Ralph Hertwig

This chapter analyzes how valuable the assumption of systematic environment imbalance is for performing rough-and-ready intuitive estimates, which people regularly do when inferring the quantitative value of an object (e.g., its frequency, size, value, or quality). The chapter outlines how systematic environment imbalance can be quantified using the framework of power laws. It investigates to what extent power-law characteristics and other statistical properties of real-world environments can be allies of two simple estimation heuristics, QuickEst and the mapping heuristic. The analyses, which involve comparing the estimation performances of the heuristics relative to more complex strategies, demonstrate that QuickEst could be particularly suited for deriving rough-and-ready estimates in skewed distributions with highly dispersed cue validities, whereas the mapping heuristic might be most suited when the cues have similar validities.

Theorists ranging from William James (1890) to some contemporary psychologists have argued that forgetting is the key to proper functioning of memory. The authors elaborate on the notion of beneficial forgetting by proposing that loss of information aids inference heuristics that exploit mnemonic information. They demonstrate this by implementing the recognition and fluency heuristics for two-alternative choice within the ACT-R cognitive architecture. For the recognition heuristic, forgetting can boost accuracy by increasing the chances that only a single alternative is recognized. Simulations of the fluency heuristic, choosing based on the speed with which the alternatives are recognized, indicate that forgetting aids the discrimination between recognition speeds. The authors show that retrieval fluency can be a proxy for real-world quantities, that people can discriminate between two objects’ retrieval fluencies, and that people’s inferences are in line with the fluency heuristic.