Heuristics in Judgment and Decision-making - Wikipedia, The Free Encyclopedia

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5/2/2016 Heuristics in judgment and decision-making - Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Heuristics_in_judgment_and_decision-making

Heuristics in judgment and decision-makingFrom Wikipedia, the free encyclo pedia

In psychology, heuristics are simple, efficient rules which people often use to form judgments and makedecisions. They are mental shortcuts that usually involve focusing on one aspect of a complex problem and

ignoring others.[1][2][3] These rules work well under most circumstances, but they can lead to systematic

deviations from logic, probability or rational choice theory. The resulting errors are called "cognitive biases" and many different types have been documented. These have been shown to affect people's choicesin situations like valuing a house, deciding the outcome of a legal case, or making an investment decision.Heuristics usually govern automatic, intuitive judgments but can also be used as deliberate mental strategiewhen working from limited information.

Cognitive scientist Herbert A. Simon originally proposed that human judgments are based on heuristics,

taking the concept from the field of computation.[a] In the early 1970s, psychologists Amos Tversky andDaniel Kahneman demonstrated three heuristics that underlie a wide range of intuitive judgments. These

findings set in motion the Heuristics and Biases (HB)[4] research program, which studies how people mak

real-world judgments and the conditions under which those judgments are unreliable. This researchchallenged the idea that human beings are rational actors, but provided a theory of information processingto explain how people make estimates or choices. This research, which first gained worldwide attention in

1974 with the Science paper "Judgment Under Uncertainty: Heuristics and Biases",[5] has guided almost al

current theories of decision-making,[6] and although the originally proposed heuristics have been challengein the further debate, this research program has changed the field by permanently setting the research

questions.[7]

This "Heuristic-and-Bias" tradition has been criticized for being too focused on how heuristics lead to

errors.[8] However, heuristics can be seen as rational in an underlying sense. According to this perspective,heuristics are good enough for most purposes without being too demanding on the brain's resources.Another theoretical perspective sees heuristics as fully rational in that they are rapid, can be made withoutfull information and can be as accurate as more complicated procedures. By understanding the role of heuristics in human psychology, marketers and other persuaders can influence decisions, such as the prices

people pay for goods or the quantity they buy.

Contents

1 Types1.1 Availability1.2 Representativeness1.3 Anchoring and adjustment1.4 Affect heuristic1.5 Others

2 Theories2.1 Cognitive laziness2.2 Attribute substitution2.3 Fast and frugal

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https://en.wikipedia.org/wiki/Heuristics_in_judgment_and_decision-making 2

3 Consequences3.1 Efficient decision heuristics3.2 "Beautiful-is-familiar" effect3.3 Judgments of morality and fairness

4 See also5 Footnotes6 Citations7 References

8 Further reading9 External links

Types

In their initial research, Tversky and Kahneman proposed three heuristics—availability, representativenessand anchoring and adjustment. Subsequent work has identified many more. Heuristics that underlieudgment are called "judgment heuristics". Another type, called "evaluation heuristics", are used to judge

the desirability of possible choices.

[9]

Availability

In psychology, availability is the ease with which a particular idea can be brought to mind. When peopleestimate how likely or how frequent an event is on the basis of its availability, they are using the availabili

heuristic.[10] When an infrequent event can be brought easily and vividly to mind, people tend to

overestimate its likelihood.[11] For example, people overestimate their likelihood of dying in a dramaticevent such as a tornado or terrorism. Dramatic, violent deaths are usually more highly publicised and

therefore have a higher availability.[12] On the other hand, common but mundane events are hard to bring tmind, so their likelihoods tend to be underestimated. These include deaths from suicides, strokes, anddiabetes. This heuristic is one of the reasons why people are more easily swayed by a single, vivid story

than by a large body of statistical evidence.[13] It may also play a role in the appeal of lotteries: to someone buying a ticket, the well-publicised, jubilant winners are more available than the millions of people who

have won nothing.[12]

When people judge whether more English words begin with T or with K , the availability heuristic gives aquick way to answer the question. Words that begin with T come more readily to mind, and so subjects giva correct answer without counting out large numbers of words. However, this heuristic can also produce

errors. When people are asked whether there are more English words with K in the first position or with K in the third position, they use the same process. It is easy to think of words that begin with K , such askangaroo, kitchen, or kept . It is harder to think of words with K as the third letter, such as lake, or acknowledge, although objectively these are three times more common. This leads people to the incorrect

conclusion that K is more common at the start of words.[14] In another experiment, subjects heard the nameof many celebrities, roughly equal numbers of whom were male and female. The subjects were then askedwhether the list of names included more men or more women. When the men in the list were more famousa great majority of subjects incorrectly thought there were more of them, and vice versa for women.Tversky and Kahneman's interpretation of these results is that judgments of proportion are based on

availability, which is higher for the names of better-known people.[10]

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In one experiment that occurred before the 1976 U.S. Presidential election, some participants were asked toimagine Gerald Ford winning, while others did the same for a Jimmy Carter victory. Each groupsubsequently viewed their allocated candidate as significantly more likely to win. The researchers found a

similar effect when students imagined a good or a bad season for a college football team. [15] The effect of

imagination on subjective likelihood has been replicated by several other researchers.[13]

A concept's availability can be affected by how recently and how frequently it has been brought to mind. In

one study, subjects were given partial sentences to complete. The words were selected to activate theconcept either of hostility or of kindness: a process known as priming . They then had to interpret the behavior of a man described in a short, ambiguous story. Their interpretation was biased towards theemotion they had been primed with: the more priming, the greater the effect. A greater interval between the

initial task and the judgment decreased the effect.[16]

Tversky and Kahneman offered the availability heuristic as an explanation for illusory correlations in whic people wrongly judge two events to be associated with each other. They explained that people judge

correlation on the basis of the ease of imagining or recalling the two events together. [10][14]

Representativeness

The representativeness heuristic is seen when people use categories, for example when deciding whether onot a person is a criminal. An individual thing has a high representativeness for a category if it is verysimilar to a prototype of that category. When people categorise things on the basis of representativeness,they are using the representativeness heuristic. "Representative" is here meant in two different senses: the

prototype used for comparison is representative of its category, and representativeness is also a relation

between that prototype and the thing being categorised.[14][17] While it is effective for some problems, thisheuristic involves attending to the particular characteristics of the individual, ignoring how common thosecategories are in the population (called the base rates). Thus, people can overestimate the likelihood that

something has a very rare property, or underestimate the likelihood of a very common property. This iscalled the base rate fallacy. Representativeness explains this and several other ways in which human

udgments break the laws of probability.[14]

The representativeness heuristic is also an explanation of how people judge cause and effect: when theymake these judgements on the basis of similarity, they are also said to be using the representativenessheuristic. This can lead to a bias, incorrectly finding causal relationships between things that resemble oneanother and missing them when the cause and effect are very different. Examples of this include both the

belief that "emotionally relevant events ought to have emotionally relevant causes", and magical associativ

thinking.[18]

Ignorance of base rates

A 1973 experiment used a psychological profile of Tom W., a fictional graduate student.[19] One group of subjects had to rate Tom's similarity to a typical student in each of nine academic areas (including Law,Engineering and Library Science). Another group had to rate how likely it is that Tom specialised in eacharea. If these ratings of likelihood are governed by probability, then they should resemble the base rates, i.ethe proportion of students in each of the nine areas (which had been separately estimated by a third group).If people based their judgments on probability, they would say that Tom is more likely to study Humanitie

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than Library Science, because there are many more Humanities students, and the additional information inthe profile is vague and unreliable. Instead, the ratings of likelihood matched the ratings of similarity almo

perfectly, both in this study and a similar one where subjects judged the likelihood of a fictional womantaking different careers. This suggests that rather than estimating probability using base rates, subjects had

substituted the more accessible attribute of similarity.[19]

Conjunction fallacy

When people rely on representativeness, they can fall into an error which breaks a fundamental law of

probability.[17] Tversky and Kahneman gave subjects a short character sketch of a woman called Linda,describing her as, "31 years old, single, outspoken, and very bright. She majored in philosophy. As astudent, she was deeply concerned with issues of discrimination and social justice, and also participated inanti-nuclear demonstrations". People reading this description then ranked the likelihood of differentstatements about Linda. Amongst others, these included "Linda is a bank teller", and, "Linda is a bank telland is active in the feminist movement". People showed a strong tendency to rate the latter, more specificstatement as more likely, even though a conjunction of the form "Linda is both X and Y " can never be more

probable than the more general statement "Linda is X ". The explanation in terms of heuristics is that the

udgment was distorted because, for the readers, the character sketch was representative of the sort of person who might be an active feminist but not of someone who works in a bank. A similar exerciseconcerned Bill, described as "intelligent but unimaginative". A great majority of people reading thischaracter sketch rated "Bill is an accountant who plays jazz for a hobby", as more likely than "Bill plays

azz for a hobby".[20]

Without success, Tversky and Kahneman used what they described as "a series of increasingly desperatemanipulations" to get their subjects to recognise the logical error. In one variation, subjects had to choose

between a logical explanation of why "Linda is a bank teller" is more likely, and a deliberately illogicalargument which said that "Linda is a feminist bank teller" is more likely "because she resembles an active

feminist more than she resembles a bank teller". Sixty-five percent of subjects found the illogical argumenmore convincing.[20][21] Other researchers also carried out variations of this study, exploring the possibility

that people had misunderstood the question. They did not eliminate the error.[22][23] The error disappearswhen the question is posed in terms of frequencies. Everyone in these versions of the study recognised thatout of 100 people fitting an outline description, the conjunction statement ("She is X and Y ") cannot apply

to more people than the general statement ("She is X ").[24]

Ignorance of sample size

Tversky and Kahneman asked subjects to consider a problem about random variation. Imagining for simplicity that exactly half of the babies born in a hospital are male, the ratio will not be exactly half inevery time period. On some days, more girls will be born and on others, more boys. The question was, doethe likelihood of deviating from exactly half depend on whether there are many or few births per day? It iswell-established consequence of sampling theory that proportions will vary much more day-to-day whenthe typical number of births per day is small. However, people's answers to the problem do not reflect thisfact. They typically reply that the number of births in the hospital makes no difference to the likelihood of more than 60% male babies in one day. The explanation in terms of the heuristic is that people consider

only how representative the figure of 60% is of the previously given average of 50%. [14][25]

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Dilution effect

Richard E. Nisbett and colleagues suggest that representativeness explains the dilution effect , in whichirrelevant information weakens the effect of a stereotype. Subjects in one study were asked whether "Paul"or "Susan" was more likely to be assertive, given no other information than their first names. They ratedPaul as more assertive, apparently basing their judgment on a gender stereotype. Another group, told thatPaul's and Susan's mothers each commute to work in a bank, did not show this stereotype effect; they ratedPaul and Susan as equally assertive. The explanation is that the additional information about Paul and Susamade them less representative of men or women in general, and so the subjects' expectations about men an

women had a weaker effect.[26] This means irrelative and undiagnostic information about certain issue can

make relative information less powerful to the issue when people understand the phenomenon.[27]

Misperception of randomness

Representativeness explains systematic errors that people make when judging the probability of randomevents. For example, in a sequence of coin tosses, each of which comes up heads (H) or tails (T), peoplereliably tend to judge a clearly patterned sequence such as HHHTTT as less likely than a less patterned

sequence such as HTHTTH. These sequences have exactly the same probability, but people tend to see themore clearly patterned sequences as less representative of randomness, and so less likely to result from a

random process.[14][28] Tversky and Kahneman argued that this effect underlies the gambler's fallacy; atendency to expect outcomes to even out over the short run, like expecting a roulette wheel to come up

black because the last several throws came up red.[17][29] They emphasised that even experts in statisticswere susceptible to this illusion: in a 1971 survey of professional psychologists, they found that respondenexpected samples to be overly representative of the population they were drawn from. As a result, the

psychologists systematically overestimated the statistical power of their tests, and underestimated the

sample size needed for a meaningful test of their hypotheses.[14][29]

Anchoring and adjustment

Anchoring and adjustment is a heuristic used in many situations where people estimate a number.[30]

According to Tversky and Kahneman's original description, it involves starting from a readily available

number—the "anchor"—and shifting either up or down to reach an answer that seems plausible.[30] InTversky and Kahneman's experiments, people did not shift far enough away from the anchor. Hence theanchor contaminates the estimate, even if it is clearly irrelevant. In one experiment, subjects watched anumber being selected from a spinning "wheel of fortune". They had to say whether a given quantity waslarger or smaller than that number. For instance, they might be asked, "Is the percentage of African

countries which are members of the United Nations larger or smaller than 65%?" They then tried to guessthe true percentage. Their answers correlated well with the arbitrary number they had been given. [30][31]

Insufficient adjustment from an anchor is not the only explanation for this effect. An alternative theory is

that people form their estimates on evidence which is selectively brought to mind by the anchor. [32]

The anchoring effect has been demonstrated by a wide variety of experiments both in laboratories and in th

real world.[31][33] It remains when the subjects are offered money as an incentive to be accurate, or when

they are explicitly told not to base their judgment on the anchor.[33] The effect is stronger when people hav

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The amount of money people will pay in anauction for a bottle of wincan be influenced byconsidering an arbitrarytwo-digit number.

to make their judgments quickly.[34] Subjects in these experiments lack introspective awareness of the heuristic, denying that the anchor affected their

estimates.[34]

Even when the anchor value is obviously random or extreme, it can still

contaminate estimates.[33] One experiment asked subjects to estimate the year of Albert Einstein's first visit to the United States. Anchors of 1215 and 1992

contaminated the answers just as much as more sensible anchor years.[34]Other experiments asked subjects if the average temperature in San Franciscois more or less than 558 degrees, or whether there had been more or fewer than 100,025 top ten albums by The Beatles. These deliberately absurd

anchors still affected estimates of the true numbers.[31]

Anchoring results in a particularly strong bias when estimates are stated in theform of a confidence interval. An example is where people predict the valueof a stock market index on a particular day by defining an upper and lower

bound so that they are 98% confident the true value will fall in that range. A

reliable finding is that people anchor their upper and lower bounds too closeto their best estimate.[14] This leads to an overconfidence effect. One much-replicated finding is that when people are 98% certain that a number is in a

particular range, they are wrong about thirty to forty percent of the

time.[14][35]

Anchoring also causes particular difficulty when many numbers are combinedinto a composite judgment. Tversky and Kahneman demonstrated this byasking a group of people to rapidly estimate the product8 x 7 x 6 x 5 x 4 x 3 x 2 x 1. Another group had to estimate the same product

in reverse order; 1 x 2 x 3 x 4 x 5 x 6 x 7 x 8. Both groups underestimated theanswer by a wide margin, but the latter group's average estimate was significantly smaller.[36] Theexplanation in terms of anchoring is that people multiply the first few terms of each product and anchor on

that figure.[36] A less abstract task is to estimate the probability that an aircraft will crash, given that thereare numerous possible faults each with a likelihood of one in a million. A common finding from studies of

these tasks is that people anchor on the small component probabilities and so underestimate the total.[36] Acorresponding effect happens when people estimate the probability of multiple events happening insequence, such as an accumulator bet in horse racing. For this kind of judgment, anchoring on the

individual probabilities results in an overestimate of the combined probability.[36]

Applications

People's valuation of goods, and the quantities they buy, respond to anchoring effects. In one experiment, people wrote down the last two digits of their social security numbers. They were then asked to consider whether they would pay this number of dollars for items whose value they did not know, such as wine,chocolate, and computer equipment. They then entered an auction to bid for these items. Those with thehighest two-digit numbers submitted bids that were many times higher than those with the lowest

numbers.[37][38] When a stack of soup cans in a supermarket was labelled, "Limit 12 per customer", the

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label influenced customers to buy more cans.[34] In another experiment, real estate agents appraised thevalue of houses on the basis of a tour and extensive documentation. Different agents were shown differentlisting prices, and these affected their valuations. For one house, the appraised value ranged from

US$114,204 to $128,754.[39][40]

Anchoring and adjustment has also been shown to affect grades given to students. In one experiment, 48teachers were given bundles of student essays, each of which had to be graded and returned. They were als

given a fictional list of the students' previous grades. The mean of these grades affected the grades thatteachers awarded for the essay.[41]

One study showed that anchoring affected the sentences in a fictional rape trial. [42] The subjects were trialudges with, on average, more than fifteen years of experience. They read documents including witness

testimony, expert statements, the relevant penal code, and the final pleas from the prosecution and defenceThe two conditions of this experiment differed in just one respect: the prosecutor demanded a 34-monthsentence in one condition and 12 months in the other; there was an eight-month difference between the

average sentences handed out in these two conditions.[42] In a similar mock trial, the subjects took the roleof jurors in a civil case. They were either asked to award damages "in the range from $15 million to $50

million" or "in the range from $50 million to $150 million". Although the facts of the case were the sameeach time, jurors given the higher range decided on an award that was about three times higher. This

happened even though the subjects were explicitly warned not to treat the requests as evidence. [37]

Affect heuristic

"Affect", in this context, is a feeling such as fear, pleasure or surprise. It is shorter in duration than a mood,occurring rapidly and involuntarily in response to a stimulus. While reading the words "lung cancer" mighgenerate an affect of dread, the words "mother's love" can create an affect of affection and comfort. When

people use affect ("gut responses") to judge benefits or risks, they are using the affect heuristic.

[43]

Theaffect heuristic has been used to explain why messages framed to activate emotions are more persuasive

than those framed in a purely factual way.[44]

Others

Control heuristicContagion heuristicEffort heuristic

Familiarity heuristic

Fluency heuristicGaze heuristicHot-hand fallacy

Naive diversificationPeak-end ruleRecognition heuristic

Scarcity heuristicSimilarity heuristicSimulation heuristic

Social proof

Theories

There are competing theories of human judgment, which differ on whether the use of heuristics is irrationaA cognitive laziness approach argues that heuristics are inevitable shortcuts given the limitations of thehuman brain. According to the natural assessments approach, some complex calculations are already done

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A visual example of attributesubstitution. This illusion works

because the 2D size of parts of thescene is judged on the basis of 3D(perspective) size, which is rapidlycalculated by the visual system.

Daniel Kahneman, American Economic Review 93 (5) December 2003, p. 1450[49]

rapidly and automatically by the brain, and other judgments make use of these processes rather thancalculating from scratch. This has led to a theory called "attribute substitution", which says that peopleoften handle a complicated question by answering a different, related question, without being aware that

this is what they are doing.[45] A third approach argues that heuristics perform just as well as morecomplicated decision-making procedures, but more quickly and with less information. This perspective

emphasises the "fast and frugal" nature of heuristics.[46]

Cognitive laziness

An effort-reduction framework proposed by Anuj K. Shah and Daniel M. Oppenheimer states that people

use a variety of techniques to reduce the effort of making decisions.[47]

Attribute substitution

In 2002 Daniel Kahneman and Shane Frederick proposed a processcalled attribute substitution which happens without consciousawareness. According to this theory, when somebody makes a

udgment (of a target attribute) which is computationally complex,a rather more easily calculated heuristic attribute is substituted.[48]

In effect, a difficult problem is dealt with by answering a rather simpler problem, without the person being aware this is

happening.[45] This explains why individuals can be unaware of their own biases, and why biases persist even when the subject ismade aware of them. It also explains why human judgments often

fail to show regression toward the mean.[45][48][49]

This substitution is thought of as taking place in the automaticintuitive judgment system, rather than the more self-aware

reflective system.[50] Hence, when someone tries to answer adifficult question, they may actually answer a related but different

question, without realizing that a substitution has taken place.[45][48]

In 1975, psychologist Stanley Smith Stevens proposed that thestrength of a stimulus (e.g. the brightness of a light, the severity of a crime) is encoded by brain cells in away that is independent of modality. Kahneman and Frederick built on this idea, arguing that the target

attribute and heuristic attribute could be very different in nature.[45]

Kahneman and Frederick propose three conditions for attribute

substitution:[45]

1. The target attribute is relatively inaccessible.Substitution is not expected to take place in answering factualquestions that can be retrieved directly from memory ("What isyour birthday?") or about current experience ("Do you feelthirsty now?).

2. An associated attribute is highly accessible.

[P]eople are not accustomed tothinking hard, and are often contentto trust a plausible judgment thatcomes to mind.

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This might be because it is evaluated automatically in normal perception or because it has been primed. For example, someone who has been thinking about their love life and is then asked howhappy they are might substitute how happy they are with their love life rather than other areas.

3. The substitution is not detected and corrected by the reflective system.For example, when asked "A bat and a ball together cost $1.10. The bat costs $1 more than the ball.How much does the ball cost?" many subjects incorrectly answer $0.10.[49] An explanation in termsof attribute substitution is that, rather than work out the sum, subjects parse the sum of $1.10 into alarge amount and a small amount, which is easy to do. Whether they feel that is the right answer wil

depend on whether they check the calculation with their reflective system.

Kahneman gives an example where some Americans were offered insurance against their own death in aterrorist attack while on a trip to Europe, while another group were offered insurance that would cover death of any kind on the trip. Even though "death of any kind" includes "death in a terrorist attack", theformer group were willing to pay more than the latter. Kahneman suggests that the attribute of fear is being

substituted for a calculation of the total risks of travel.[51] Fear of terrorism for these subjects was stronger than a general fear of dying on a foreign trip. See Morewedge and Kahneman (2010), for a recent summary

of attribute substitution.[50]

Fast and frugal

Gerd Gigerenzer and colleagues have argued that heuristics can be used to make judgments that areaccurate rather than biased. According to them, heuristics are "fast and frugal" alternatives to more

complicated procedures, giving answers that are just as good.[52] The benefits of heuristic or 'less is more'decision-making strategies have been observed in a variety of settings, ranging from food consumption, to

the stock market to online dating.[53]

Consequences

Efficient decision heuristics

Warren Thorngate, an emeritus social psychologist, implemented 10 simple decision rules or heuristics in simulation program as computer subroutines chose an alternative. He determined how often each heuristicselected alternatives with highest-through-lowest expected value in a series of randomly generated decisiosituations. He found that most of the simulated heuristics selected alternatives with highest expected valueand almost never selected alternatives with lowest expected value. More information about the simulation

can be found in his "Efficient decision heuristics" article (1980).[54]

"Beautiful-is-familiar" effect

Psychologist Benoît Monin reports a series of experiments in which subjects, looking at photographs of faces, have to judge whether they have seen those faces before. It is repeatedly found that attractive faces

are more likely to be mistakenly labeled as familiar.[55] Monin interprets this result in terms of attributesubstitution. The heuristic attribute in this case is a "warm glow"; a positive feeling towards someone thatmight either be due to their being familiar or being attractive. This interpretation has been criticised,

because not all the variance in familiarity is accounted for by the attractiveness of the photograph.[47]

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Judgments of morality and fairness

Legal scholar Cass Sunstein has argued that attribute substitution is pervasive when people reason about

moral, political or legal matters.[56] Given a difficult, novel problem in these areas, people search for a morfamiliar, related problem (a "prototypical case") and apply its solution as the solution to the harder problemAccording to Sunstein, the opinions of trusted political or religious authorities can serve as heuristicattributes when people are asked their own opinions on a matter. Another source of heuristic attributes is

emotion: people's moral opinions on sensitive subjects like sexuality and human cloning may be driven byreactions such as disgust, rather than by reasoned principles.[57] Sunstein has been challenged as not

providing enough evidence that attribute substitution, rather than other processes, is at work in these

cases.[47]

See also

Behavioral economicsBounded rationalityDebiasingEcological rationalityCognitive miser List of cognitive biasesList of memory biasesLow information voter Methodology of heuristicsAdaptive Toolbox

Footnotes

a. "Heuristic" was originally an adjective and is derived from the Greek word εὑρίσκειν (heuriskein) meaning"serving to discover". Its use as a noun came later, as an abbreviation for "heuristic method" or "heuristic

principle". (Baron 2000, p. 50)

Citations

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