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Expertise and the Illusion of Expertise in Gambling

Authors:

Abstract

This chapter presents the concept of the illusion of expertise - the belief that one possesses a higher level of specific knowledge or skill than objectively justified, in a domain in which one has prolonged experience, and possesses other knowledge or skills. This chapter integrates research in the psychology of expertise with the problem gambling literature. We use expertise theories - chunking theory (Chase & Simon, 1973) and template theory (Gobet & Simon, 1996) - to propose explanations of the mechanisms underlying gambling expertise, cognitive biases in gambling, and the illusion of expertise in gambling. We suggest that the concept of the illusion of expertise could be useful to understanding problem gambling and to implementing problem gambling interventions.
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Expertise and the Illusion of Expertise in Gambling
Guillermo Campitelli
Craig Speelman
Edith Cowan University
Author Note
We are thankful to the School of Psychology and Social Science, Edith Cowan University, for the
funding provided to participate in the 2011 London Problem Gambling Workshop.
Guillermo Campitelli. School of Psychology and Social Science, Edith Cowan University, 270
Joondalup Drive, Joondalup, 6027, Western Australia. Tel: 00 61 8 6304 5736. Email:
g.campitelli@ecu.edu.au
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Abstract
This chapter presents the concept of the illusion of expertise - the belief that one possesses a
higher level of specific knowledge or skill than objectively justified, in a domain in which one
has prolonged experience, and possesses other knowledge or skills. This chapter integrates
research in the psychology of expertise with the problem gambling literature. We use expertise
theories - chunking theory (Chase & Simon, 1973) and template theory (Gobet & Simon, 1996) -
to propose explanations of the mechanisms underlying gambling expertise, cognitive biases in
gambling, and the illusion of expertise in gambling. We suggest that the concept of the illusion of
expertise could be useful to understanding problem gambling and to implementing problem
gambling interventions.
Keywords: gambling, expertise, illusion of expertise, problem gambling
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Running head: ILLUSION OF EXPERTISE 3
Expertise and the Illusion of Expertise in Gambling
Research on the phenomenon of problem gambling could be characterised as the
investigation of factors involved in the acquisition, development and maintenance of gambling
behaviour. In this chapter we aim at integrating the problem gambling research field with the
psychology of expertise research field in two ways. First, we address the issue of acquisition of
expertise in gambling using theories of expertise. Second, we introduce the concept of the
illusion of expertise, as one of the possible causes of the maintenance of problem gambling.
The reader may have already identified that research on expertise could be useful to
understanding games such as poker in which chance and skill are involved. On the other hand,
expertise studies are not useful for investigating games such as a lottery, in which skill cannot
change the probability of success. The interesting twist in this story is that research on “expert
judgment” has identified that in some fields experts make biased judgments, or are overconfident
in their judgements. Since overconfidence is a phenomenon typically found in problem gambling
(Goodie, 2005), research on expertise and expert judgment not only could be relevant to the
investigation of the skillful components of gambling, but also could shed light on the
investigation of factors involved in problem gambling.
This chapter has the following structure. The first section discusses gambling as expert
behaviour; the second section tackles the issue of problem gambling. The third section introduces
the concept of the illusion of expertise; the fourth section proposes an explanation of problem
gambling using a theory of expertise. Finally, we discuss these issues and draw some
conclusions.
Given that expertise has been investigated independently in the field of cognition and the
field of judgment and decision making, and that the results found in these literatures are very
different –(i.e., experts are better than novices in cognitive studies (e.g., Campitelli & Gobet,
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2004, 2005), experts are poor at making judgments in the judgment and decision-making
literature (Shanteau, 1988, 1992; Oskamp, 1965)–, we introduce the cognitive studies of
expertise in the section of gambling as expert behavior, and the judgment and decision-making
studies of expertise in the problem gambling section. The sections on the illusion of expertise
and the explanation of problem gambling using a theory of expertise represent a unique
combination of the domains of gambling studies and expertise.
Before we present the sections indicated above, and given its importance in the whole
chapter, we anticipate here the definition of illusion of expertise, and we discuss it in the
corresponding section. We define the illusion of expertise as the belief that one possesses a
higher level of specific knowledge or skill than objectively justified, in a domain in which one
has prolonged experience, and possesses other knowledge or skills.
Gambling as expert behaviour
In this section we propose that some gambling games are games of skill, and thus could
be investigated under the framework of expertise. We first describe the field of expertise as
investigated in cognitive psychology, then we briefly review a few studies in which a gambling
game (i.e., poker) was investigated using the expertise approach, and finally we apply a theory of
expertise developed in the context of chess to poker expertise.
Expertise in cognitive psychology
The study of expert cognitive processing has been strongly influenced by Chase and
Simon’s (1973) chunking theory. This theory states that the key to understanding the acquisition,
development and maintenance of expertise is that, in the course of acquiring their skill, experts
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Running head: ILLUSION OF EXPERTISE 5
learn domain-specific patterns (i.e., chunks) that get stored in long-term memory (LTM).
Chunks are described as “a collection of elements having strong associations with one another,
but weak associations with elements within other chunks” (Gobet, Lane, Croker, Cheng, Jones,
Oliver, et al., 2001, p. 236). When experts make a decision (e.g., a chess grandmaster has to
decide which move to play in a specific position) they engage in “search behaviour”, which
consists of generating possible courses of action (e.g., a move in chess), and its consequences
(e.g., the possible responses of the opponent). Since the human cognitive system has limitations,
it is impossible to search all the possibilities exhaustively. In order to search for possibilities
efficiently skilled players use heuristics, or rules of thumb that afford them the possibility to
eliminate irrelevant possibilities from the analysis, thus limiting the necessary search. These
strategies and heuristics rest upon the recognition of chunks. When a situation (or part of it) in a
game matches one or more chunks stored in LTM, the expert player has quick access to
information associated with these chunks. For example, a typical configuration of chess pieces
may be associated with an advantageous move or a typical strategy.
Gobet and Simon (1996) acknowledged some anomalies of the chunking theory and
developed the template theory. This theory maintains the core of chunking theory, and
incorporates the concept of a template. Templates are also domain-specific configurations of
items that appear more or less frequently in situations of the domain. Besides being larger than
chunks (indeed, chunks could evolve into templates when they appear frequently in the
environment and a connection is formed between them), templates contain slots in which
additional information can be placed. Also individual items or chunks could be placed into the
slots. The templates are implicitly acquired by experts in the course of their exposure to the
domain-specific environment.
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Some aspects of chunking theory and template theory have been implemented in a
computational model called CHREST (Gobet et al., 2001; Gobet & Simon, 2000; see also an
application of CHREST to problem gambling in Gobet & Schiller, 2011; Gobet & Schiller, this
book). Here we only present a very general explanation, focusing on the issues that are relevant
for this chapter. In order to simulate human learning, CHREST is trained by being presented a
large number of domain-specific situations (e.g., chess positions in the case of chess). When
items appear together in several situations chunks are formed by establishing connections
between individual items. With extended exposure to situations chunks may evolve into
templates by establishing connections among them. For example, a chess player observes that
grandmasters always play the same move in a specific position. Therefore, a possible course of
action (i.e., that move) is associated with the representation of the situation stored in LTM (i.e.,
the template that corresponds to that specific position). Also, the chess player may observe that
the white side always wins when that move is played by grandmasters. This information (i.e.,
“this position is advantageous for white”) is added to one of the slots of the template. Hence,
every time that the player encounters the same position in the future he/she will quickly
recognise the situation (because the template stored in LTM gets activated), and will have
immediate access to the associated information, and the best course of action.
Experimental research has shown that performance in domain-specific memory tasks is a
function of the level of expertise, and computational simulations with CHREST suggest that this
phenomenon is well accounted for by the number of templates and chunks stored in LTM (e.g.,
Gobet & Simon, 2000). Research also shows that experts of higher levels outperform novices (or
experts of lower levels) in domain-specific problem-solving tasks (e.g., Campitelli & Gobet,
2004; Connors, Burns, & Campitelli, 2011), domain-specific imagery tasks (Campitelli & Gobet,
2005), and that the former search for possible options more selectively than the latter, when they
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are solving problems (e.g., DeGroot, 1978). Finally, brain imaging evidence is starting to identify
the localization of the domain-specific LTM network (e.g., Campitelli et al., 2007; Bilalic,
Turella, Campitelli, Erb, & Grodd, 2012).
Another important issue introduced in Chase and Simon's (1973) seminal article is their
proposal that the attainment of high levels of expert performance requires acquiring a large
number of domain-specific patterns (i.e., 50,000 chunks). Therefore, this is a process that
develops over a long period of time (i.e., about 10 years of intense dedication). This proposal
was adopted by Ericsson, Krampe and Tesch-Römer (1993) who developed the “deliberate
practice” (DP) framework. This framework proposes that expert performance is a monotonic
function of the amount of DP. DP consists of training activities that are aimed at correcting
mistakes, and are characterised by optimal feedback (e.g., provided by a coach, published
material or software). There is evidence that a large amount of DP is a necessary condition to
achieve high levels of expert performance in several domains such as music (Ericsson et al.,
1993), chess (Gobet & Campitelli, 2007; Charness, Tuffiash, Krampe, Reingold, & Vasyukova,
2005), SCRABBLE (Tuffiash, Roring, & Ericsson, 2007), and sports (Helsen, Starkes, &
Hodges, 1998; Starkes, Deakin, Allard, Hodges, & Hayes, 1996); but there is also evidence that
DP is not a sufficient condition to achieve expert performance (Campitelli & Gobet, 2011;
Hambrick, Oswald, Altmann, Meinz, Gobet & Campitelli, in press), and that other factors are
also involved. For example, Gobet and Campitelli (2007) showed that the age at which chess
players start studying seriously is a good predictor of expert performance after controlling for
hours of practice, and Meinz and Hambrick (2010) showed that working memory capacity is a
significant predictor of music reading, above and beyond hours of practice.
In summary, the expertise literature in cognitive psychology shows that performance in
domain-specific tasks is a function of the level of expertise, that a plausible explanation of this
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phenomenon is the existence of a large network of chunks and templates associated with courses
of action and relevant information stored in LTM, and that differences in the size of that network
are mainly explained by the amount of time dedicated to the field. In the next section we discuss
whether this explanation of expertise could be applied to gambling.
Cognitive psychology of expert gambling
Poker is a gambling game that involves an element of skill. Croson, Fishman and Pope
(2008) investigated the extent to which poker involves skill versus chance by regressing the rank
of players in a current poker tournament over the rank of the same players in previous
tournaments. If poker were a game of chance the rank on previous tournaments should not
significantly predict the rank in a current tournament. They found that rank in previous
tournaments was a significant predictor of the current tournament rank. Although the variance
accounted for by the predictor variable was only 2.8%, this was comparable to a similar analysis
in golf – a sport that is considered a game of skill. Parke, Griffiths and Parke (2005) identified a
number of skills involved in poker: critical-evaluative, numerical, pragmatic, interpersonal,
problem solving, goal orientation, learning, higher-order analytic and strategic, flexibility, face
management/deception, self-awareness, and self-control. They proposed that some of these skills
are transferable to everyday life situations.
Research on gambling using expertise paradigms has been scarce. Dedonno and
Detterman (2008) trained a group of students in poker strategies and another group received
information in poker history. Both groups played a number of hands before treatment and after
treatment. There was no difference in profits between groups before treatment, but there was a
significant difference between groups after treatment, with the strategy group outperforming the
history group. This result was replicated in a second experiment, in which strategy instruction
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also influenced the number of hands played. (Playing a small percentage of hands – less than
15% of hands dealt - is a marker of skilled playing in poker).
St. Germain and Tenenbaum (2012) asked three groups of poker players [experts (13
years, and 39,200 hours of poker-playing experience, on average), intermediate players (7.1
years, and 1,990 hours), and novices (2.4 years, 23.9 hours)] to play 60 hands of a computerised
version of Texas Hold’Em poker, and report out-loud what they were thinking while playing.
They found a skill effect in the average expected value of bets, and in earnings. They also found
that experts generated more verbalizations categorised as “opponent behaviour” and “advanced
poker considerations”, whereas the novices produced more verbalizations categorised as “basic
poker considerations” and “other” (this category includes thoughts such as “feeling lucky”,
“angry with one player”, “scared to raise/bet”). Finally, Meinz, Hambrick, Hawkins, Gillings,
Meyer and Schneider (2012) studied the role of number of hours of dedication, domain-specific
knowledge, and working memory capacity (WMC) on performance in tasks that measure Texas
Hold’Em poker skill. They found that the number of hours of dedication is a strong and
significant predictor of domain-specific knowledge, which in turn is a strong and significant
predictor of poker tasks. They also found that WMC was a significant predictor of performance
in poker tasks.
Although the literature on expert gambling is scarce it seems that the results are similar to
those in other fields of expertise. High-level players outperform lower-level players in
representative tasks of the field, they make bets that are objectively better, and they earn more
money. Moreover, the skill levels could be differentiated in terms of the numbers of hours of
dedication. In the next section we put forward an explanation of expert gambling using template
theory and CHREST.
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Chunks, templates and gambling
The results presented above suggest that, although chance is an important component,
poker is a game of skill. This implies that template theory (Gobet & Simon, 1996) and CHREST
(Gobet et al., 2001) could explain skilled performance in a gambling game such as poker. Indeed,
expertise in poker could be accounted for by, at least in part, a network of chunks that associate a
card configuration with a course of action. For example, the fact that expert players play less
than 15% of the hands dealt, and inexperienced players play too many hands could, in part, be
accounted for by a difference between experts and inexperienced players in the network of
chunks stored in LTM. An expert player that receives the cards 4-8 in Texas Hold’Em poker
recognises a chunk stored in LTM with these numbers that is associated with the actions “pass or
fold, but never bet”. On the other hand, an inexperienced player may not have any course of
action associated with this chunk, so his/her decision to play this hand depends on incidental
factors such as “feeling lucky”.
More complex strategic behaviour in poker requires a more complex explanation. The
concept of a template is useful to provide an account of such behaviour. A template may include
information about the cards one is holding, the communal cards, the number of players playing
the hand, the position of oneself in the table, the number of chips available, and the betting
behaviour of the participants in the hand. In some cases such a template would be associated
with a clear-cut course of action (e.g., go “all in”), and in other cases with general strategic
concepts (e.g., “the odds are in my favour in this situation, but only slightly”).
Summing up, some gambling games could be considered games of skill, and the theories
that explain expert behavior could be used to explain expert gambling behaviour. An interesting
issue that is considered later is that a large network of chunks could be associated with chunks
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that lead to bad outcomes. The proposal in this chapter is that a large network of chunks that lead
to bad outcomes could be a key factor in the maintenance of problematic gambling behaviour.
Unfortunately, expertise in gambling is not the whole story. Gambling can be a very
damaging activity for some people. A continuous biased assessment of the chances of winning
leads to problem gambling. Interestingly, the literature on expert judgment and decision making
shows examples in which some experts make biased judgements. In the following section we
discuss the relationship between problem gambling and expert judgement.
Problem gambling and its relationship to expert judgement
The picture that we get from the literature on expertise in cognitive psychology is that
experts outperform (or are better than) novices most of the time. The task of expertise
researchers is to explain the nature and development of expert performance. The field of expert
judgment has a different goal: it aims at determining whether experts are rational in their
judgements. The findings in this research field are not encouraging: in some domains experts’
judgements are flawed. We believe that this line of research is relevant for the investigation of
problem gambling. Regular gamblers, as experts, have prolonged experience in their field; thus,
we propose that some of the irrational thoughts of problem gamblers could be maintained for the
same reason that experts make inconsistent judgements. In the following sub-section we briefly
describe the literature in expert judgement, and in the subsequent sub-section we briefly review
the literature on cognitive biases in problem gambling.
Expert Judgement
Studies with medical doctors, clinical psychologists, and other experts, have shown that
the judgements of experts are frequently invalid and unreliable. For example, Goldberg (1959)
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had 4 practicing clinical psychologists, 10 student interns, and 8 naive subjects examine Bender-
Gestalt protocols. The accuracy for all groups fell between 65% and 70% (where 50% is chance).
Oskamp (1965) had clinical psychologists and students study a clinical case and asked questions
about the case in four stages. He also asked the participants to provide a confidence judgement
about their performance. The results show that the participants did not increase their accuracy
from stage 1 (26%) to stage 4 (28%). On the other hand, their confidence increased from stage 1
(33%) to stage 4 (53%). Further, no difference was found between expert clinicians and students.
Einhorn (1974) found that the reliability of judgements of medical pathologists (as measured by
the correlation between two judgements of the same case at different points in time) was only .5.
Moreover, Trumbo, Adams, Milner and Schipper (1962) studied licensed grain judges and found
that experience increased their confidence in judgments, but not necessarily their accuracy. This
indicates that the phenomenon of overconfidence that is found in the general population
(Lichtenstein, Fischhoff, & Phillips, 1982) and in problem gamblers (Goodie, 2005) is also found
in experts.
Gervais and Odean (2001) proposed a mathematical model to explain why professional
investors are overconfident (e.g., Odean, 1999). In Gervais and Odean's model overconfidence is
learned because investors updated their beliefs on their skill accurately when their investment is
not successful, but with a learning bias when it is successful. This model is interesting since,
unlike most models of overconfidence, it takes into account the learning process. Indeed, our
proposal of the illusion of expertise adopts a learning perspective. However, the model has a
problem in that a learning bias is assumed, but not explained. Explanation of the learning bias is
not the purpose of this financial model, which aims at providing evidence that overconfident
investors could survive in the market for a long while, despite trading more than they should.
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However, explaining, rather than assuming, the learning bias is important from a psychological
stand point.
The conclusion from the literature on expert judgment is that experts do not always
outperform novices, their judgments could be unreliable and they could also be overconfident.
The existence of overconfidence in experts is very intriguing. We hypothesise that, indeed, the
sheer fact that someone is considered an expert by peers could lead them to make a biased
evaluation of the likelihood of success. We refer to this phenomenon as the illusion of expertise,
which we discuss later in the chapter.
Note, however, that, as reported by Shanteau (1988), not all the fields of expertise show
biased judgment and/or overconfidence: for example, livestock judges and weather forecasters
were found to be competent decision makers. In an attempt to reconcile these two opposing
findings, Shanteau (1992) proposed that the difference in performance among fields of expertise
is due, in part, to the characteristics of the tasks. One explanation for this difference is that good-
performance domains generally involve decisions about objects or things, (i.e., the stimuli are
relatively constant), and problems are more predictable, whereas bad-performance domains
involve decisions about behavior, and problems are less predictable (see Shanteau, 1992, Table 2
for a full list of task characteristics). Since predictability in gambling games is low, it is not
surprising that gambling is a field in which biased judgment is apparent. In the next section we
examine the literature on cognitive biases in gambling.
Cognitive biases in gambling
The previous section described the poor performance of experts’ judgments in some
fields. Paradoxically, the literature on expert judgment has a lot in common with the
literature that studies the underlying mechanisms of problem gambling: they both show
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that individuals commit serious cognitive biases when they make judgments and/or
decisions.
Studies that use the think aloud protocol technique have shown that gamblers produce a
great number of irrational statements (e.g., Delfabbro & Winefield, 2000; Griffiths, 1994) such
as attributing personal qualities to gambling machines, the gambler’s fallacy (i.e., the belief that,
for random events, runs of a particular outcome (e.g., heads on the toss of a coin) will be
balanced by a tendency for the opposite outcome (e.g., tails)), attribution of wins to skill and
losses to external factors (Gilovich, 1983).
One of the most investigated biases is the “illusion of control” (Langer, 1975). Langer
defines the illusion of control as ‘‘an expectancy of a personal success probability
inappropriately higher than the objective probability would warrant’’ (p. 313). Langer introduced
aspects of a skill (i.e., choice, stimulus or response familiarity, passive or active involvement and
competition) in a situation in which chance, not skill, determines the outcome. In several
experiments they found that the participants behaved as if they had control in a situation of
chance. In the first experiment the participants bet more if they were competing against a
confident confederate than if they were competing against a nervous confederate. In the second
experiment a group of participants that had chosen a lottery ticket were willing to sell the ticket
for $8.67 on average, whereas a group of participants who held a lottery ticket chosen by
someone else were willing to sell the ticket for $1.96, on average. In the third experiment they
found that the familiarity of a lottery ticket (i.e., the familiar ticket had letters, the unfamiliar had
symbols) had an impact on the decision to change the ticket for a ticket of another lottery with
higher chances of winning, with the participants having the letter tickets being more willing to
keep the original ticket. In another experiment the confidence to perform a chance task was
influenced by the degree to which the participants were involved with the task, with more
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confidence shown by the participants that were more involved. In another experiment Langer
shows that the more people think about a lottery the more confident they are on winning the
lottery.
Langer (1975) proposes that the reason why people approach a chance situation that
resembles a skill situation with a skill orientation is that people are motivated to control their
environment, and people try to avoid the negative consequences that accompany the perception
of having no control. Langer’s findings have been corroborated on many occasions (e.g., Chóliz,
2010; Griffiths, 1990b; Ladoceur & Sevigny, 2005; Langer & Roth, 1975). Ladoceur and
Sevigny (2005) indicated that video lottery machines offer players the possibility of using
numerous unnecessary accessories. The existence of these accessories may create the illusion of
possessing a certain control over the machine, chance, or outcomes. The pseudo reels-stopping
device allows players to believe that they can stop the spinning of the reels by exerting pressure
on the screen.
Ladoceur and Walker (1996) stated that the cognitive approach to problem gambling
argues that problem gamblers continue playing because they possess distorted beliefs that cause
them to overestimate their chances of winning. Also, Goodie (2005) developed the Georgia
Gambling Task (GGT) to measure overconfidence in gambling. He found that problem gamblers
were more overconfident than non-problem gamblers, which in GGT means that they also lose
more money.
Although the existence of cognitive biases in problem gamblers is apparent, there are
reasons to believe that cognitive biases on their own cannot explain why people continue
gambling despite severe losses. First, although cognitive biases are important in problem
gamblers, these biases are also found in the general population, and even in some experts. Even
though the biases are more prevalent in problem gamblers, this may not mean that problem
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gamblers are less rational than the general population. Delfabbro (2004) indicated that the fact
that regular slot-machine players are more likely to have irrational beliefs than non-problem
players (Griffiths, 1994) does not mean that the former are more irrational than the latter, but that
the regular players have a wider repertoire of irrational beliefs due to greater experience (i.e.,
they have had more time to learn new associations and strategies). Moreover, Griffiths described
the paradoxical situation in which gamblers know that they cannot “beat the house”, but they still
believe they can win.
The regular slot-machine player who is aware that “the house always wins” may believe
that he/she will eventually find a trick or system that affords the possibility to exploit some flaw
in the design of the machines. And this belief may be supported by the actual accumulation of
knowledge about slot-machines due to prolonged gambling experience. As indicated by
Delfabbro (2004), this is not entirely irrational: some slot-machines are arranged to have higher
pay-offs than others, and discovering this requires skilled observationi.
The illusion of expertise in problem gambling
The expert judgment literature shows that in some fields experts believe that they have a
much higher level of skills or knowledge than their objective level of knowledge or skill. This
may be the case because those experts have prolonged experience in the field, peers recognize
them as experts, and indeed they have a great amount of knowledge in the field, which may not
be useful in a specific judgment situation. We call this “the illusion of expertise”ii. We define the
illusion of expertise as the belief that one possesses a higher level of specific knowledge or skill
than objectively justified, in a domain in which one has prolonged experience, and possesses
other knowledge or skills. Beyond the examples described in the expert judgment literature, other
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examples could be put forward: a politician who has excellent skills on how to be elected and
believes that he/she could make sound policy decisions; a football fan who has extended
knowledge about his team and believes that he/she has knowledge about strategies of the game; a
science journalist who has strong skills in interviewing scientists and believes he/she can put
forward a scientific theory.
In this chapter we propose that one of the factors that maintains problematic gambling
behavior is the illusion of expertise. The illusion of expertise is not the same as the illusion of
control. The latter is a short-term effect that, as described above, could be induced by an
experimental manipulation in a non-problem-gambling sample. On the other hand, the illusion of
expertise is a long-term effect and requires extended experience in a field.
The concept of illusion of expertise is similar to that of illusion of skill. We first briefly
describe studies based on the latter concept, and then we explain why we prefer the former
concept. Griffiths (1990a,b, 1994) and Fischer (1993) studied the role of skill and perceived skill
in problem gambling. Slot machine players develop a number of skills that create the illusion that
their chances of winning are higher. For example, some regular gamblers acquire the “knowledge
of the reels” (i.e., knowing the exact sequence of symbols of the reels). They also develop a
number of heuristics and strategies to identify which machine has recently paid off. Moreover,
Griffiths (1993) found that regular gamblers rated themselves more skillful than the average fruit
machine player.
Ladoceur and Sevigny (2005) studied the illusion of skill in video lottery players, taking
advantage of the lottery terminal stopping device (i.e., a device by which gamblers could
voluntarily stop the spinning of the reels). Since this stopping device does not objectively
improve the probabilities of winning (see Griffiths, 1994), it is interesting to know whether
gamblers believe that “skillfully” using the stopping device improves the probabilities of
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Running head: ILLUSION OF EXPERTISE 18
winning. They asked participants to answer the following question: “If you were to obtain a
winning combination, would it be due to chance, skill or a combination of the two? Why is that?”
They found that gamblers believe that there is an element of skill in the use of the stopping
device, and that their chances of winning are higher when they can use the device.
Since the concept of the illusion of skill was not very clearly defined in the literature of
problem gambling, we decided to refer to this phenomenon as “the illusion of expertise”. This
choice affords us the possibility of emphasising that, in some respects, problem gamblers behave
as experts. For example, Delfabbro (2004) indicates that even in 100% chance games there is
skill involved in learning rules. Also, even in slot-machines players can select machines that lose
less than others, which involves knowledge or skills. We also want to emphasise the fact that the
extended experience in the field of gambling plays an important role in the maintenance of
irrational beliefs.
The illusion of expertise does not always arise; a number of conditions should be met.
First, the illusion of expertise occurs when a gambler makes clear efforts to acquire knowledge
or skills that he/she believes will help improve the probabilities of winning. For example, the
lottery gambler whose only involvement with gambling is buying the lottery ticket and checking
the results may have cognitive biases, but not the illusion of expertise. On the other hand, if the
lottery gambler reads books or websites that present “systems” on how to earn money playing
lottery, he/she may develop the illusion of expertise. Second, the (irrelevant) knowledge or skills
acquired should be strongly related to the gambling situation. For example, a regular slot-
machine player will not develop the illusion of expertise in poker playing. This gambler would
know that the “skills” he/she is acquiring in a field are not transferable to another field. Third, the
chances of success do not improve (or slightly improve) in the process of acquiring the irrelevant
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Running head: ILLUSION OF EXPERTISE 19
skills. For example, the professional poker player does not develop the illusion of expertise,
instead he/she becomes a poker expert.
In the next section we propose how the illusion of expertise and cognitive biases could be
explained using the expertise theories presented above (i.e., chunking and template theories).
Chunks and templates in problem gambling
Our claim in this chapter is that problem gamblers behave as experts in some fields. The
challenge in this section is to entertain the possibility that the theories that explain expert
performance - template theory (Gobet & Simon, 1996) and/or CHREST (Gobet et al., 2001) -
could also be applied to account for irrational gambling behavior. Here we present a general
explanation; please refer to Gobet and Schiller (this book) for a detailed implementation of
problem gambling behavior in CHREST.
Template theory (Gobet & Simon, 1996) and CHREST (Gobet et al., 2001) explain
expertise mainly as an accumulation of chunks and templates in LTM associated with courses of
action or information. The accumulation of chunks and templates does not guarantee expert
performance. Expert performance occurs if the courses of action or information associated with
the chunks lead to an advantageous situation.
For example, in the course of his/her chess career, a club chess player accumulates
chunks and templates related to his/her favourite opening. These chunks and templates associate
with typical courses of action and other types of information. All these pieces of knowledge
allow the club player to play his/her favorite opening with confidence. However, this opening
leads to inferior positions if the opponent plays well. Hence, even though the chess player is
learning chunks and templates, his probability of winning does not increase, or increases very
slightly but remains very low. Similarly, regular gamblers store domain-specific chunks and
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Running head: ILLUSION OF EXPERTISE 20
templates associated with courses of action and information in their LTM. For example, the
gambler’s fallacy in a roulette player could be accounted for by the existence in LTM of a chunk
of four consecutive blacks, associated with the information “it is highly likely that next ball will
be a red” and the course of action “bet red”. Likewise, the chunk of four consecutive odd
numbers may be associated with the information “it is highly likely that the next ball will be
even”, and the course of action “bet even”. Of course, in both cases the associated information is
not learned by experience, because repeated experience shows that after four consecutive blacks
or odds the chances of red and even are equal to that of black or odds, respectively. Rather, this
information is typically learned from other gamblers or other unreliable sources.
The regular gambler, in comparison to a non-gambler may develop a larger repertoire of
chunks related to 4 consecutive outcomes. For example, the outcomes 22-16-31-7 may not have
a meaning to the novice player; on the other hand, the regular roulette gambler may quickly
identify this sequence as 4 consecutive 1st column outcomes due to the existence of the chunk
22-16-31-7 associated with the pieces of information “four consecutive 1st column outcomes”,
and “it is highly likely that the next would be 2nd or 3rd column numbers”, and the course of
action “bet 2nd or 3rd column numbers”. The fact that the regular gambler is much more skillful
than a novice player in recognizing patterns contributes to the illusion of expertise. The regular
gambler rightfully perceives him/herself as more skilful than other players, and thus he/she
believes that his/her chances of winning are higher, when in fact they are not.
A similar explanation could be proposed in relation to regular slot-machine gamblers. As
explained in detail by Griffiths (1994), regular players possess a number of skills. For example,
“knowing the reels” (i.e., knowing the exact sequence of symbols in the reels) is a skill that is
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acquired by accumulation of chunks (a sequence of 3 or 4 symbols) that evolve into a template
(i.e., the whole sequence of symbols in the reel) by the combination of chunks. Also, the regular
player knows all the functions of the available buttons: this skill is acquired by learning the
association between a chunk (e.g., a specific button) and the action associated with it. The
accurate perception of the regular gambler that he/she is more skillful than other players in this
aspect of the game may lead to the illusion of expertise.
Discussion
There are two important problems in the phenomenon of problem/pathological gambling:
the easy one – why do people gamble? - and the difficult one – why do people continue gambling
despite severe monetary losses that impact their financial and personal well-being and that of
their families? People gamble because gambling can be a rewarding activity in many ways. For a
small minority (i.e., professional gamblers) gambling is financially rewarding, and it becomes a
profession. For the majority gambling is entertaining, an intellectual challenge, and/or an
interesting social activity. The losses incurred in gambling could be considered fees paid to have
a good time. However, for an important minority, the maintenance of gambling behavior signifies
significant financial losses, destruction of families, etc. In this chapter we propose the concept of
the illusion of expertise as one possible explanation for why people continue gambling.
The innovative approach of this chapter is that we combine gambling with expertise. In
some gambling games (notably poker) acquisition of expertise is possible. By studying and
practicing poker, players become better and better, and they can make a living out of it.
Moreover, as discussed by Parke, Griffiths and Parke (2005), skills developed in the course of
acquiring poker expertise may be transferable to other life situations. The study of cognitive
processes underlying expertise has been dominated by the game of chess. There are no reasons
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Running head: ILLUSION OF EXPERTISE 22
why expertise in poker should not receive the same attention as chess. Indeed, for the sake of
generalizability, the investigation of poker expertise would be an important endeavour.
On the other hand, gambling is a field in which a huge number of skills that are irrelevant
for the purpose of earning money could be developed. Hence, the illusion of expertise is quite
probable in this field, and the consequences could be catastrophic for the regular gambler. We
defined the illusion of expertise as the belief that one possesses a higher level of specific
knowledge or skill than objectively justified, in a domain in which one has prolonged experience,
and possesses other knowledge or skills. We discussed some conditions that have to occur for the
illusion of expertise to appear, and we finally used theories of expertise to explain the illusion of
expertise and biased thinking.
We believe that our conceptualisation of the illusion of expertise is useful for theoretical
and practical purposes. For example, if a case of problem gambling is related to the illusion of
expertise, interventions that aim at changing cognitive biases would be fruitless. If information is
given to avoid cognitive biases, the problem gambler who is under the illusion of expertise will
change one type of bias for another. This is because the problem gambler still believes s/he is an
expert in the field. The fact that some of her/his thoughts were not rational indicates that the
strategies were not correct, but it does not stop the problem gambler searching for (or inventing)
new strategies. Hence, in this case the illusion of expertise should be targeted. However, the
intervention should be cautious. Delfabbro (2004) rightfully suggests that in problem gambling
interventions two issues should be kept separate: the belief of the possession of skills (which
could be accurate), and the belief of the chances of winning (which is usually inaccurate in
problem gamblers). We suggest that telling the gambler that s/he is under the illusion of expertise
may infuriate her/him. S/he believes s/he is in the process of acquiring skills that eventually
would lead to success. Since this, in some cases, has a degree of truth, this type of intervention
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would fail. An intervention that may have better chances of success in problem gamblers under
the illusion of expertise should make clear to the gambler that s/he is, indeed, an expert in the
field of gambling. Moreover, disputing the belief that the gambler may eventually discover a
method to “beat the house” may not be a good idea either.
Instead, interventions to tackle the illusion of expertise should concentrate on the costs of
acquiring expertise. Experts spent thousands of hours acquiring high-levels of expertise.
Moreover, as shown in Campitelli and Gobet (2011), spending a huge amount of time in
dedication to a field is a necessary condition to achieve high levels of expertise, but is not
sufficient. Some chess players dedicate more than 30,000 hours to chess and do not achieve a
high-level of expertise in chess. Even players that do achieve this level of expertise may not be
able to make a living out of it. The same applies to other fields such as music and sports. Only a
small fraction of the individuals that start a music or sport career reach the levels of expertise
required to make a living. Gambling is a worse career to pursue: the chances of being successful
in games in which skill has a minimum impact (if any) on the outcomes are even slimmer than
that in the fields mentioned above. Moreover, although there are some financial costs involved in
maintaining a chess, music or sporting career, the financial costs of pursuing a gambling career
in games of chance are extremely high.
In other words, pursuing a gambling career is not a bad prospect because making a living
out of it is impossible, but because it is very improbable given the costs to maintain the gambling
career. The aim of an intervention, then, should be to target beliefs that could be changed, rather
than those that are very difficult to change. This would involve agreeing with the problem
gambler under the illusion of expertise that acquiring gambling expertise is possible, and that he
may well be (or on track to become) a gambling expert. By not disputing this belief, his/her
willingness to change other beliefs may be higher; hence, working on a realistic assessment of
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what is the probability of being successful at gambling given the financial and time costs, may be
a better strategy.
Conclusion
We proposed the concept of the illusion of expertise as one of the possible causes of
maintenance of problematic gambling behavior. We considered this concept in the context of
cognitive research on expertise and expert judgment research. We used theories of expertise to
propose an explanation of the underlying mechanisms of three phenomena in gambling: expertise
acquisition, cognitive biases, and the illusion of expertise. It is important to emphasise that we
are not proposing that every problem gambler is under the illusion of expertise. We explicitly
indicated the conditions under which the illusion of expertise may arise. Despite this proviso, we
do claim that the concept of the illusion of expertise may be useful for problem gambling
interventions. We hope that this chapter constitutes an important step towards incorporating the
knowledge acquired in the field of expertise research into problem gambling research. By doing
that, we feel this is an important contribution to the understanding of the acquisition,
development and maintenance of gambling behavior.
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i An anonymous reviewer indicated that acquiring this expertise is not possible because the
sequences of slot machines are often ten of thousands of plays, thus it would be impossible to
predict results even by systematic observation.
ii The term the “illusion of expertise” has been used by Fellner, Güth and Maciejovsky (2004) in the
context of financial decisions. They defined it as “the tendency to prefer own choices much more than
objectively justifiable…” (p. 358). We believe the phenomenon studied by Fellner and colleagues is
that of the illusion of control, rather than the illusion of expertise. The fact that people prefer their own
portfolios does not occur due to extended experience in the field or the possession of domain
knowledge that is not relevant to this situation.
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... One type of cognitive distortion identified in the gambling-type disorders is the illusion of expertise -"the belief that one possesses a higher level of specific knowledge or skill than objectively justified, in a domain in which one has prolonged experience, and possesses other knowledge of skills". 90 Compared in this way, the condition underlying problem gambling could be understood as less directly connected to the offender's choice to offend than the states of mind underlying the Verdins type of mental malfunctioning. This distinguishing feature is less tenable when it is understood the cognitive distortions of the problem gambler may be more pervasive than simply those directly related to gambling activities. ...
Article
Full-text available
In the U.K., the major commercial gambling activity in adolescents is the playing of slot machines (commonly known as “fruit machines”). Over the past few years, the negative effects of “fruit machine addiction” have been reported by various helping organizations (e.g. Gamblers Anonymous) and the national press, including allegations of attempted murder, suicide and prostitution as well as a wider incidence of petty crime. Fifty adolescent fruit machine players from a ‘user population’ participated in a face-to-face interview and questionnaire study examining factors in the acquisition, development and maintenance of gambling behaviour. Nine adolescent males were deemed to be pathological gamblers as measured by the American Psychiatric Association DSM-III-R diagnostic criteria, and a number of serious consequences were reported including gambling debts, truancy and stealing.
Book
What does a chess master think when he prepares his next move? How are his thoughts organized? Which methods and strategies does he use by solving his problem of choice? To answer these questions, the author did a study, to which famous chess masters participated (Alekhine, Max Euwe, Reuben Fine, Tartakower and Flohr). This book is still useful for everybody who studies cognition and artificial intelligence. The studies involve participants of all chess backgrounds, from amateurs to masters. They investigate the cognitive requirements and the thought processes involved in moving a chess piece. The participants were usually required to solve a given chess problem correctly under the supervision of an experimenter and represent their thought-processes vocally so that they could be recorded. De Groot found that much of what is important in choosing a move occurs during the first few seconds of exposure to a new position. Four stages in the task of choosing the next move were noted. The first stage was the 'orientation phase', in which the subject assessed the situation and determined a general idea of what to do next. The second stage, the 'exploration phase' was manifested by looking at some branches of the game tree. The third stage, or 'investigation phase' resulted in the subject choosing a probable best move. Finally, in the fourth stage, the 'proof phase', saw the subject confirming with him/herself that the results of the investigation were valid. De Groot concurred with Alfred Binet that visual memory and visual perception are important and that problem-solving ability is of paramount importance. Memory is particularly important, according to de Groot (1965), in that there are no 'new' moves in chess and so those from personal experience or from the experience of others can be committed to memory. © 1965, Mouton Publishers, The Hague, The Netherlands. All right reserved.
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The theoretical framework presented in this article explains expert performance as the end result of individuals' prolonged efforts to improve performance while negotiating motivational and external constraints. In most domains of expertise, individuals begin in their childhood a regimen of effortful activities (deliberate practice) designed to optimize improvement. Individual differences, even among elite performers, are closely related to assessed amounts of deliberate practice. Many characteristics once believed to reflect innate talent are actually the result of intense practice extended for a minimum of 10 years. Analysis of expert performance provides unique evidence on the potential and limits of extreme environmental adaptation and learning.
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We develop a multiperiod market model describing both the process by which traders learn about their ability and how a bias in this learning can create overconfident traders. A trader in our model initially does not know his own ability. He infers this ability from his successes and failures. In assessing his ability the trader takes too much credit for his successes. This leads him to become overconfident. A trader's expected level of overconfidence increases in the early stages of his career. Then, with more experience, he comes to better recognize his own ability. The patterns in trading volume, expected profits, price volatility, and expected prices resulting from this endogenous overconfidence are analyzed. Article published by Oxford University Press on behalf of the Society for Financial Studies in its journal, The Review of Financial Studies.
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A number of recent studies have shown there may be a strong cognitive bias in explaining persistent gambling. Theories that have been put forward include the illusion of control, "cognitive regret," biased evaluations and the "psychology of the near miss." Two exploratory studies examining the acquisition, development and maintenance of gambling behaviour involving adolescent fruit machine gamblers were carried out. Those factors which directly relate to the cognitive biases (notably erroneous beliefs about skill) during gambling activity are discussed with reference to the above cognitive influences.
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Domain knowledge is a powerful predictor of success in many complex tasks, but do general cognitive abilities also play a role? To investigate this question, we had 155 participants representing a wide range of poker experience and skill complete tests of poker knowledge, working memory capacity (WMC), and two components of skill in Texas Hold’Em poker: the ability to remember hands and the ability to evaluate hands. Not surprisingly, poker knowledge positively predicted performance in all of the Hold’Em tasks. However, WMC added significantly to the prediction, and there was no evidence for interactions between poker knowledge and WMC. That is, WMC was as important as a predictor of performance at high levels of poker knowledge as at low levels, suggesting that domain knowledge may not always enable circumvention of WMC in domain-relevant tasks.
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This paper develops a technique for isolating and studying the per- ceptual structures that chess players perceive. Three chess players of varying strength - from master to novice - were confronted with two tasks: ( 1) A perception task, where the player reproduces a chess position in plain view, and (2) de Groot's ( 1965) short-term recall task, where the player reproduces a chess position after viewing it for 5 sec. The successive glances at the position in the perceptual task and long pauses in tbe memory task were used to segment the structures in the reconstruction protocol. The size and nature of these structures were then analyzed as a function of chess skill. What does an experienced chess player "see" when he looks at a chess position? By analyzing an expert player's eye movements, it has been shown that, among other things, he is looking at how pieces attack and defend each other (Simon & Barenfeld, 1969). But we know from other considerations that he is seeing much more. Our work is concerned with just what ahe expert chess pIayer perceives.