Heuristics the retrievability of instances. Additionally, there is a

Heuristics are “mental shortcuts” that people use to
judge and make decisions when they are presented with limited information. They
are considered to be useful because people are unable to take in an overload of
information. Consequently, people make use of these heuristics as they are
time-saving and rely on simple rules to form decisions. However, these rules
can lead to systematic biases and errors in judgement. This essay will focus on
three heuristics proposed by Tversky and Kahneman (1974) – availability,
representativeness, and anchoring and adjustment – and provide evidence in how
each of these are used to make judgements. It will also discuss whether heuristics
help or harm judgement.

 

The availability heuristic involves judging events on
how easily they come to mind and how vivid they are. For example, Tversky and
Kahneman (1974) asked participants whether traffic accidents/stomach cancer or
suicide/homicide caused more deaths in developed countries. Most participants
responded with traffic accidents and suicide, when in reality more people die
from suicide and stomach cancer. This indicates that traffic accidents and
homicide is more easily recalled therefore, participants tend to overestimate
the likelihood of these events when judging them. In doing so, they are
exhibiting a bias that is correlated media overexposure. For instance, newspapers
reported 137 traffic accidents to just one stomach cancer death. This is
because the media are more likely to report interesting events to capture
attention, thus making events like homicide more noticeable. As a result, more
people are exposed to these reports, which is why they are easier to retrieve. Consequently,
their judgements come from a biased source. Further research support comes from
Lichtenstein, Slovic, Fischhoff, Layman, & Combs (1978) who asked
participants to estimate how many people die from different causes of death
that were listed. Results showed that participants tended to overestimate
melodramatic causes such as tornados and homicide, and underestimated causes
like smallpox. This reinforces how people make biased judgements in relation to
media coverage of salient events. This is known as a bias due to the
retrievability of instances. Additionally, there is a further bias caused by
availability, known as illusory correlation. This is when a relationship
between variables is perceived, even though there is no evidence that this
relationship exists. Chapman and Chapman (1969) investigated the illusory
correlation by asking participants to examine notes containing clinical diagnoses
for a set of patients, some of which had a paranoid diagnosis, and their
drawings of a person. When participants were asked if they observed a
relationship between the diagnoses and drawings, participants mentioned a
correlation between paranoid patients and drawings with strange eyes. However,
no correlation was present but this result was found because participants found
it easier to imagine a link between drawings of strange eyes and paranoia, thus
alluding to the availability heuristic. Consequently, the research highlights
how people use the availability heuristic to make judgements, but it also shows
that this can harm judgement as it leads to a number of biases.

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Additionally, the representativeness heuristic refers
to judging the probability of an event based on past experiences and similarity.
It is mainly used in categorisation, whereby people evaluate the likelihood
that “an event is a member of
category by considering how similar or typical the event is to the category” (Ayton,
2012, p. 20). The representativeness heuristic is useful when people have to
make judgements under uncertainty. This heuristic allows people to use their stereotypical knowledge in
order to form a judgement about a particular person. For example, making an
eyewitness statement about a crime. Under these circumstances, a robber
stereotypically might have long hair, a beard, balaclava and black clothes. As
a result, they can be helpful because it allows you to make a quick decision that
requires little effort. On the other hand, it can lead to false convictions as
it relies on stereotypes, in this example. However, when people judge purely
based on similarity, they have a tendency to ignore the base-rate (i.e. general
information given). Tversky and Kahneman (1973) demonstrated base-rate neglect using
an experiment where participants had to estimate the probability that someone
called ‘Jack’ was an engineer, after reading a description of him. Half the
participants were told that the description was drawn from sample of 70 lawyers
and 30 engineers, and the other half were told he was drawn from 30 lawyers and
70 engineers. The results indicated that participants had a base-rate neglect
as they gave similar estimates regardless of what group they were in.
Consequently, their decision was made on a stereotypical basis. A further bias
within the representativeness heuristic is the conjunction fallacy. People may
rely heavily on representativeness and risk violating a law of probability. For
example, Tversky and Kahneman (1983) conducted an experiment where participants
were given a statement in which “Linda” is the subject. “Linda is 31 years old, single, outspoken and very bright.  As a student she was deeply concerned with
issues of discrimination and social justice, and she participated in
antinuclear demonstrations.” They are then provided with two descriptions;
either she is a “bank teller” or a “bank teller and a feminist” and have to
select which option is more likely. People are more likely to select the more
specific option because of how representative it is of Linda, despite the descriptions
being equally true, demonstrating how people use the representativeness
heuristic leading to use of conjunction fallacy. Using the representativeness
heuristic, therefore, can lead to errors and biases that result from using
stereotypes subsequently harming judgement and decision making. Furthermore, when
people judge the likelihood of random events occurring using the
representativeness heuristic, this can lead to a misperception of randomness. This
links in with the gambler’s fallacy which is the incorrect “idea that past
events will influence future ones even though the results are independent of
each other” (Veares, 2017, para. 4). For example, the belief that after a series
of landing on heads in a game of coin tossing, the next toss would be tails.
People are influenced by gambler’s fallacy as getting heads or tails is equally
likely on the next coin toss. However, the opposite of this fallacy is known as
the hot-hand fallacy which refers to the belief that a sequence of success will
continue. Challenging evidence to this fallacy was put forward by Gilovich,
Vallone, & Tversky (1985) who found that 91% of basketball fans thought a
basketball player would be more likely to score if he was successful in the
previous two or three attempts compared to if he missed his last shots. However,
the researchers found that the probabilities for success is better when you
have failed in the past, thus challenging the hot-hand fallacy. This further
reinforces how the representativeness heuristic can lead to impaired judgement
as people are influenced by fallacies. Nevertheless, recent research such as Green
and Zwiebel (2017)

 has found
supporting evidence for the hot-hand fallacy. They state that “the absence of a
hot hand should not necessarily be interpreted as a cognitive mistake, but
rather, as an endogenous defensive response” (p. 66). For instance, sports such
as basketball invoke this phenomenon. Andrews (2014) explains this study whereby the opposition team dedicate more attention to the
“hot” player and in this way, throw them off balance resulting in a decline of
shooting percentage. “It’s not because the hot streak was an illusion, but
rather that the hot player attracted more opposition” (para. 11). As a result,
this suggests that people are correct in believing in this fallacy and this may
not harm judgement after all.

 

Lastly, the third heuristic principle, anchoring and
adjustment, is used to make estimates whereby, people usually begin at an
initial target (the ‘anchor’) and then adjust this to reach a final estimate. Tversky
and Kahneman (1974) demonstrated the anchoring effect by asking participants to
spin a wheel which landed on percentages. The wheel was set up to always land
on either 10% or 65%. After this, participants were then asked about the
percentage of African nations in the United Nations (UN) relative to one of
these percentages. They were then asked to guess the actual percentage of
African countries in the UN. Participants who landed on 10% tended to guess
around 25%, while 45% was the mean estimate for participants who landed on 65%.
This illustrates how a random number generated provided an anchor which
participants used to adjust their estimates. This heuristic is commonly used
within jobs such as real estate and car sales. For example, if you saw the
price of a house in one area, it would then influence how you perceived other
houses, either cheap or expensive in comparison. If the sales person or real
estate agent shows their customers a higher price initially, a more reasonable
lower price will be perceived as a good deal later. Northcraft and Neale (1987)
found research evidence of this heuristic in real estate agents. The agents viewed
a house and were given a booklet of information about the house (e.g. features
of the house, square footage etc.). They were also told what the seller thought
the house was worth which was either high ($83,900) or low ($65,900). The agents
claimed this was unimportant but it did affect their judgements, as this
information did influence their perception of the price when making their estimates.
Additionally, the majority of research into heuristics uses laboratory methods
and this does not represent real life. These artificial settings may produce
the use of heuristics in people, whereas this study acknowledged the bias that
heuristics can elicit, but provided adequate information to real estate agents (Hogarth,
1981). Consequently, the anchoring and adjustment heuristic can be helpful in
making real-life decisions like buying a car or house, especially if you are
uncertain as it exerts a considerable amount of influence. Moreover, it can
also help to increase profit in marketing companies.

 

In conclusion, research has shown that availability,
representativeness, and anchoring and adjustment heuristics can be used to form
decisions and make judgements. As a result, they can be helpful because it
allows people to come to a decision in a time-efficient and simple way.
However, heuristics can be susceptible to biases and errors such as the
illusory correlation, base-rate neglect, conjunction fallacy and many more. Based
on the evidence given, it reveals that heuristics can be harmful when it comes
to judgement and decision-making as many people are influenced by the biases
associated with these heuristics. 

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