Cognitive Biases

Conceptual Overview and Discussion

Cognitive biases often occur when people use shortcuts in thinking. In the 1960s, Amos Tversky and Daniel Kahneman began their pioneering research on biases when they discovered that experts were overconfident in the replicability of results from small samples. These shortcuts in thinking, also termed heuristics, work reasonably well when people need to make quick decisions. However, heuristics can lead to systematic biases in thinking, especially in situations calling for systematic and logical reasoning.

Leda Cosmides, Gerd Gigerenzer, and Steven Pinker theorize that the ability of human beings to make quick decisions has evolutionary value because in some situations, especially those deemed dangerous and harmful to our survival, quick responses are vital. Furthermore, cognitive scientists such as Jonathan Evans and Steven Sloman [Page 159]hypothesize that the ability to make quick decisions is part of the brain's dual information-processing system. One part of the system is conscious, slow, and sequential, linked to working memory and measured intelligence, capable of abstract and hypothetical thinking, able to be controlled, and effortful; the other part is unconscious, rapid, associative, pragmatic, efficient in memory resources, independent of general measured intelligence, and relatively effortless. Heuristics arise from this second system and often lead to satisfactory outcomes in vital situations; however, they can also lead to serious errors in thinking that should be avoided in situations that call for more controlled and effortful thought.

Cognitive biases can arise in almost all forms of thinking and reasoning, including quantitative judgment, decision analysis, moral thinking, and social dilemmas. While many examples of cognitive biases exist in the psychological and economic literature, common cognitive biases expected to arise in case study research include those pertaining to hypothesis testing, judgments of probability, and correlation and contingency. Classic examples of cognitive biases in judgments of probability include the hindsight bias and biases arising from the representativeness heuristic and the availability heuristic. In hypothesis testing, commonly illustrated examples of cognitive biases include the congruence or confirmation bias and the information bias. Finally, in judgments of correlation and contingency, pertinent cognitive biases include the attentional bias, and those arising from the effects of prior belief leading to illusory correlations. A brief definition for each of these biases follows.

Representativeness Heuristic. Estimating the probability that an event A belongs to (or originates from) a particular class B by evaluating the degree to which A is similar to or typical of B. This heuristic can lead to errors of judgment because it ignores prior probabilities of classes (i.e., the prior probability or base rate of B) and therefore can lead people to categorize events incorrectly into classes.

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