This article described three heuristics that are employed in making judgements under uncertainty: representativeness, which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process B; availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development; and adjustment from an anchor, which is usually employed in numerical prediction when a relevant value (...) is available. These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors. A better understanding of these heuristics and of the biases to which they lead could improve judgements and decisions in situations of uncertainty. (shrink)

The program of research now known as the heuristics and biases approach began with a study of the statistical intuitions of experts, who were found to be excessively confident in the replicability of results from small samples. The persistence of such systematic errors in the intuitions of experts implied that their intuitive judgments may be governed by fundamentally different processes than the slower, more deliberate computations they had been trained to execute. The ancient idea that cognitive processes can be partitioned (...) into two main families--traditionally called intuition and reason--is now widely embraced under the general label of dual-process theories. Dual-process models come in many flavors, but all distinguish cognitive operations that are quick and associative from others that are slow and governed by rules. To represent intuitive and deliberate reasoning, we borrow the terms "system 1" and "system 2" from Stanovich and West. In the following section, we present an attribute-substitution model of heuristic judgment, which assumes that difficult questions are often answered by substituting an answer to an easier one. Following sections introduce a research design for studying attribute substitution, as well as discuss the controversy over the representativeness heuristic in the context of a dual-system view that we endorse. The final section situates representativeness within a broad family of prototype heuristics, in which properties of a prototypical exemplar dominate global judgments concerning an entire set. (shrink)

In a famous study of expert problem solving, de Groot (1946/1978) examined how chess players found the best move. He reported that there was little difference in the way that the best players (Grand Masters) and very good players (Candidate Masters) searched the board. Although this result has been regularly cited in studies of expertise, it is frequently misquoted. It is often claimed that de Groot found no difference in the way that experts and novices investigate a problem. Comparison of (...) expert and novice chess players on de Groot's problem shows that there are clear differences in their search patterns. We discuss the troublesome theoretical and practical consequences of incorrectly reporting de Groot's findings. (shrink)

The thirty-five chapters in this book describe various judgmental heuristics and the biases they produce, not only in laboratory experiments but in important...

Heuristics are efficient cognitive processes that ignore information. In contrast to the widely held view that less processing reduces accuracy, the study of heuristics shows that less information, computation, and time can in fact improve accuracy. We review the major progress made so far: the discovery of less-is-more effects; the study of the ecological rationality of heuristics, which examines in which environments a given strategy succeeds or fails, and why; an advancement from vague labels to computational models of heuristics; the (...) development of a systematic theory of heuristics that identifies their building blocks and the evolved capacities they exploit, and views the cognitive system as relying on an “adaptive toolbox;” and the development of an empirical methodology that accounts for individual differences, conducts competitive tests, and has provided evidence for people’s adaptive use of heuristics. Homo heuristicus has a biased mind and ignores part of the available information, yet a biased mind can handle uncertainty more efficiently and robustly than an unbiased mind relying on more resource-intensive and general-purpose processing strategies. (shrink)

Intuitive-automatic processes are crucial for making judgements and decisions. The fascinating complexity of these processes has attracted many decision researchers, prompting them to start investigating intuition empirically and to develop numerous models. Dual-process models assume a clear distinction between intuitive and deliberate processes but provide no further differentiation within both categories. We go beyond these models and argue that intuition is not a homogeneous concept, but a label used for different cognitive mechanisms. We suggest that these mechanisms have to be (...) distinguished to allow for fruitful investigations of intuition. Specifically, we argue that researchers should concentrate on investigating the processes underlying intuition before making strong claims about its performance. We summarise current models for intuition and propose a categorisation according to the underlying cognitive processes: (a) associative intuition based on simple learning-retrieval processes, (b) matching intuition based on comparisons with prototypes/exemplars, (c) accumulative intuition based on automatic evidence accumulation, and (d) constructive intuition based on construction of mental representations. We discuss how this differentiation might help to clarify the relationship between affect and intuition and we derive a very general hypothesis as to when intuition will lead to good decisions and when it will go astray. (shrink)

A new approach examined two aspects of chess skill, long a popular topic in cognitive science. A powerful computer‐chess program calculated the number and magnitude of blunders made by the same 23 grandmasters in hundreds of serious games of slow (“classical”) chess, regular “rapid” chess, and rapid “blindfold” chess, in which opponents transmit moves without ever seeing the actual position. Rapid chess led to substantially more and larger blunders than classical chess. Perhaps more surprisingly, the frequency and magnitude of blunders (...) did not differ in rapid versus blindfold play, despite the additional memory and visualization load imposed by the latter. We discuss the involvement of various cognitive processes in human problem‐solving and expertise, especially with respect to chess. Prior opposing views about the basis of general chess skill have emphasized the dominance of either (a) swift pattern recognition or (b) analyzing ahead, but both seem important and the controversy appears currently unresolvable and perhaps fruitless. (shrink)