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Towards a rational theory of human information acquisition

Introduction Many situations require judiciously choosing particular pieces of information to acquire before otherwise acting. Consider the case of a scientist studying gravity. Dropping an apple from a bridge, to see whether it will fall, is a possible experiment. But it does not appear to be a useful experiment, perhaps because all plausible theories predict the apple will fall. In a Bayesian optimal experimental design (OED) framework, simply testing predictions of various theories does not constitute good science. Rather, possible experiments are judged useful to the extent that plausible competing theories make contradictory predictions about the results. Beginning roughly 1980, psychologists began to use OED theories of the value of information as normative (theoretically optimal) or descriptive models of human queries and intuitions about the value of information (Table 7.10). Examples of scenarios studied include people's intuitions about what medical tests are most useful (Baron et al., 1988), about what features would be most helpful to categorize objects (Skov & Sherman, 1986; Slowiaczek et al., 1992), and about what cards are most useful on Wason's selection task (Klayman & Ha, 1987; Oaksford & Chater, 1994); human eye movements for learning an object's shape (Walker-Renninger et al., 2005), for finding an object hidden in noise (Najemnik & Geisler, 2005), or for categorization (Nelson & Cottrell, 2007); and monkeys' eye movements to query the location of a hidden target (Nakamura, 2006). In life, of course, information gathering is frequently also coupled with other goals 144 distribution of a food source, while simultaneously maximizing immediate energy intake. Similarly, a physician diagnosing an illness would want to balance the expected informational value of diagnostic tests with their monetary cost and possible harm to the patient. (An expensive test that deposits large quantities of radiation on the patient, such as a CT scan, should be avoided if an inexpensive blood test provides equivalent information.) It would be inappropriate to build mathematical models of these situations based solely on information gathering; the other goals must also be incorporated. There is evidence that in some situations people can optimize fairly arbitrary utility functions (Trommershäuser et al., 2003) and that in other situations, people have difficulty doing so (Baron & Hershey, 1988). In this chapter, however, our focus is on situations in which information gathering is the only goal. A unified theory of information gathering might be possible in these situations, depending on the consistency of intuitions across …