This chapter focuses on how we induce properties of the world. Some psychologists have been coming back to the view that induction is mediated by causal models — causal models that are often generated online through the application of causal principles, abstract causal relations that have general applicability. Such causal models help to explain how people make inductive inferences when the inference can be conceived as a causal effect, as in the ‘bananas have it; therefore, monkeys have it’ example. In other cases, inference involves analogy: a predicate is applied to one category because it is known to apply to an analogous category, as in the ‘tigers do it; therefore, hawks do it’ example. In such cases, the analogy seems to be between causal structures. Finally, causal models give a psychologically plausible way to think about why people sometimes show sensitivity to statistical information. Instead of assuming that people calculate statistics like measures of the variability of a property, the requisite information can be interpreted as a property's centrality in a causal model.
Keywords: deduction, causal models, causal knowledge, causal relations, inference