Recognition heuristic

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The recognition heuristic (Engl. Recognition heuristic, also recognition heuristic called) is a judgment heuristics of cognitive psychology . It states that in the assessment of multiple objects with respect to a criterion (in certain circumstances the recognition Rekognition, . From the English recognition is used) as the sole decision-making.

background

According to Herbert A. Simon's concept of limited rationality , human cognitive abilities are limited. For this reason, the optimal, normative solution for many complex problems is associated with too much effort. To solve these problems, people therefore resort to heuristics or rules of thumb - simplifying decision-making strategies in order to arrive at the best possible solution, which does not necessarily have to be optimal ( satisficing ). The idea that people use simplistic heuristics to solve problems was taken up in the following by many researchers who proposed heuristics in different areas.

The recognition heuristic was proposed as part of a research program by Gerd Gigerenzer , Daniel G. Goldstein and colleagues, which focuses on fast and simple heuristics and the conditions under which they can be successful. It is assumed that people have a collection of decision-making strategies (a so-called adaptive toolbox ) from which they can select the right strategy depending on the situation and task.

Originally, the recognition heuristic was implemented as the first part of the take-the-best heuristic . Eventually, however, it was postulated as a stand-alone model. At first it was limited to the comparison of two objects, but was later expanded.

Explanation

The recognition heuristic is a decision strategy for comparative judgments. If two objects are to be assessed with regard to a certain criterion, it says the following:

"If one of two objects is recognized and the other is not, then infer that the recognized object has the higher value with respect to the criterion."

"If one of two objects is recognized and the other is not, conclude from this that the recognized object has the higher value on the criterion."

A typical and often examined paradigm is the task of assessing which of two cities has more inhabitants, such as San Diego or San Antonio . If a person only knows one of the two cities, they should judge it to be larger when using the recognition heuristic. If a person knows both cities or both are unknown, the recognition heuristic cannot be used.

Ecological rationality

The recognition heuristic is based on the assumption that in certain environments the recognition or non-recognition of an object is systematically related to the criterion to be assessed - for example, because cities with more inhabitants are mentioned more often in the media and are therefore more easily recognized. Recognizing or not recognizing a city would be a valid indication of its population. The strength of this relationship is called recognition validity . It turns out that recognition is a valid indicator in many environments. Because the recognition heuristic exploits the natural connection between recognition and criterion, it is called ecologically rational .

Ignorance-based decision-making

Another central assumption by Gigerenzer, Goldstein and colleagues is that the recognition heuristic is a non-compensatory strategy: The recognition or non-recognition of an object is used as the sole information. The decision is therefore based exclusively on this recognition information and all further information is ignored.

Conditions for the application

Several boundary conditions are established for the use of the recognition heuristic:

  • The application of the recognition heuristic requires that some objects are not recognized . Only then can recognized and unrecognized objects be compared.
  • The recognition heuristic should only be used if the recognition of an object is actually related to the criterion to be assessed, i.e. if it offers valid information . Specifically, recognition should only influence the decision if it is better than guessing.
  • The person makes their judgment based on their memory. Further information will not be made available to her.
  • Recognition of an object should be due to a person's natural environment and not to experimental manipulation.

Less-is-more effect

One implication of the recognition heuristic is that under certain circumstances less knowledge - in the sense of less recognized objects - can lead to better results: In an environment in which recognition is strongly related to the criterion, people who recognize almost all objects have a disadvantage , since they can rarely use the recognition heuristic. In contrast, people who only recognize a few objects would have an advantage.

Central findings

In the classic experiments on recognition heuristics, people have the task of making judgments for a series of city pairs as to which city is larger. In addition, it is recorded which city is known to the person and which is not. When evaluating these experiments, the city pairs are first classified according to the cases in which a person could have used the recognition heuristic (all cases in which they only recognized one of the two cities). Finally, it is considered in how many of these cases she actually chose the famous city. In a study, Goldstein and Gigerenzer report values ​​averaging 90%.

A finding on recognition heuristics that is also known in popular science is the demonstration of the less-is-more effect in people of different nationalities: Germans and Americans should give a judgment about which of two US cities is larger (San Diego or San Antonio) . Of the American participants, most of whom were familiar with both cities, around 62% gave the correct answer (based on the population at the time, San Diego), whereas it was 100% of the German participants, most of whom only recognized San Diego. However, this finding was not without criticism. a. because the recognition validity for Germans and Americans was not the same.

In several experiments it could be shown that people are able to distinguish whether the use of the recognition heuristic is appropriate in a situation or not: For example, if the task was to indicate which of two cities is larger, the judgments of the people were correct often agree with the predictions of the recognition heuristic. This was not the case for the task of specifying how far a city is from a given point.

criticism

A heated debate has developed about the status of the recognition heuristic. A number of findings refute several assumptions of the recognition heuristic. These are considered below.

Non-compensatory use of the recognition information

The original version of the recognition heuristic assumes that recognition is used as the only feature in the formation of judgments. Several findings call this sole (non-compensatory) use of the recognition information into question.

People also seem to include other information in their judgment if it provides additional information about the size being judged (e.g. whether the city being judged has a football team). In addition, people choose the recognized object less often when it is actually the wrong choice. This also suggests that recognition is not used as the only information.

Binary nature of the recognition information

The recognition heuristic implies that recognition represents binary information, i.e. that an object is either recognized or not. It turns out, however, that the speed of recognition also plays a role: the faster a known object is judged to be known, the more often it is assessed as larger than an unknown object. The processing fluid seems to have an additional influence on the judgment process.

The recognition heuristic as a process model

Many studies on recognition heuristics use the agreement between the predictions of the recognition heuristic and actually observed judgments as a measure for their use. In many cases this agreement is very high, which is interpreted as evidence for the sole use of the recognition heuristic.

However, the agreement between these predictions and the observations does not necessarily mean that the assumed process was the basis of the decisions. If alternative strategies (e.g. the use of additional knowledge) make the same predictions as the recognition heuristic, this measure does not allow a clear statement about the strategy actually used. If the measure is used in this case anyway, the extent to which the recognition heuristic is used is overestimated. However, undistorted measurements show that recognition is used as the sole indicator for a significant proportion of the decisions.

In general, even for entirely fictitious heuristics, there is quite a high degree of correspondence between the predicted and observed judgments - provided that they use information that is ecologically rational, i.e. actually related to the judgment dimension.

In summary, it cannot be deduced from the high predictive power of the recognition heuristic as a theoretical model that recognition is used as the sole indicator in decision-making. Proponents of the recognition heuristic, on the other hand, argue that their critics have hardly proposed their own models. However, more recently, alternative models have been developed.

See also

literature

Web links

Footnotes

  1. ^ Herbert A. Simon: Rational choice and the structure of the environment. In: Psychological Review. 63, 2, 1956, doi: 10.1037 / h0042769 , pp. 129-138.
  2. ^ Herbert A. Simon: Invariants of human behavior. In: Annual Review of Psychology. Vol. 41, 1990, doi: 10.1146 / annurev.ps.41.020190.000245 , pp. 1-19.
  3. ^ Gerd Gigerenzer, Peter M. Todd, & the ABC Research Group: Simple heuristics that make us smart. Oxford University Press, New York 1999
  4. ↑ Gerd Gigerenzer & Reinhard Selten (eds.): Bounded rationality: The adaptive toolbox. The MIT Press, Cambridge 2001
  5. ^ A b Gerd Gigerenzer & Daniel G. Goldstein: Reasoning the fast and frugal way: Models of bounded rationality. In: Psychological Review. 103, 4, 1996, doi : 10.1037 // 0033-295X.103.4.650 , pp. 650-669 ( PDF; 2.317 MB )
  6. ↑ a b c d e f g h i j Daniel G. Goldstein & Gerd Gigerenzer: Models of ecological rationality: The recognition heuristic. In: Psychological Review. 109, 1, doi : 10.1037 // 0033-295X.109.1.75 , pp. 75-90 ( PDF; 411 kB )
  7. ^ A b Julian N. Marewski, Wolfgang Gaissmaier, Lael J. Schooler, Daniel G. Goldstein & Gerd Gigerenzer: From recognition to decisions: Extending and testing recognition-based models for multi-alternative inference. In: Psychonomic Bulletin and Review. 17, 3, 2010, doi: 10.3758 / PBR.17.3.287 , pp. 287–309 ( PDF; 588 kB )
  8. ↑ a b c d Rüdiger F. Pohl: Empirical tests of the recognition heuristic. In: Journal of Behavioral Decision Making. 19, 3, 2006, doi: 10.1002 / bdm.522 , pp. 251-271
  9. ^ Daniel G. Goldstein & Gerd Gigerenzer: The recognition heuristic: How ignorance makes us smart. In: Gerd Gigerenzer, Peter M. Todd & the ABC Research Group: Simple heuristics that make us smart. Oxford University Press, New York 1999, pp. 37-58
  10. ↑ Thomas Lange: Half-knowledge as a recipe for success . In: Image of Science . 10/2006, p. 74
  11. ↑ Michael R. Dougherty, Ana M. Franco-Watkins & Rick Thomas: Psychological plausibility of the theory of probabilistic mental models and the fast and frugal heuristics. In: Psychological Review. 115, 1, 2008, pp. 199–213 ( PDF; 160 kB )
  12. ↑ Ben R. Newell & David R. Shanks: On the role of recognition in decision making. In: Journal of Experimental Psychology: Learning, Memory, and Cognition. 30, 4, 2004, doi: 10.1037 / 0278-7393.30.4.923 , pp. 923-935 ( PDF; 222 kB )
  13. ^ Julian N. Marewski, Rüdiger F. Pohl & Oliver Vitouch: Recognition-based judgments and decisions: Introduction to the special issue (Vol. 1). In: Judgment and Decision Making. Vol. 5, No. 4, pp. 207–215 ( PDF; 120 kB )
  14. ^ Julian N. Marewski, Rüdiger F. Pohl & Oliver Vitouch: Recognition-based judgments and decisions: What we have learned (so far). In: Judgment and Decision Making. Vol. 6, No. 5, pp. 359–380 ( PDF; 552 kB )
  15. ↑ a b Ben R. Newell & Duane Fernandez: On the binary quality of recognition and the inconsequentiality of further knowledge: Two critical tests of the recognition heuristic. In: Journal of Behavioral Decision Making. 19, 4, 2006, doi: 10.1002 / bdm.531 , pp. 333–346 ( PDF; 121 kB )
  16. ^ Benjamin E. Hilbig: Precise models deserve precise measures: A methodological dissection. In: Judgment and Decision Making. Vol. 5, No. 4, 2010, pp. 272–284 ( PDF; 193 kB )
  17. ↑ Benjamin E. Hilbig, Edgar Erdfelder & Rüdiger F. Pohl: One-reason decision making unveiled: A measurement model of the recognition heuristic. In: Journal of Experimental Psychology: Learning, Memory, and Cognition. 36, 1, 2010, doi: 10.1037 / a0017518 , pp. 123-134
  18. ^ Benjamin E. Hilbig: Reconsidering “evidence” for fast-and-frugal heuristics. In: Psychonomic Bulletin & Review. Vol. 17, Issue 6, 2010, doi: 10.3758 / PBR.17.6.923 , pp. 923-930
  19. ↑ Gerd Gigerenzer & Daniel G. Goldstein: The recognition heuristic: A decade of research. In: Judgment and Decision Making. Vol. 6, No. 1, 2011, pp. 100–121 ( PDF; 217 kB )
  20. ↑ Andreas Glöckner & Arndt Bröder: Processing of recognition information and additional cues: A model-based analysis of choice, confidence, and response time. In: Judgment and Decision Making. Vol. 6, No. 1, 2011, pp. 23–42 ( PDF; 344 kB )