A key purpose of causal reasoning by individuals and by collectives is to enhance action, to give humans yet more control over their environment. As a result, causal reasoning serves as the infrastructure of both thought and discourse. Humans represent causal systems accurately in some ways, but also show some systematic biases (we tend to neglect causal pathways other than the one we are thinking about). Even when accurate, people’s understanding of causal systems tends to be superficial; we depend on our communities for most of our causal knowledge and reasoning. Nevertheless, we are better causal reasoners than machines. Modern machine learners do not come close to matching human abilities.

The seminar will first outline the architecture of the human mind, specifying general and domain-specific mental processes. The place of causal reasoning and its relations with the other processes will be specified. Experimental, psychometric, developmental, and brain-based evidence will be summarized. The main message of the talk is that causal thought involves domain-specific core processes rooted in perception and served by special brain networks which capture interactions between objects. With development, causal reasoning is increasingly associated with a general abstraction system which generates general principles underlying inductive, analogical, and deductive reasoning and also heuristics for specifying causal relations. These associations are discussed in some detail. Possible implications for artificial intelligence and educational implications are also discussed.