and were asked to generalize them to new stimuli, alphabets, and lengths, without feedback. Given very limited data, participants across ages, cultures, and conditions constructed response patterns that shared abstract structure with the sample patterns. Computational modeling shows that responses likely reflect discovery of latent rules, rather than simple heuristics or associations, even among children without formal schooling. The results suggest program induction serves as a domain-general learning mechanism from early in life, allowing children across cultures to rapidly infer the algorithmic structure of their natural and cultural environment, whatever it might be. Humans are extraordinarily fast, flexible learners. Here, the authors show evidence that this capacity is powered by a general-purpose learning mechanism that allows children across cultures to discover patterns in data, even without instruction.
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