Bounded Rationality and Emotions

Bounded Rationality

In 1957, Herbert Simon proposed the notion of bounded rationality to account for the fact that perfectly rational decisions are often not feasible in practice due to the finite information-processing capacities of humans. Simon points out that most people are only partly rational and are in fact emotional or irrational in the remaining part of their actions. Human beings are limited in their capacity for storing and processing information. As a consequence, people process information sequentially and use heuristics, or rules of thumb, to keep the information-processing demands of complex tasks within the bounds of their cognitive capacities. These heuristics are procedures for systematically simplifying the search through the available information. The use of heuristic strategies improves the performance of the individual as a limited information processor and is, as Simon argues, “at the heart of human intelligence.” In this vein, Gerd Gigerenzer and colleagues argue that simple alternatives (i.e., heuristics) to a full rational analysis as a mechanism for decision making frequently lead to better decisions than the theoretically optimal procedure. These heuristics are generally successful, but in certain situations they lead to systematic cognitive biases.

Heuristics

People use heuristics for multi-attribute decision problems such as choosing a car or choosing a hospital for treatment as well as for risky decision making such as the choice between an operation and a wait-and-see policy with different mortality risks. Two approaches to the use of heuristics in decision making can be distinguished: the accuracy/effort approach and the heuristics-and-biases approach. According to the accuracy/effort approach, people process and evaluate only a part of the information and use noncompensatory decision rules to limit the information-processing demands of multi-attribute decision problems. For instance, people eliminate options because of an unsatisfactory score on one attribute, as, for example, when choosing among cars, a decision maker eliminates all options above a certain price, irrespective of the evaluation of the other attributes. John Payne and colleagues see humans as adaptive decision makers who weight the benefits of a decision strategy (i.e., the probability that a strategy will select the best alternative) against the costs (i.e., the mental effort, time, and money needed).

Another approach is the heuristics-and-biases approach. This approach is most prominently represented by the research of Amos Tversky and Daniel Kahneman and emphasizes the biases and errors in human judgment that are due to the use of heuristics. Contrary to the earlier approach, it does not consider the use of heuristics as a rational trade-off between accuracy and effort but as a failure to recognize the “correct” solution. Tversky and Kahneman consider these heuristics as highly economical and usually effective but add that in some cases they may lead to systematic and predictable errors. An example of such a heuristic is the availability heuristic: Objects or events are judged as frequent and probable or causally efficacious to the extent that they are readily available in memory. This heuristic is likely to erroneously affect the evaluation of information whenever some aspect in the environment is made disproportionally salient or available to the perceiver.

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