Visions of rationality Valerie

Firefighters predict how fires will progress from cues such as smoke and roof 'sponginess' 1 , while peahens use the elabo-rateness of peacocks' tails to infer their fitness before deciding whether to mate with them 2. The cues on which organisms base their inductive inferences are typically uncertain: the old adage aside, sometimes there's no smoke even where there's fire. How do people make inferences, and are their inferences rational? Most researchers of inference share a vision of rationality whose roots trace back to the Enlightenment. This now classical view holds that the laws of human inference are equivalent to the laws of probability and logic. For French astronomer Pierre Laplace, for example, probability theory embodied human intuition: 'The theory of probability is at bottom nothing more than good sense reduced to a calculus' 3. Nineteenth-century German philosopher Theodor Lipps wrote that logic 'is nothing if not the physics of thought' 4. So fundamental was the belief that the mind worked by the rules of probability and logic that when human intuition was observed to deviate from them, the rules themselves were revised 5. In short, many pre-20th-century thinkers believed that the psychological defines the rational. Variants of the classical view have flourished in 20th-century psychology. Many researchers maintain the belief that the laws of probability theory and logic at least approximately describe human inference. In the view of Cameron Peterson and Lee Beach, for example: 'Probability theory and statistics can be used as the basis for psychological models that integrate and account for human performance in a wide range of inferential tasks' 6. According to Jean Piaget, cognitive development culminates in a set of logico-mathematical abilities that essentially reflect the laws of probability and logic. More recently, Lance Rips has argued for the existence of 'mental logic' 7. Finally, rational-choice theo-rists and economists often model people's decisions using probability theory as an approximation (e.g. Refs 8,9). Unlike their Enlightenment predecessors, however, these modern researchers see classical models as norms against which human reasoning can be evaluated rather than as codifications of it: when the two diverge, it is concluded that there is something wrong with the reasoning, not with the norms. In the past 25 years, the idea that human inference can be either defined or described by probability theory and logic has been increasingly challenged. Proponents of the heuristics-and-biases program have argued that inference is systematically biased and …