Heuristic

A heuristic technique (/hjʊəˈrɪstɪk/; Ancient Greek: εὑρίσκω, "find" or "discover"), often called simply a heuristic, is any approach to problem solving, learning, or discovery that employs a practical method, not guaranteed to be optimal, perfect, logical, or rational, but instead sufficient for reaching an immediate goal. Where finding an optimal solution is impossible or impractical, heuristic methods can be used to speed up the process of finding a satisfactory solution. Heuristics can be mental shortcuts that ease the cognitive load of making a decision. Examples that employ heuristics include using a rule of thumb, an educated guess, an intuitive judgment, a guesstimate, stereotyping, profiling, or common sense.

Overview

Heuristics are the strategies derived from previous experiences with similar problems. These strategies rely on using readily accessible, though loosely applicable, information to control problem solving in human beings, machines, and abstract issues.[1][2]

The most fundamental heuristic is trial and error, which can be used in everything from matching nuts and bolts to finding the values of variables in algebra problems.

Here are a few other commonly used heuristics, from George Pólya's 1945 book, How to Solve It:[3]

  • If you are having difficulty understanding a problem, try drawing a picture.
  • If you can't find a solution, try assuming that you have a solution and seeing what you can derive from that ("working backward").
  • If the problem is abstract, try examining a concrete example.
  • Try solving a more general problem first (the "inventor's paradox": the more ambitious plan may have more chances of success).

In psychology, heuristics are simple, efficient rules, learned or hard-coded by evolutionary processes, that have been proposed to explain how people make decisions, come to judgments, and solve problems typically when facing complex problems or incomplete information. Researchers test if people use those rules with various methods. These rules work well under most circumstances, but in certain cases lead to systematic errors or cognitive biases.[4]

History

The study of heuristics in human decision-making was developed in the 1970s and 80s by psychologists Amos Tversky and Daniel Kahneman,[5] although the concept was originally introduced by Nobel laureate Herbert A. Simon. Simon's original, primary object of research was problem solving which showed that we operate within what he calls bounded rationality. He coined the term "satisficing", which denotes the situation where people seek solutions or accept choices or judgments that are "good enough" for their purposes, but could be optimized.[6]

Rudolf Groner analyzed the history of heuristics from its roots in ancient Greece up to contemporary work in cognitive psychology and artificial intelligence,[7] and proposed a cognitive style "heuristic versus algorithmic thinking" which can be assessed by means of a validated questionnaire.[8]

Gerd Gigerenzer focused on the "fast and frugal" properties of heuristics, i.e., using heuristics in a way that is principally accurate and thus eliminating most cognitive bias.[9] Heuristics – like the recognition heuristic or the take-the-best heuristic – are viewed as special tools that tackle specific tasks (e.g., binary choice) under conditions of uncertainty[10] and are organized in an "adaptive toolbox".[11] From one particular batch of research, Gigerenzer and Wolfgang Gaissmaier found that both individuals and organizations rely on heuristics in an adaptive way. They also found that ignoring part of the information [with a decision], rather than weighing all the options, can actually lead to more accurate decisions.[12][13]

Heuristics, through greater refinement and research, have begun to be applied to other theories, or be explained by them. For example: the cognitive-experiential self-theory (CEST) also is an adaptive view of heuristic processing. CEST breaks down two systems that process information. At some times, roughly speaking, individuals consider issues rationally, systematically, logically, deliberately, effortfully, and verbally. On other occasions, individuals consider issues intuitively, effortlessly, globally, and emotionally.[14] From this perspective, heuristics are part of a larger experiential processing system that is often adaptive, but vulnerable to error in situations that require logical analysis.[15]

In 2002, Daniel Kahneman and Shane Frederick proposed that cognitive heuristics work by a process called attribute substitution, which happens without conscious awareness.[16] According to this theory, when somebody makes a judgment (of a "target attribute") that is computationally complex, a rather easier calculated "heuristic attribute" is substituted. In effect, a cognitively difficult problem is dealt with by answering a rather simpler problem, without being aware of this happening.[16] This theory explains cases where judgments fail to show regression toward the mean.[17] Heuristics can be considered to reduce the complexity of clinical judgements in healthcare.[18]

Theorized psychological heuristics

Well known

  • Anchoring and adjustment – Describes the common human tendency to rely more heavily on the first piece of information offered (the "anchor") when making decisions. For example, in a study done with children, the children were told to estimate the number of jellybeans in a jar. Groups of children were given either a high or low "base" number (anchor). Children estimated the number of jellybeans to be closer to the anchor number that they were given.[19]
  • Availability heuristic – A mental shortcut that occurs when people make judgments about the probability of events by the ease with which examples come to mind. For example, in a 1973 Tversky & Kahneman experiment, the majority of participants reported that there were more words in the English language that start with the letter K than for which K was the third letter. There are actually twice as many words in the English Language that have K as the third letter as those that start with K, but words that start with K are much easier to recall and bring to mind.[20]
  • Representativeness heuristic – A mental shortcut used when making judgments about the probability of an event under uncertainty. Or, judging a situation based on how similar the prospects are to the prototypes the person holds in his or her mind. For example, in a 1982 Tversky and Kahneman experiment, participants were given a description of a woman named Linda. Based on the description, it was likely that Linda was a feminist. Eighty to ninety percent of participants, choosing from two options, chose that it was more likely for Linda to be a feminist and a bank teller than only a bank teller. The likelihood of two events cannot be greater than that of either of the two events individually. For this reason, the representativeness heuristic is exemplary of the conjunction fallacy.[20]
  • Naïve diversification – When asked to make several choices at once, people tend to diversify more than when making the same type of decision sequentially.
  • Escalation of commitment – Describes the phenomenon where people justify increased investment in a decision, based on the cumulative prior investment, despite new evidence suggesting that the cost, starting today, of continuing the decision outweighs the expected benefit. This is related to the sunk cost fallacy.
  • Familiarity heuristic – A mental shortcut applied to various situations in which individuals assume that the circumstances underlying the past behavior still hold true for the present situation and that the past behavior thus can be correctly applied to the new situation. Especially prevalent when the individual experiences a high cognitive load.

Lesser known

Cognitive maps

Heuristics were also found to be used in the manipulation and creation of cognitive maps. Cognitive maps are internal representations of our physical environment, particularly associated with spatial relationships. These internal representations of our environment are used as memory as a guide in our external environment. It was found that when questioned about maps imaging, distancing, etc., people commonly made distortions to images. These distortions took shape in the regularization of images (i.e., images are represented as more like pure abstract geometric images, though they are irregular in shape).

There are several ways that humans form and use cognitive maps. Visual intake is a key part of mapping. The first is by using landmarks. This is where a person uses a mental image to estimate a relationship, usually distance, between two objects. Second, is route-road knowledge, and this is generally developed after a person has performed a task and is relaying the information of that task to another person. Third, is survey. A person estimates a distance based on a mental image that, to them, might appear like an actual map. This image is generally created when a person's brain begins making image corrections. These are presented in five ways: 1. Right-angle bias is when a person straightens out an image, like mapping an intersection, and begins to give everything 90-degree angles, when in reality it may not be that way. 2. Symmetry heuristic is when people tend to think of shapes, or buildings, as being more symmetrical than they really are. 3. Rotation heuristic is when a person takes a naturally (realistically) distorted image and straightens it out for their mental image. 4. Alignment heuristic is similar to the previous, where people align objects mentally to make them straighter than they really are. 5. Relative-position heuristic: people do not accurately distance landmarks in their mental image based on how well they remember that particular item.

Another method of creating cognitive maps is by means of auditory intake based on verbal descriptions. Using the mapping based from a person's visual intake, another person can create a mental image, such as directions to a certain location.[21]

Philosophy

"Heuristic device" is used when an entity X exists to enable understanding of, or knowledge concerning, some other entity Y. A good example is a model that, as it is never identical with what it models, is a heuristic device to enable understanding of what it models. Stories, metaphors, etc., can also be termed heuristic in that sense. A classic example is the notion of utopia as described in Plato's best-known work, The Republic. This means that the "ideal city" as depicted in The Republic is not given as something to be pursued, or to present an orientation-point for development; rather, it shows how things would have to be connected, and how one thing would lead to another (often with highly problematic results), if one would opt for certain principles and carry them through rigorously.

"Heuristic" is also often used as a noun to describe a rule-of-thumb, procedure, or method.[22] Philosophers of science have emphasized the importance of heuristics in creative thought and constructing scientific theories.[23] (See The Logic of Scientific Discovery by Karl Popper; and philosophers such as Imre Lakatos,[24] Lindley Darden, William C. Wimsatt, and others.)

Law

In legal theory, especially in the theory of law and economics, heuristics are used in the law when case-by-case analysis would be impractical, insofar as "practicality" is defined by the interests of a governing body.[25]

The present securities regulation regime largely assumes that all investors act as perfectly rational persons. In truth, actual investors face cognitive limitations from biases, heuristics, and framing effects.

For instance, in all states in the United States the legal drinking age for unsupervised persons is 21 years, because it is argued that people need to be mature enough to make decisions involving the risks of alcohol consumption. However, assuming people mature at different rates, the specific age of 21 would be too late for some and too early for others. In this case, the somewhat arbitrary deadline is used because it is impossible or impractical to tell whether an individual is sufficiently mature for society to trust them with that kind of responsibility. Some proposed changes, however, have included the completion of an alcohol education course rather than the attainment of 21 years of age as the criterion for legal alcohol possession. This would put youth alcohol policy more on a case-by-case basis and less on a heuristic one, since the completion of such a course would presumably be voluntary and not uniform across the population.

The same reasoning applies to patent law. Patents are justified on the grounds that inventors must be protected so they have incentive to invent. It is therefore argued that it is in society's best interest that inventors receive a temporary government-granted monopoly on their idea, so that they can recoup investment costs and make economic profit for a limited period. In the United States, the length of this temporary monopoly is 20 years from the date the application for patent was filed, though the monopoly does not actually begin until the application has matured into a patent. However, like the drinking-age problem above, the specific length of time would need to be different for every product to be efficient. A 20-year term is used because it is difficult to tell what the number should be for any individual patent. More recently, some, including University of North Dakota law professor Eric E. Johnson, have argued that patents in different kinds of industries – such as software patents – should be protected for different lengths of time.[26]

Stereotyping

Stereotyping is a type of heuristic that all people use to form opinions or make judgments about things they have never seen or experienced.[27] They work as a mental shortcut to assess everything from the social status of a person based on their actions to assumptions that a plant that is tall, has a trunk, and has leaves is a tree even though the person making the evaluation has never seen that particular type of tree before.

Stereotypes, as first described by journalist Walter Lippmann in his book Public Opinion (1922), are the pictures we have in our heads that are built around experiences as well as what we are told about the world.[28][29]

Artificial intelligence

A heuristic can be used in artificial intelligence systems while searching a solution space. The heuristic is derived by using some function that is put into the system by the designer or by adjusting the weight of branches based on how likely each branch is to lead to a goal node.

Critiques and controversies

The concept of heuristics has critiques and controversies. The "We Cannot Be That Dumb" critique shows that the average person has low ability to make sound and effective judgments.[30]

See also

References

  1. ↑ Pearl, Judea (1983). Heuristics: Intelligent Search Strategies for Computer Problem Solving. New York, Addison-Wesley, p. vii. ISBN 978-0-201-05594-8
  2. ↑ Emiliano, Ippoliti (2015). Heuristic Reasoning: Studies in Applied Philosophy, Epistemology and Rational Ethics. Switzerland: Springer International Publishing. pp. 1–2. ISBN 978-3-319-09159-4.
  3. ↑ Pólya, George (1945) How to Solve It: A New Aspect of Mathematical Method, Princeton, NJ: Princeton University Press. ISBN 0-691-02356-5   ISBN 0-691-08097-6
  4. ↑ Gigerenzer, Gerd (1991). "How to Make Cognitive Illusions Disappear: Beyond "Heuristics and Biases"" (PDF). European Review of Social Psychology. 2: 83–115. doi:10.1080/14792779143000033. Retrieved 14 October 2012.
  5. ↑ Daniel Kahneman, Amos Tversky, and Paul Slovic, eds. (1982) Judgment under Uncertainty: Heuristics & Biases. Cambridge, UK, Cambridge University Press ISBN 0-521-28414-7
  6. ↑ "Heuristics and heuristic evaluation". Interaction-design.org. Retrieved 2013-09-01.
  7. ↑ Rudolf Groner, Marina Groner & Walter F. Bischof (1983). Methods of heuristics. Hillsdale N.J., Lawrence Erlbaum.
  8. ↑ Rudolf Groner & Marina Groner (1991). Heuristische versus algorithmische Orientierung als Dimension des individuellen kognitiven Stils. In K. Grawe, N. Semmer, R. Hänni (Hrsg.), Über die richtige Art, Psychologie zu betreiben . Göttingen, Hogrefe.
  9. ↑ Gerd Gigerenzer, Peter M. Todd, and the ABC Research Group (1999). Simple Heuristics That Make Us Smart. Oxford, UK, Oxford University Press. ISBN 0-19-514381-7
  10. ↑ Neth, Hansjörg; Gigerenzer, Gerd (May 2015). "Heuristics: Tools for an uncertain world". Emerging Trends in the Social and Behavioral Sciences. Wiley & Sons, Inc. pp. 1–18. doi:10.1002/9781118900772.etrds0394. Retrieved 10 August 2017.
  11. ↑ Gigerenzer, Gerd, and Reinhard Selten, eds. (2002) Bounded rationality: The adaptive toolbox. Cambridge, Massachusetts, MIT press. ISBN 978-0262571647
  12. ↑ Gigerenzer, Gerd; Gaissmaier, Wolfgang (January 2011). "Heuristic Decision Making". Annual Review of Psychology. Ssrn.com. pp. 451–482. SSRN 1722019. Missing or empty |url= (help)
  13. ↑ Gigerenzer, G; Gaissmaier, W (2011). "Heuristic Decision Making". Annual Review of Psychology. 62: 451–482. doi:10.1146/annurev-psych-120709-145346. PMID 21126183.
  14. ↑ "Cognitive experiential self theory - Psychlopedia". psych-it.com.au. 2008-10-18. doi:10.1177/1745691611429354. Retrieved 2013-09-01.
  15. ↑ Epstein, S.; Pacini, R.; Denes-Raj, V.; Heier, H. (1996). "Individual differences in intuitive-experiential and analytical-rational thinking styles". Journal of Personality and Social Psychology. 71 (2): 390–405. doi:10.1037/0022-3514.71.2.390. PMID 8765488.
  16. 1 2 Kahneman, Daniel; Shane Frederick (2002). "Representativeness Revisited: Attribute Substitution in Intuitive Judgment". In Thomas Gilovich; Dale Griffin; Daniel Kahneman. Heuristics and Biases: The Psychology of Intuitive Judgment. Cambridge: Cambridge University Press. pp. 49–81. ISBN 978-0-521-79679-8. OCLC 47364085.
  17. ↑ Kahneman, Daniel (December 2003). "Maps of Bounded Rationality: Psychology for Behavioral Economics" (PDF). American Economic Review. American Economic Association. 93 (5): 1449–1475. doi:10.1257/000282803322655392. ISSN 0002-8282.
  18. ↑ Cioffi, Jane (1997). "Heuristics, servants to intuition, in clinical decision making". Journal of Advanced Nursing. 26: 203–208. doi:10.1046/j.1365-2648.1997.1997026203.x.
  19. ↑ Smith, H. (1999). "Use of the anchoring and adjustment heuristic by children". Current Psychology. 18 (3): 294–300. doi:10.1007/s12144-999-1004-4.
  20. 1 2 Harvey, N (2007). "Use of heuristics: Insights from forecasting research". Thinking & Reasoning. 13 (1): 5–24. doi:10.1080/13546780600872502.
  21. ↑ Sternberg, Robert J.; Karin Sternberg (2012). Cognitive Psychology (6th ed.). Belmont, CA: Wadsworth, Cengage Learning. pp. 310–1315. ISBN 978-1-111-34476-4.
  22. ↑ K. M. Jaszczolt (2006). "Defaults in Semantics and Pragmatics", The Stanford Encyclopedia of Philosophy, ISSN 1095-5054
  23. ↑ Roman Frigg and Stephan Hartmann (2006). "Models in Science", The Stanford Encyclopedia of Philosophy, ISSN 1095-5054
  24. ↑ Kiss, Olga (2006). "Heuristic, Methodology or Logic of Discovery? Lakatos on Patterns of Thinking". Perspectives on Science. 14 (3): 302–317. doi:10.1162/posc.2006.14.3.302.
  25. ↑ Gerd Gigerenzer and Christoph Engel, eds. (2007). Heuristics and the Law, Cambridge, The MIT Press, ISBN 978-0-262-07275-5
  26. ↑ Johnson, Eric E. (2006). "Calibrating Patent Lifetimes" (PDF). Santa Clara Computer & High Technology Law Journal. 22: 269–314.
  27. ↑ Bodenhausen, Galen V.; et al. (1999). "On the Dialectics of Discrimination: Dual Processes in Social Stereotyping", in Dual-process Theories in Social Psychology edited by Shelly Chaiken and Yaacov Trope. NY: Guilford Press. pp. 271–92. ISBN 1572304219. Retrieved 24 March 2015.
  28. ↑ Kleg, Milton (1883). Hate Prejudice and Racism. Albany: State University of New York Press. p. 135. ISBN 0791415368. Retrieved 24 March 2015.
  29. ↑ Gökçen, Sinan. "Pictures in Our Heads". European Roma Rights Centre. Retrieved 24 March 2015.
  30. ↑ "Heuristics and Biases" - The Psychology of Intuitive Judgment Edited by THOMAS GILOVICH, Cornell University DALE GRIFFIN, Stanford University DANIEL KAHNEMAN, Princeton University (page 8-9)

Further reading

  • How To Solve It: Modern Heuristics, Zbigniew Michalewicz and David B. Fogel, Springer Verlag, 2000. ISBN 3-540-66061-5
  • Russell, Stuart J.; Norvig, Peter (2003), Artificial Intelligence: A Modern Approach (2nd ed.), Upper Saddle River, New Jersey: Prentice Hall, ISBN 0-13-790395-2
  • The Problem of Thinking Too Much, 2002-12-11, Persi Diaconis
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