Collaborative Research: Knowledge Transmission Through Iterated Learning

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Much of human knowledge is not learned from the physical world around us, but from other people. For example, each new generation of physicists does not have to rediscover the laws of Newtonian mechanics; these laws are passed on from one physicist to the next. This same kind of "iterated learning" occurs for language, music, and other kinds of complex knowledge that are not easily relearned from scratch, so to speak. Despite the ubiquity of iterated learning in human culture and society, very little is known about the cognitive processes by which knowledge changes when it is transmitted from one person to the next. With support from the National Science Foundation, Dr. Kalish and Dr. Griffiths will investigate this issue by testing and extending theories that unify the mathematics of cultural evolution with the processes of human cognition. They will conduct a series of experiments that are designed to reproduce the processes of iterated learning in a laboratory environment, and the experiments will be complemented by the development of computational models designed to test the theoretical predictions against the observed learning data. The main issue is whether relatively small perturbations in knowledge that may occur in the act of transmission will or will not add up to have large effects over the course of many iterations. The results of these experiments promise to provide us with some important and general constraints on theories of human cognition, as well as theories of cultural transmission of knowledge.