Confirmation Bias: A Ubiquitous Phenomenon in Many Guises

Abstract

Confirmation bias, as the term is typically used in the psychological literature, connotes the seeking or interpreting of evidence in ways that are partial to existing beliefs, expectations, or a hypothesis in hand. The author reviews evidence of such a bias in a variety of guises and gives examples of its operation in several practical contexts. Possible explanations are considered, and the question of its utility or disutility is discussed.

Full text

Review of General Psychology
1998,
Vol. 2, No. 2, 175-220Copyright 1998 by the Educational Publishing Foundation
1089-2680«8/$3.00
Confirmation Bias: A Ubiquitous Phenomenon in Many Guises
Raymond S. Nickerson
Tufts University
Confirmation bias, as the term is typically used in the psychological literature, connotes
the seeking or interpreting of evidence in ways that are partial to existing beliefs,
expectations, or a hypothesis in hand. The author reviews evidence of such a bias in a
variety of guises and gives examples of its operation in several practical contexts.
Possible explanations are considered, and the question of its utility or disutility is
discussed.
When men wish to construct or support a theory, how
they torture facts into their service! (Mackay, 1852/
1932,
p.
552)
Confirmation bias is perhaps the best known and most
widely accepted notion of inferential error to come out
of the literature on human
reasoning.
(Evans,
1989,
p.
41)
If one were to attempt to identify a single
problematic aspect of human reasoning that
deserves attention above all others, the confirma-
tion bias would have to be among the candidates
for consideration. Many have written about this
bias,
and it appears to be sufficiently strong and
pervasive that one is led to wonder whether the
bias,
by
itself,
might account for a significant
fraction of the disputes, altercations, and misun-
derstandings that occur among individuals,
groups, and nations.
Confirmation bias has been used in the
psychological literature to refer to a variety of
phenomena. Here I take the term to represent a
generic concept that subsumes several more
specific ideas that connote the inappropriate
bolstering of hypotheses or beliefs whose truth
is in question.
Deliberate Versus Spontaneous
Case Building
There is an obvious difference between
impartially evaluating evidence in order to come
to an unbiased conclusion and building a case to
justify a conclusion already drawn. In the first
instance one seeks evidence on all sides of a
Correspondence concerning this article should be ad-
dressed to Raymond S. Nickerson, Department of Psychol-
ogy, Paige Hall, Tufts University, Medford, Massachusetts
02155.
Electronic mail may be sent to mickerson@infonet.
tufts.edu.
question, evaluates it as objectively as one can,
and draws the conclusion that the evidence, in
the aggregate, seems to dictate. In the second,
one selectively gathers, or gives undue weight
to,
evidence that supports one's position while
neglecting to gather, or discounting, evidence
that would tell against it.
There is a perhaps less obvious, but also
important, difference between building a case
consciously and deliberately and engaging in
case-building without being aware of doing so.
The first type of case-building is illustrated by
what attorneys and debaters do. An attorney's
job is to make a case for one or the other side of
a legal dispute. The prosecutor tries to marshal
evidence to support the contention that a crime
has been committed; the defense attorney tries
to present evidence that will support the
presumption that the defendant is innocent.
Neither is committed to an unbiased weighing of
all the evidence at hand, but each is motivated to
confirm a particular position. Debaters also
would be expected to give primary attention to
arguments that support the positions they are
defending; they might present counterargu-
ments, but would do so only for the purpose of
pointing out their weaknesses.
As the term is used in this article and, I
believe, generally by psychologists, confirma-
tion bias connotes a less explicit, less con-
sciously one-sided case-building process. It
refers usually to unwitting selectivity in the
acquisition and use of evidence. The line
between deliberate selectivity in the use of
evidence and unwitting molding of facts to fit
hypotheses or beliefs is a difficult one to draw in
practice, but the distinction is meaningful
conceptually, and confirmation bias has more to
do with the latter than with the former. The
175

176RAYMOND S. NICKERSON
assumption that people can and do engage in
case-building unwittingly, without intending to
treat evidence in a biased way or even being
aware of doing so, is fundamental to the
concept.
The question of what constitutes confirmation
of a hypothesis has been a controversial matter
among philosophers and logicians for a long
time (Salmon, 1973). The controversy is exem-
plified by Hempel's (1945) famous argument
that the observation of a white shoe is
confirmatory for the hypothesis "All ravens are
black," which can equally well be expressed in
contrapositive form as "All nonblack things are
nonravens." Goodman's (1966) claim that
evidence that something is green is equally good
evidence that it is "grue"—grue being defined
as green before a specified future date and blue
thereafter—also provides an example. A large
literature has grown up around these and similar
puzzles and paradoxes. Here this controversy is
largely ignored. It is sufficiently clear for the
purposes of this discussion that, as used in
everyday language, confirmation connotes evi-
dence that is perceived to support—to increase
the credibility of—a hypothesis.
I also make a distinction between what might
be called motivated and unmotivated forms of
confirmation bias. People may treat evidence in
a biased way when they are motivated by the
desire to defend beliefs that they wish to
maintain. (As already noted, this is not to
suggest intentional mistreatment of evidence;
one may be selective in seeking or interpreting
evidence that pertains to a belief without being
deliberately so, or even necessarily being aware
of the selectivity.) But people also may proceed
in a biased fashion even in the testing of
hypotheses or claims in which they have no
material stake or obvious personal interest. The
former case is easier to understand in common-
sense terms than the latter because one can
appreciate the tendency to treat evidence
selectively when a valued belief is at risk. But it
is less apparent why people should be partial in
their uses of evidence when they are indifferent
to the answer to a question in hand. An adequate
account of the confirmation bias must encom-
pass both cases because the existence of each is
well documented.
There are, of
course,
instances of one wishing
to disconfirm a particular hypothesis. If, for
example, one believes a hypothesis to be untrue,
one may seek evidence of that fact or give undue
weight to such evidence. But in such cases, the
hypothesis in question is someone else's
belief.
For the individual who seeks to disconfirm such
a hypothesis, a confirmation bias would be a
bias to confirm the individual's own
belief,
namely that the hypothesis in question is false.
A Long-Recognized Phenomenon
Motivated confirmation bias has long been
believed by philosophers to be an important
determinant of thought and behavior. Francis
Bacon (1620/1939) had this to say about it, for
example:
The human understanding when it has once adopted an
opinion (either as being the received opinion or as
being agreeable to itself) draws all things else to
support and agree with it. And though there be a greater
number and weight of instances to be found on the
other side, yet these it either neglects and despises, or
else by some distinction sets aside and rejects; in order
that by this great and pernicious predetermination the
authority of its former conclusions may remain
inviolate.. . . And such is the way of all superstitions,
whether in astrology, dreams, omens, divine judg-
ments, or the like; wherein men, having a delight in
such vanities, mark the events where they are fulfilled,
but where they fail, although this happened much
oftener, neglect and pass them
by.
(p. 36)
Bacon noted that philosophy and the sciences
do not escape this tendency.
The idea that people are prone to treat
evidence in biased ways if the issue in question
matters to them is an old one among psycholo-
gists also:
If we have nothing personally at stake in a dispute
between people who are strangers to us, we are
remarkably intelligent about weighing the evidence and
in reaching a rational conclusion. We can be convinced
in favor of either of the fighting parties on the basis of
good evidence. But let the fight be our own, or let our
own friends, relatives, fraternity brothers, be parties to
the fight, and we lose our ability to see any other side of
the issue than our own. .. . The more urgent the
impulse, or the closer it comes to the maintenance of
our own selves, the more difficult it becomes to be
rational and intelligent. (Thurstone, 1924, p. 101)
The data that I consider in what follows do
not challenge either the notion that people
generally like to avoid personally disquieting
information or the belief that the strength of a
bias in the interpretation of evidence increases
with the degree to which the evidence relates
directly to a dispute in which one has a personal

CONFIRMATION BIAS177
stake. They are difficult to reconcile, however,
with the view that evidence is treated in a totally
unbiased way if only one has no personal
interest in that to which it pertains.
The following discussion of this widely
recognized bias is organized in four major
sections. In the first, I review experimental
evidence of the operation of a confirmation bias.
In the second, I provide examples of the bias at
work in practical situations. The third section
notes possible theoretical explanations of the
bias that various researchers have proposed. The
fourth addresses the question of the effects of
the confirmation bias and whether it serves any
useful purposes.
Experimental Studies
A great deal of empirical evidence supports
the idea that the confirmation bias is extensive
and strong and that it appears in many guises.
The evidence also supports the view that once
one has taken a position on an issue, one's
primary purpose becomes that of defending or
justifying that position. This is to say that
regardless of whether one's treatment of evi-
dence was evenhanded before the stand was
taken, it can become highly biased afterward.
Hypothesis-Determined Information
Seeking and Interpretation
People tend to seek information that they
consider supportive of favored hypotheses or
existing beliefs and to interpret information in
ways that are partial to those hypotheses or
beliefs. Conversely, they tend not to seek and
perhaps even to avoid information that would be
considered counterindicative with respect to
those hypotheses or beliefs and supportive of
alternative possibilities (Koriat, Lichtenstein, &
Fischhoff,
1980).
Beyond seeking information that is support-
ive of an existing hypothesis or
belief,
it appears
that people often tend to seek only, or primarily,
information that will support that hypothesis or
belief in a particular way. This qualification is
necessary because it is generally found that
people seek a specific type of information that
they would expect to find, assuming the
hypothesis is true. Also, they sometimes appear
to give weight to information that is consistent
with a hypothesis but not diagnostic with respect
to it. These generalizations are illustrated by
several of
the
following experimental findings.
Restriction of attention to a favored hypoth-
esis.
If one entertains only a single possible
explanation of some event or phenomenon, one
precludes the possibility of interpreting data as
supportive of any alternative explanation. Even
if one recognizes the possibility of other
hypotheses or beliefs, perhaps being aware that
other people hold them, but is strongly commit-
ted to a particular position, one may fail to
consider the relevance of information to the
alternative positions and apply it (favorably)
only to one's own hypothesis or
belief.
Restricting attention to a single hypothesis
and failing to give appropriate consideration to
alternative hypotheses is, in the Bayesian
framework, tantamount to failing to take likeli-
hood ratios into account. The likelihood ratio is
the ratio of two conditional probabilities,
p(D\Hx)lp(p\Hj), and represents the probability
of a particular observation (or datum) if one
hypothesis is true relative to the probability of
that same observation if the other hypothesis is
true.
Typically there are several plausible
hypotheses to account for a specific observation,
so a given hypothesis would have several
likelihood ratios. The likelihood ratio for a
hypothesis and its complement, p{D\H)l
p{D\~H),
is of special interest, however,
because an observation gives one little evidence
about the probability of the truth of a hypothesis
unless the probability of that observation, given
that the hypothesis is true, is either substantially
larger or substantially smaller than the probabil-
ity of that observation, given that the hypothesis
is false.
The notion of diagnosticity reflects the
importance of considering the probability of an
observation conditional on hypotheses other
than the favored one. An observation is said to
be diagnostic with respect to a particular
hypothesis to the extent that it is consistent with
that hypothesis and not consistent, or not as
consistent, with competing hypotheses and in
particular with the complementary hypothesis.
One would consider an observation diagnostic
with respect to a hypothesis and its complement
to the degree that the likelihood ratio, p{D\H)l
p(D\~H),
differed from 1. An observation that
is consistent with more than one hypothesis is
said not to be diagnostic with respect to those
hypotheses; when one considers the probability

178RAYMOND S. NICKERSON
of an observation conditional on only a single
hypothesis, one has no way of determining
whether the observation is diagnostic.
Evidence suggests that people often do the
equivalent of considering only p(D\H) and
failing to take into account the ratio of this and
p(D\~H),
despite the fact that considering only
one of these probabilities does not provide a
legitimate basis for assessing the credibility of//
(Beyth-Marom &
Fischhoff,
1983; Doherty &
Mynatt, 1986; Doherty, Mynatt, Tweney, &
Schiavo, 1979; Griffin & Tversky, 1992; Kern &
Doherty, 1982; Troutman & Shanteau, 1977).
This tendency to focus exclusively on the case
in which the hypothesis is assumed to be true is
often referred to as a tendency toward pseudodi-
agnosticity (Doherty & Mynatt, 1986; Doherty
et al., 1979; Fischhoff & Beyth-Marom, 1983;
Kern & Doherty, 1982). Fischhoff and Beyth-
Marom (1983) have argued that much of what
has been interpreted as a confirmation bias can
be attributed to such a focus and the consequen-
tial failure to consider likelihood ratios.
Preferential treatment of evidence supporting
existing beliefs. Closely related to the restric-
tion of attention to a favored hypothesis is the
tendency to give greater weight to information
that is supportive of existing beliefs or opinions
than to information that runs counter to them.
This does not necessarily mean completely
ignoring the counterindicative information but
means being less receptive to it than to
supportive information—more likely, for ex-
ample, to seek to discredit it or to explain it
away.
Preferential treatment of evidence supporting
existing beliefs or opinions is seen in the
tendency of people to recall or produce reasons
supporting the side they favor—my-side
bias—on a controversial issue and not to recall
or produce reasons supporting the other side
(Baron, 1991, 1995; Perkins, Allen, & Hafner,
1983;
Perkins, Farady, & Bushey, 1991). It
could be either that how well people remember a
reason depends on whether it supports their
position, or that people hold a position because
they can think of more reasons to support it.
Participants in the study by Perkins, Farady, and
Bushey were capable of generating reasons for
holding a view counter to their own when
explicitly asked to do so; this finding led
Tishman, Jay, and Perkins (1993) to interpret the
failure to do so spontaneously as a motivational
problem as distinct from a cognitive limitation.
Baron (1995) found that, when asked
to
judge
the quality of arguments, many people were
likely to rate one-sided arguments higher than
two-sided arguments, suggesting that the bias is
at least partially due to common beliefs about
what makes an argument strong. In keeping with
this result, participants in a mock jury trial who
tended to use evidence selectively to build one
view of what happened expressed greater
confidence in their decisions than did those who
spontaneously tried to weigh both sides of the
case (D. Kuhn, Weinstock, & Flaton, 1994).
When children and young adults were given
evidence that was inconsistent with a theory
they favored, they often "either failed to
acknowledge discrepant evidence or attended to
it in a selective, distorting manner. Identical
evidence was interpreted one way in relation to a
favored theory and another way in relation to a
theory that was not favored" (D. Kuhn, 1989, p.
677).
Some of Kuhn's participants were unable
to indicate what evidence would be inconsistent
with their theories; some were able to generate
alternative theories when asked, but they did not
do so spontaneously. When they were asked to
recall their theories and the related evidence that
had been presented, participants were likely to
recall the evidence as being more consistent
with the theories than it actually was. The
greater perceived consistency was achieved
sometimes by inaccurate recall of theory and
sometimes by inaccurate recall of evidence.
Looking only or primarily for positive cases.
What is considerably more surprising than the
fact that people seek and interpret information in
ways that increase their confidence in favored
hypotheses and established beliefs is the fact
that they appear to seek confirmatory informa-
tion even for hypotheses in whose truth value
they have no vested interest. In their pioneering
concept-discovery experiments, Bruner, Good-
now, and Austin (1956) found that participants
often tested a hypothesized concept by choosing
only examples that would be classified as
instances of the sought-for concept if the
hypothesis were correct. This strategy precludes
discovery, in some cases, that an incorrect
hypothesis is incorrect. For example, suppose
the concept to be discovered is small circle and
one's hypothesis is small red
circle.
If one tests
the hypothesis by selecting only things that are

CONFIRMATION BIAS179
small, red, and circular, one will never discover
that the class denned by the concept includes
also small circular things that are yellow or blue.
Several investigators (Levine, 1970; Millward
& Spoehr, 1973; Taplin, 1975; Tweney et al.,
1980;
Wason & Johnson-Laird, 1972) subse-
quently observed the same behavior of partici-
pants testing only cases that are members of the
hypothesized category.
Some studies demonstrating selective testing
behavior of this sort involved a task invented by
Wason (1960) in which people were asked to
find the rule that was used to generate specified
triplets of numbers. The experimenter presented
a triplet, and the participant hypothesized the
rule that produced it. The participant then tested
the hypothesis by suggesting additional triplets
and being told, in each case, whether it was
consistent with the rule to be discovered. People
typically tested hypothesized rules by producing
only triplets that were consistent with them.
Because in most cases they did not generate any
test items that were inconsistent with the
hypothesized rule, they precluded themselves
from discovering that it was incorrect if the
triplets it prescribed constituted a subset of those
prescribed by the actual rule. Given the triplet
2-4-6, for example, people were likely to come
up with the hypothesis successive even numbers
and then proceed to test this hypothesis by
generating additional sets of successive even
numbers. If the 2-4-6 set had actually been
produced by the rule numbers increasing by 2,
numbers increasing in size, or any
three
positive
numbers, the strategy of using only sets of
successive even numbers would not reveal the
incorrectness of the hypothesis because every
test item would get a positive response.
The use only of test cases that will yield a
positive response if
a
hypothesis under consider-
ation is correct not only precludes discovering
the incorrectness of certain types of hypotheses
with a correct hypothesis, this strategy would
not yield as strongly confirmatory evidence,
logically, as would that of deliberately selecting
tests that would show the hypothesis to be
wrong, if it is wrong, and failing in the attempt.
To the extent that the strategy of looking only
for positive cases is motivated by a wish to find
confirmatory evidence, it is misguided. The
results this endeavor will yield will, at best, be
consistent with the hypothesis, but the confirma-
tory evidence they provide will not be as
compelling as would the failure of a rigorous
attempt at disconfirmation.
This point is worth emphasizing because the
psychological literature contains many refer-
ences to the confirmatory feedback a participant
gets when testing a hypothesis with a positive
case.
These references do not generally distin-
guish between confirmatory in a logical sense
and confirmatory in a psychological sense. The
results obtained by Wason (1960) and others
suggest that feedback that is typically inter-
preted by participants to be strongly confirma-
tory often is not logically confirmatory, or at
least not strongly so. The "confirmation" the
participant receives in this situation is, to some
degree, illusory. This same observation applies
to other studies mentioned in the remainder of
this article.
In an early commentary on the triplet-rule
task, Wetherick (1962) argued that the experi-
mental situation did not reveal the participants'
intentions in designating any particular triplet as
a test case. He noted that any test triplet could
either conform or not conform to the rule, as
defined by the experimenter, and it could also
either conform or not conform to the hypothesis
being considered by the participant. Any given
test case could relate to the rule and hypothesis
in combination in any of four ways: conform-
conform, conform-not conform, not conform-
conform, and not conform-not conform. Weth-
erick argued that one could not determine
whether an individual was intentionally attempt-
ing to eliminate a candidate hypothesis unless
one could distinguish between test cases that
were selected because they conformed to a
hypothesis under consideration and those that
were selected because they did not.
Suppose a participant selects the triplet 3-5-7
and is told that it is consistent with the rule (the
rule being any three numbers in ascending
order).
The participant might have chosen this
triplet because it conforms to the hypothesis
being considered, say numbers increasing by
two,
and might have taken the positive response
as evidence that the hypothesis is correct. On the
other hand, the participant could have selected
this triplet in order to eliminate one or more
possible hypotheses (e.g., even numbers
ascend-
ing; a
number,
twice the
number,
three times the
number).
In this case, the experimenter's
positive response would constitute the discon-

180RAYMOND S. NICKERSON
firming evidence (with respect to these hypoth-
eses) the participant sought.
Wetherick (1962) also pointed out that a test
triplet may logically rule out possible hypoth-
eses without people being aware of the fact
because they never considered those hypoth-
eses.
A positive answer to the triplet 3-5-7
logically eliminates even numbers ascending
and a
number,
twice the
number,
three times the
number, among other possibilities, regardless of
whether the participant thought of them. But of
course, only if the triplet was selected with the
intention of ruling out those options should its
selection be taken as an instance of a falsifica-
tion strategy. Wetherick's point was that without
knowing what people have in mind in making
the selections they do, one cannot tell whether
they are attempting to eliminate candidates from
further consideration or not.
Wason (1962, 1968/1977) responded to this
objection with further analyses of the data from
the original experiment and data from additional
experiments showing that although some partici-
pants gave evidence of understanding the
concept of falsification, many did not. Wason
summarized the findings from these experi-
ments this way: "there would appear to be
compelling evidence to indicate that even
intelligent individuals adhere to their own
hypotheses with remarkable tenacity when they
can produce confirming evidence for them"
(1968/1977, p. 313).
In other experiments in which participants
have been asked to determine which of several
hypotheses is the correct one to explain some
situation or event, they have tended to ask
questions for which the correct answer would be
yes if the hypothesis under consideration were
true (Mynatt, Doherty, & Tweney, 1977; Shak-
lee &
Fischhoff,
1982). These experiments are
among many that have been taken to reveal not
only a disinclination to test a hypothesis by
selecting tests that would show it to be false if it
is false, but also a preference for questions that
will yield a positive answer if the hypothesis is
true.
Others have noted the tendency to ask
questions for which the answer is yes if the
hypothesis being tested is correct in the context
of experiments on personality perception (Hod-
gins & Zuckerman, 1993; Schwartz, 1982;
Strohmer & Newman, 1983; Trope & Bassock,
1982,
1983; Trope, Bassock, & Alon, 1984;
Zuckerman, Knee, Hodgins, & Miyake, 1995).
Fischhoff and Beyth-Marom (1983) also noted
the possibility that participants in such experi-
ments tend to assume that the hypothesis they
are asked to test is true and select questions that
would be the least awkward to answer if that is
the case. For instance, participants asked
assumed extroverts (or introverts) questions that
extroverts (or introverts) would find particularly
easy to answer.
Overweighting positive confirmatory in-
stances. Studies of social judgment provide
evidence that people tend to overweight positive
confirmatory evidence or underweight negative
discomfirmatory evidence. Pyszczynski and
Greenberg (1987) interpreted such evidence as
supportive of the view that people generally
require less hypothesis-consistent evidence to
accept a hypothesis than hypothesis-inconsistent
information to reject a hypothesis. These
investigators argued, however, that this asymme-
try is modulated by such factors as the degree of
confidence one has in the hypothesis to begin
with and the importance attached to drawing a
correct conclusion. Although they saw the need
for accuracy as one important determinant of
hypothesis-evaluating behavior, they suggested
that other motivational factors, such as needs for
self-esteem, control, and cognitive consistency,
also play significant roles.
People can exploit others' tendency to over-
weight (psychologically) confirming evidence
and underweight disconfirming evidence for
many purposes. When the mind reader, for
example, describes one's character in more-or-
less universally valid terms, individuals who
want to believe that their minds are being read
will have little difficulty finding substantiating
evidence in what the mind reader says if they
focus on what fits and discount what does not
and if they fail to consider the possibility that
equally accurate descriptions can be produced if
their minds are not being read (Fischhoff &
Beyth-Marom, 1983; Forer, 1949; Hyman,
1977).
People who wish to believe in astrology
or the predictive power of psychics will have no
problem finding some predictions that have
turned out to be true, and this may suffice to
strengthen their belief if they fail to consider
either predictions that proved not to be accurate
or the possibility that people without the ability
to see the future could make predictions with
equally high (or low) hit rates. A confirmation

CONFIRMATION BIAS181
bias can work here in two ways: (a) people may
attend selectively to what is said that turns out to
be true, ignoring or discounting what turns out
to be false, and (b) they may consider only
p(D\H),
the probability that what was said
would be said if the seer could really see, and
fail to consider p(D\~H), the probability that
what was said would be said if the seer had no
special psychic powers. The tendency of gam-
blers to explain away their losses, thus permit-
ting themselves to believe that their chances of
winning are higher than they really are, also
illustrates the overweighting of supportive
evidence and the underweighting of opposing
evidence (Gilovich, 1983).
Seeing what one is looking for. People
sometimes see in data the patterns for which
they are looking, regardless of whether the
patterns are really there. An early study by
Kelley (1950) of the effect of expectations on
social perception found that students' percep-
tions of social qualities (e.g., relative sociability,
friendliness) of a guest lecturer were influenced
by what they had been led to expect from a prior
description of the individual. Forer (1949)
demonstrated the ease with which people could
be convinced that a personality sketch was an
accurate depiction of themselves and their
disinclination to consider how adequately the
sketch might describe others as well.
Several studies by Snyder and his colleagues
involving
the
judgment of personality traits lend
credence to the idea that the degree to which
what people see or remember corresponds to
what they are looking for exceeds the correspon-
dence as objectively assessed (Snyder, 1981,
1984;
Snyder & Campbell, 1980; Snyder &
Gangestad, 1981; Snyder & Swann, 1978a,
1978b). In a study representative of this body of
work, participants would be asked to assess the
personality of a person they are about to meet.
Some would be given a sketch of an extrovert
(sociable, talkative, outgoing) and asked to
determine whether the person is that type.
Others would be asked to determine whether the
person is an introvert (shy, timid, quiet).
Participants tend to ask questions that, if given
positive answers, would be seen as strongly
confirmatory and that, if given negative an-
swers,
would be weakly disconfirmatory of the
personality type for which they are primed to
look (Snyder, 1981; Snyder & Swann, 1978a).
Some of the questions that people ask in these
situations are likely to evoke similar answers
from extroverts and introverts (Swann, Giuli-
ano,
& Wegner, 1982)—answers not very
diagnostic with respect to personality type.
When this is the case, askers find it easy to see
the answers they get as supportive of the
hypothesis with which they are working, inde-
pendently of what that hypothesis is.
The interpretation of the results of these
studies is somewhat complicated by the finding
of a tendency for people to respond to questions
in a way that, in effect, acquiesces to whatever
hypothesis the interrogator is entertaining (Len-
ski & Leggett, 1960; Ray, 1983; Schuman &
Presser, 1981; Snyder, 1981; Zuckerman et al.,
1995).
For example, if the interrogator hypoth-
esizes that the interviewee is an extrovert and
asks questions that an extrovert would be
expected to answer in the affirmative, the
interviewee is more likely than not to answer in
the affirmative independently of his or her
personality type. Snyder, Tanke, and Berscheid
(1977) have reported a related phenomenon.
They found that male participants acted differ-
ently in a phone conversation toward female
participants who had been described as attrac-
tive than toward those who had been described
as unnattractive, and that their behavior evoked
more desirable responses from the "attractive"
than from the "unattractive" partners.
Such results suggest that responders may
inadvertently provide evidence for a working
hypothesis by, in effect, accepting the assump-
tion on which the questions or behavior are
based and behaving in a way that is consistent
with that assumption. Thus the observer's
expectations become self-fulfilling prophecies
in the sense suggested by Merton (1948, 1957);
the expectations are "confirmed" because the
behavior of the observed person has been
shaped by them, to some degree. Studies in
education have explored the effect of teachers'
expectations on students' performance and have
obtained similar results (Dusek, 1975; Meichen-
baum, Bowers, & Ross, 1969; Rosenthal, 1974;
Rosenthal & Jacobson, 1968; Wilkins, 1977;
Zanna, Sheras, Cooper, & Shaw, 1975).
Darley and Fazio (1980) noted the importance
of distinguishing between the case in which the
behavior of a target person has changed in
response to the perceiver's expectation-guided
actions and that in which behavior has not
changed but is interpreted to have done so in a

182RAYMOND S. NICKERSON
way that is consistent with the perceiver's
expectations. Only the former is considered an
example of a self-fulfilling prophecy. In that
case,
the change in behavior should be apparent
to an observer whose observations are not
subject to distortion by the expectations in
question. When people's actions are interpreted
in ways consistent with observers' expectations
in the absence of any interaction between
observer and observed, the self-fulfilling-
prophecy effect cannot be a factor.
Darley and Gross (1983) provided evidence
of seeing what one is looking for under the latter
conditions noted above. These authors had two
groups of people view the same videotape of a
child taking an academic test. One of the groups
had been led to believe that the child's
socioeconomic background was high and the
other had been led to believe that it was low. The
former group rated the academic abilities, as
indicated by what they could see of her
performance on the test, as above grade level,
whereas the latter group rated the same perfor-
mance as below grade level. Darley and Gross
saw this result as indicating that the participants
in their study formed a hypothesis about the
child's abilities on the basis of assumptions
about the relationship between socioeconomic
status and academic ability and then interpreted
what they saw in the videotape so as to make it
consistent with that hypothesis.
Numerous studies have reported evidence of
participants seeing or remembering behavior
that they expect. Sometimes the effects occur
under conditions in which observers interact
with the people observed and sometimes under
conditions in which they do not. "Confirmed"
expectations may be based on ethnic (Duncan,
1976),
clinical (Langer & Abelson, 1974;
Rosenhan, 1973; Swann et al., 1982), educa-
tional (Foster, Schmidt, & Sabatino, 1976;
Rosenthal & Jacobson, 1968), socioeconomic
(Rist, 1970), and lifestyle (Snyder & Uranowitz,
1978) stereotypes, among other factors. And
they can involve induced expectations regarding
oneself as well as others (Mischel, Ebbensen, &
Zeiss,
1973).
Pennebaker and Skelton (1978) have pointed
out how a confirmation bias can reinforce the
worst fears of a hypochondriac. The body more
or less continuously provides one with an
assortment of signals that, if attended to, could
be interpreted as symptoms of illness of one sort
or another. Normally people ignore these
signals. However, if one suspects that one is ill,
one is likely to begin to attend to these signals
and to notice those that are consistent with the
assumed illness. Ironically, the acquisition of
factual knowledge about diseases and their
symptoms may exacerbate the problem. Upon
learning of a specific illness and the symptoms
that signal its existence, one may look for those
symptoms in one's own body, thereby increas-
ing the chances of detecting them even if they
are not out of the normal range (Woods,
Matterson, & Silverman, 1966).
Similar observations apply to paranoia and a
variety of neurotic or psychotic states. If one
believes strongly that one is a target of other
people's ill will or aggression, one is likely to be
able to fit many otherwise unaccounted-for
incidents into this view. As Beck (1976) has
suggested, the tendency of people suffering
from mental depression to focus selectively on
information that gives further reason to be
depressed and ignore information of a more
positive nature could help perpetuate the de-
pressed state.
The results of experiments using such abstract
tasks as estimating the proportions of beads of
different colors in a bag after observing the
color(s) of one or a few beads shows that data
can be interpreted as favorable to a working
hypothesis even when the data convey no
diagnostic information. The drawing of beads of
a given color may increase one's confidence in a
hypothesis about the color distribution in the
bag even when the probability of drawing a bead
of that color is the same under the working
hypothesis and its complement (Pitz, 1969;
Troutman & Shanteau, 1977). After one has
formed a preference for one brand of a
commercial product over another, receiving
information about an additional feature that is
common to the two brands may strengthen one's
preexisting preference (Chernev, 1997). Simi-
larly, observers of a sports event may describe it
very differently depending on which team they
favor (Hastorf
&
Cantril, 1954).
It is true in science as it is elsewhere
(Mitroff,
1974) that what one sees—actually or metaphori-
cally—depends, to no small extent, on what one
looks for and what one expects. Anatomist A.
Kolliker criticized Charles Darwin for having

CONFIRMATION BIAS183
advanced the cause of teleological thinking, and
botanist Asa Gray praised Darwin for the same
reason. Meanwhile, biologist T. H. Huxley and
naturalist Ernst Haeckel praised Darwin for
thoroughly discrediting thinking of this kind
(Gigerenzer et al., 1989).
Several investigators have stressed the impor-
tance of people's expectations as sources of bias
in their judgments of covariation (Alloy &
Abramson, 1980; Alloy & Tabachnik, 1984;
Camerer, 1988; Crocker, 1981; Golding &
Rorer, 1972; Hamilton, 1979; D. Kuhn, 1989;
Nisbett & Ross, 1980). The belief that two
variables are related appears to increase the
chances that one will find evidence consistent
with the relationship and decrease the chances
of obtaining evidence that tends to disconfirm it.
Judgments of covariation tend to be more
accurate when people lack strong preconcep-
tions of
the
relationship between the variables of
interest or when the relationship is consistent
with their preconceptions than when they have
preconceptions that run counter to the relation-
ship that exists.
The perception of a correlation where none
exists is sometimes referred to as an illusory
correlation. The term also has been applied
when the variables in question are correlated but
the correlation is perceived to be higher than it
actually is Chapman and Chapman (1967a,
1967b, 1969; see also Chapman, 1967) did early
work on the phenomenon. These investigators
had participants view drawings of human
figures, each of which occurred with two
statements about the characteristics of the
person who drew it. Statements were paired with
drawings in such a way as to ensure no
relationship between drawings and personality
types,
nevertheless participants saw the relation-
ships they expected to see.
Nisbett and Ross (1980) summarized the
Chapmans' work on illusory correlation by
saying that "reported covariation was shown to
reflect true covariation far less than it reflected
theories or preconceptions of the nature of the
associations that 'ought' to exist" (p. 97).
Goldberg (1968) said that this research "illus-
trates the ease with which one can 'learn'
relationships which do not exist" (p. 493). For
present purposes, it provides another illustration
of how the confirmation bias can work: the
presumption of
a
relationship predisposes one to
find evidence of that relationship, even when
there is none to be found or, if there is evidence
to be found, to overweight it and arrive at a
conclusion that goes beyond what the evidence
justifies.
A
form of stereotyping involves believing that
specific behaviors are more common among
people who are members of particular groups
than among those who are not. There is a
perceived correlation between group member-
ship and behavior. Such perceived correlations
can be real or illusory. One possible explanation
of the perception of illusory correlations is that
unusual behavior by people in distinctive groups
is more salient and easily remembered than
similar behavior by people who are not mem-
bers of those groups (Feldman, Camburn, &
Gatti, 1986; Hamilton, Dugan, & Trolier, 1985).
Another possibility is that, once a person is
convinced that members of a specific group
behave in certain ways, he or she is more likely
to seek and find evidence to support the belief
than evidence to oppose it, somewhat indepen-
dently of the facts.
Some investigators have argued that people
typically overestimate the degree to which
behavior in different situations can be predicted
from trait variables or the degree to which an
individual's typical social behavior can be
predicted from a knowledge of that person's
behavior on a given occasion (Kunda & Nisbett,
1986).
An illusion of
consistency,
according to
this view, leads people to misjudge the extent to
which a friendly individual's behavior is consis-
tently friendly or a hostile individual's behavior
is consistently hostile (Jennings, Amabile, &
Ross,
1982; Mischel, 1968; Mischel & Peake,
1982).
It is easy to see how a pervasive
confirmation bias could be implicated in this
illusion: once one has categorized an individual
as friendly or hostile, one will be more attuned
to evidence that supports that categorization
than to evidence that undermines it.
A more subtle problem relating to categoriza-
tion involves the phenomenon of reification.
Taxonomies that are invented as conceptual
conveniences often come to be seen as represent-
ing the way the world is really structured. Given
the existence of a taxonomy, no matter how
arbitrary, there is a tendency to view the world in
terms of the categories it provides. One tends to

184RAYMOND S. NICKERSON
fit what one sees into the taxonomic bins at
hand. In accordance with the confirmation bias,
people are more likely to look for, and find,
confirmation of the adequacy of a taxonomy
than to seek and discover evidence of its
limitations.
Formal Reasoning and the Selection Task
I have already considered a task invented by
Wason and much used in rule-discovery experi-
ments that revealed a tendency for people to test
a hypothesized rule primarily by considering
instances that are consistent with it. Wason
(1966,
1968) invented another task that also has
been widely used to study formal reasoning. In a
well-known version of this task, participants see
an array of
cards
and are told that each card has a
letter on one side and a number on the other.
Each of
the
cards they see shows either a vowel,
a consonant, an even number, or an odd number,
and participants are asked to indicate which
cards one would have to turn over in order to
determine the truth or falsity of the following
statement: If a card has a vowel on one side then
it has an even number on the other side.
Suppose the array that people performing this
task see is as follows:
Given this set of cards, experimenters have
generally considered selection of those showing
A and 7 to be correct, because finding an odd
number on the other side of the A or finding a
vowel behind the 7 would reveal the statement
to be false. The cards showing B and 4 have
been considered incorrect selections, because
whatever is on their other sides is consistent
with the statement. In short, one can determine
the claim to be false by finding either the card
showing the A or the card showing the 7 to be
inconsistent with it, or one can determine the
claim to be true by finding both of these cards to
be consistent with it. Wason found that people
performing this task are most likely to select
only the card showing a vowel or the card
showing a vowel and the one showing an even
number; people seldom select either the card
showing a consonant or the one showing an odd
number. Numerous investigators have obtained
essentially the same result. Experiments with
this task and variants of it have been
reviewed many times (Cosmides, 1989; Evans,
1982;
Evans, Newstead, & Byrne, 1993; Twe-
ney & Doherty, 1983; Wason & Johnson-Laird,
1972).
The logic of Wason's selection task is that of
the conditional: if P then Q. In the case of the
above example, P is there is a vowel on one side,
and Q is there is an even number on the other.
Selecting the card showing the 7 is analogous to
checking to see if
the
not-Q case is accompanied
by
not-P,
as it must be if the conditional is true.
The basic finding of experiments with the task
lends support to the hypothesis—which is
supported also by other research (Evans, New-
stead, & Byrne, 1993; Hollis, 1970)—that
people find the modus tollens argument (not-Q,
therefore not-P) to be less natural than the
modus ponens form
(P,
therefore Q). And it is
consistent with the idea that, given the objective
of assessing the credibility of a conditional
assertion, people are more likely to look for the
presence of the consequent given the presence
of the antecedent than for the absence of the
antecedent given the absence of the consequent.
Several experiments have shown that perfor-
mance of the selection task tends to be
considerably better when the problem is couched
in familiar situational terms rather than ab-
stractly (Johnson-Laird, Legrenzi, & Legrenzi,
1972;
Wason & Shapiro, 1971), although it is by
no means always perfect in the former case
(Einhorn & Hogarth, 1978). People also gener-
ally do better when the task is couched in terms
that require deontic reasoning (deciding whether
a rule of behavior—e.g., permission, obligation,
promise—has been violated) rather than indica-
tive reasoning (determining whether a hypoth-
esis is true or false; Cheng & Holyoak, 1985;
Cosmides, 1989; Cosmides & Tooby, 1992;
Gigerenzer & Hug, 1992; Griggs & Cox, 1993;
Kroger, Cheng, & Holyoak,
1993;
Manktelow &
Over, 1990, 1991; Markovits & Savary, 1992;
Valentine, 1985; Yachanin & Tweney, 1982).
In relating confirmation bias to Wason's
selection task, it is important to make three
distinctions. The first is the distinction between
the objective of specifying which of four cards
in view must be turned over in order to
determine the truth or falsity of the assertion
with respect to those four cards and the
objective of saying which of the four types of
cards represented should be turned over in order
to determine the plausibility of the assertion

CONFIRMATION BIAS185
more generally. I believe that in most of the
earlier experiments, the first of these tasks was
the intended one, although instructions have not
always made it explicit that this was the case.
The distinction is critical because what one
should do when given the first objective is clear
and not controversial. However the answer to
what one should do when given the second
objective is considerably more complicated and
debatable.
When the task is understood in the first way,
the only correct answer is the card showing the
vowel and the one showing the odd number.
However, when one believes one is being asked
how one should go about obtaining evidence
regarding the truth or falsity of an assertion of
the form if P then Q where P and Q can be
understood to be proxies for larger sets, it is no
longer so clear that the cards showing P and ~Q
are the best choices. Depending on the specifics
of the properties represented by P and Q and
what is known or assumed about their preva-
lence in the population of interest, P may be the
only selection that is likely to be very informa-
tive,
and selection of ~Q may be essentially
pointless (Kirby, 1994b; Nickerson, 1996; Oaks-
ford & Chater, 1994; Over & Evans, 1994).
Although experimenters have often, perhaps
more often than not, intended that the selection
task be interpreted in the first of the two ways
described, the second interpretation seems to me
more representative of the kind of conditional
reasoning that people are required to do in
everyday life; it is hard to think of everyday
examples of needing to determine the truth or
falsity of a claim about four entities like the
cards in the selection task, all of which are
immediately available for inspection. Perhaps a
tendency to carry over to the task, uncritically,
an effective approach in the world of everyday
hypothesis testing that is not always effective in
the contrived world of
the
laboratory contributes
to performance on the selection task.
The second and third distinctions pertain to
instances when the task is understood to involve
only the four cards in view. They are the
distinctions that were made in the context of the
discussion of how confirmation bias relates to
"find-the-rule" tasks and other tasks involving
conditional syllogisms, namely the distinction
between evidence that is confirmatory by virtue
of the presence of two entities rather than by
their joint absence and the distinction between
logical and psychological confirmation. As
applied to the selection task, confirmation bias
has typically connoted a tendency to look for the
joint occurrence of the items specified in the
task description. In the original version of the
task, this means looking for instances of the
joint occurrence of
a
vowel and an even number,
and thus the turning over of the cards showing
A
and 4, inasmuch as these are the only cards of
the four shown that could have both of the
named properties.
Selection of evidence that can only be
confirmatory of the hypothesis under consider-
ation—or avoidance of evidence that could
possibly falsify the hypothesis—is one interpre-
tation of the confirmation bias that is not
consistent with the selection of A and 4 in
Wason's task. A is a potentially falsifying card;
if the rule that cards that have a vowel on one
side have an even number on the other is false,
turning over the card showing A could reveal the
fact. So in selecting A one is not avoiding the
possibility of falsification; one is performing an
appropriate test, even in the strictest Popperian
sense. The only way to avoid the possibility of
disconfirming the hypothesized rule in Wason's
task is to select either or both of the cards
showing B and
4,
inasmuch as nothing that is on
the other sides of these cards could be
inconsistent with it.
The fact that, when given the selection task,
people are at least as likely to select
A
as they are
to select 4 weighs against the idea that their
behavior can be attributed to a logically based
desire to seek only confirming evidence and to
avoid potentially disconfirming evidence. I say
logically based because it may be that people
select A because they are seeking confirming
evidence, even though their selection also
provides the opportunity to acquire falsifying
evidence. From a strictly logical point of view,
although selecting A is part of the correct
solution, selecting only A, or
A
and 4, not only
fails to ensure the discovery that the hypoth-
esized rule is false if it is false, it also fails to
establish its truth if it is true. The only way to
demonstrate its truth is to rule out the possibility
that it is false, and this means checking all (both)
cases (A and 7) that could possibly show it to be
false if it is.
So again, behavior that has been interpreted
as evidence of a confirmation bias is not
strongly confirmatory in a logical sense, al-

186RAYMOND S. NICKERSON
though it may well be seen (erroneously) as so
by those who display it. Inasmuch as an
observation can be confirming in a psychologi-
cal sense (i.e., interpreted as confirming evi-
dence) independently of whether it is logically
confirmatory, perhaps the confirmation bias
should be thought of as a tendency to seek
evidence that increases one's confidence in a
hypothesis regardless of whether it should. The
distinction between logical confirmation and
psychological confirmation deserves greater
emphasis than it has received.
Although researchers have interpreted the
considerable collection of results that have been
obtained from experiments with variations of
the selection task as generally reflective of a
confirmation bias, alternative hypotheses have
also been proposed. L. J. Cohen (1981) argued
that it is not necessary to suppose that people do
anything more in testing a conditional rule than
check whether the consequent holds true when-
ever the antecedent does. The fact that people
sometimes select the card representing Q (4 in
the case of the present example) as well as the
one representing P (A) is because they falsely
perceive ifP then Q to be equivalent to ifQ then
P (conversion error); and the fact that they do
not select the card representing not-Q (7 in the
present example) is attributed to a failure to
apply the law of the contrapositive.
Several investigators have argued that people
interpret the conditional relationship ifP then Q
as equivalent to the biconditional relationship if
and only if P then Q, or that they fail to
distinguish between ifP then Q and ifQ then P,
especially as the if-then construction is used in
everyday language (Chapman & Chapman,
1959;
L. J. Cohen,
1981;
Henle, 1962; Legrenzi,
1970;
Politzer, 1986; Revlis, 1975a, 1975b).
Others have assumed the operation of a
matching bias whereby people tend to focus on
(and select) cards explicitly named in the
statement of the rule to be tested (Evans, 1972;
Evans & Lynch, 1973; Hoch & Tschirgi, 1983).
Evans (1989) has suggested that people make
their selections, without thinking much about
them, on the basis of a "preconscious heuristic
judgment of relevance, probably linguistically
determined" (p. 108).
Recent theorizing about the selection task has
given rise to several new explanations of how
people interpret it and deal with it, especially as
presented in various concrete frames of refer-
ence.
An idea common to several of these
explanations is that people's performance of the
task is indicative of behavior that has proved to
be adaptively effective in analogous real-world
situations. Cosmides (1989), for example, has
argued that the typical results are consistent with
the idea that people are predisposed to look for
cheating on a social contract and are particularly
skilled at detecting it. Consequently, they do
well on selection tasks in which checking the
not-Q condition is analogous to looking for an
instance of violating a tacit social agreement,
like failing to meet an obligation. Gigerenzer
and Hug (1992) have defended a similar point of
view.
Liberman and Klar (1996) proposed an
alternative explanation of the results of research
on cheating detection. They argued that a
cheating-detection perspective is neither neces-
sary nor sufficient to yield the P and not-Q
selection; they contend that the logically correct
choice will be likely if the conditional ifP then
Q is understood to represent a deterministic (as
opposed to a probabilistic) unidirectional rela-
tionship between P and Q, if what constitutes a
violation of the rule is clear, and if it is
understood that the task is to look for such a
violation.
Other investigators have begun to view the
selection task as more a problem of data
selection and decision making than of logical
inference (Kirby, 1994a, 1994b; Manktelow &
Over, 1991, 1992). Oaksford and Chater (1994),
for example, have proposed a model of the task
according to which people should make selec-
tions so as to maximize their gain in information
regarding the tenability of the hypothesis that
the conditional ifP then Q is true relative to the
tenability that it is false. I have done an analysis
that leads to a similar conclusion, at least when
the task is perceived as that of deciding whether
the conditional is true in a general sense, as
opposed to being true of four specific cards
(Nickerson, 1996).
Wason's selection task has proved to be one
of the most fertile paradigms in experimental
psychology. It would be surprising if all the
results obtained with the many variations of the
task could be accounted for by a single simple
hypothesis. I believe that, taken together, the
results of experimentation support the hypoth-
esis that one of the several factors determining
performance on this task is a confirmation bias

CONFIRMATION BIAS187
that operates quite pervasively. This is not to
suggest that a confirmation bias explains all the
findings with this task, or even that it is the most
important factor in all cases, but only that it
exists and often plays a substantive role.
The Primacy Effect and Belief Persistence
When a person must draw a conclusion on the
basis of information acquired and integrated
over time, the information acquired early in the
process is likely to carry more weight than that
acquired later (Lingle & Ostrom, 1981; Sher-
man, Zehner, Johnson, & Hirt, 1983). This is
called the primacy effect. People often form an
opinion early in the process and then evaluate
subsequently acquired information in a way that
is partial to that opinion (N. H. Anderson &
Jacobson, 1965; Jones & Goethals, 1972;
Nisbett & Ross, 1980; Webster, 1964). Francis
Bacon (1620/1939) observed this tendency
centuries ago: "the first conclusion colors and
brings into conformity with itself all that come
after" (p. 36).
Peterson and DuCharme (1967) had people
sample a sequence of colored chips and estimate
the probability that the sequence came from an
urn with a specified distribution of colors rather
than from a second urn with a different
distribution. The sampling was arranged so that
the first 30 trials favored one urn, the second 30
favored the other, and after 60 trials the evidence
was equally strong for each possibility. Partici-
pants tended to favor the urn indicated by the
first 30 draws, which is to say that the evidence
in the first 30 draws was not countermanded by
the evidence in the second 30 even though
statistically it should have been.
Bruner and Potter (1964) showed people the
same picture on a series of slides. The first slide
was defocused so the picture was not recogniz-
able.
On successive slides the focus was made
increasingly clear. After each presentation the
participant was asked to identify what was
shown. A hypothesis formed on the basis of a
defocused picture persisted even after the
picture was in sufficiently good focus that
participants who had not looked at the poorly
focused picture were able to identify it correctly.
Jones,
Rock, Shaver, Goethals, and Ward (1968)
had participants form opinions about people's
problem-solving abilities by watching them in
action. The problem solvers were judged to be
more competent if they solved many problems
early in a problem series and few late than if
they did the reverse.
The primacy effect is closely related to (and
can perhaps be seen as a manifestation of) belief
persistence. Once a belief or opinion has been
formed, it can be very resistive to change, even
in the face of fairly compelling evidence that it
is wrong (Freedman, 1964; Hay den & Mischel,
1976;
Luchins, 1942,1957; Rhine & Severance,
1970;
Ross, 1977; Ross & Lepper, 1980; Ross,
Lepper, & Hubbard, 1975). Moreover it can bias
the evaluation and interpretation of evidence
that is subsequently acquired. People are more
likely to question information that conflicts with
preexisting beliefs than information that is
consistent with them and are more likely to see
ambiguous information to be confirming of
preexisting beliefs than disconfirming of them
(Ross
&
Anderson,
1982).
And they can be quite
facile at explaining away events that are
inconsistent with their established beliefs (Hen-
rion &
Fischhoff,
1986).
I have already discussed studies by Pitz
(1969) and Troutman and Shanteau (1977)
showing that people sometimes take norma-
tively uninformative data as supportive of a
favored hypothesis. One could interpret results
from these studies as evidence of a
belief-
preserving bias working in situations in which
the "information" in hand is not really informa-
tive.
This is in keeping with the finding that two
people with initially conflicting views can
examine the same evidence and both find
reasons for increasing the strength of their
existing opinions (Lord, Ross, & Lepper, 1979).
The demonstration by Pitz, Downing, and
Reinhold (1967) that people sometimes interpret
evidence that should count against a hypothesis
as counting in favor of it may be seen as an
extreme example of the confirmation bias
serving the interest of belief preservation.
Ross and his colleagues have also shown
experimentally that people find it extremely
easy to form beliefs about or generate explana-
tions of individuals' behavior and to persevere
in those beliefs or explanations even after
learning that the data on which the beliefs or
explanations were originally based were ficti-
tious (Ross et al., 1975; Ross, Lepper, Strack, &
Steinmetz, 1977). Ross et al. (1975), for
example, had people attempt to distinguish
between authentic and unauthentic suicide

188RAYMOND S. NICKERSON
notes.
As the participants made their choices,
they were given feedback according to a
predetermined schedule that was independent of
the choices they made, but that insured that the
feedback some participants received indicated
that they performed far above average on the
task while that which others received indicated
that they performed far below average.
Following completion of Ross et al.'s (1975)
task, researchers informed participants of the
arbitrary nature of the feedback and told them
that their rate of "success" or "failure" was
predetermined and independent of their choices.
When the participants were later asked to rate
their ability to make such
judgments,
those who
had received much positive feedback on the
experimental task rated themselves higher than
did those who had received negative feedback,
despite being told that they had been given
arbitrary information. A follow-up experiment
found similar perseverance for people who
observed others performing this task (but did not
perform it themselves) and also observed the
debriefing session.
Nisbett and Ross (1980) pointed out how a
confirmation bias could contribute to the perse-
verance of unfounded beliefs of the kind
involved in experiments like this. Receiving
feedback that supports the assumption that one
is particularly good or particularly poor at a task
may prompt one to search for additional
information to confirm that assumption. To the
extent that such a search is successful, the belief
that persists may rest not exclusively on the
fraudulent feedback but also on other evidence
that one has been able to find (selectively) in
support of it.
It is natural to associate the confirmation bias
with the perseverance of false beliefs, but in fact
the operation of the bias may be independent of
the truth or falsity of the belief involved. Not
only can it contribute to the perseverance of
unfounded beliefs, but it can help make beliefs
for which there is legitimate evidence stronger
than the evidence warrants. Probably few beliefs
of the type that matter to people are totally
unfounded in the sense that there is no
legitimate evidence that can be marshalled for
them. On the other hand, the data regarding
confirmation bias, in the aggregate, suggest that
many beliefs may be held with a strength or
degree of certainty that exceeds what the
evidence justifies.
Own-Judgment Evaluation
Many researchers have done experiments in
which people have been asked to express their
degree of confidence in judgments that they
have made. When participants have expressed
confidence as probability estimates or as ratings
that, with some plausible assumptions, can be
transformed into probability estimates, it has
been possible to compare confidence with
performance on the primary task. Thus research-
ers can determine for each confidence judgment
the percentage of the correct items on the
primary task to which that judgment was
assigned. Plots of actual percent correct against
percent correct "predicted" by the confidence
judgments are often referred to as calibration
curves; perfect calibration is represented by the
unit line, which indicates that for a given
confidence level, X, the proportion of all the
judgments with that level that were correct was X.
In general, people tend to express a higher
degree of confidence than is justified by the
accuracy of their performance on the primary
task, which is to say that calibration studies have
typically shown overconfidence to be more
common than underconfidence (Einhorn &
Hogarth, 1978;
Fischhoff,
1982; Lichtenstein &
Fischhoff,
1977; Lichtenstein,
Fischhoff,
&
Phillips, 1977; Pitz, 1974; Slovic,
Fischhoff,
&
Lichtenstein, 1977). Kahneman and Tversky
(1973) refer to the confidence that people feel
for highly fallible performance as the illusion of
validity. Being forced to evaluate one's views,
especially when that includes providing reasons
against one's position, has reduced overconfi-
dence in some instances (Fischhoff, 1977; Hoch,
1984,
1985; Koriat, Lichtenstein, &
Fischhoff,
1980;
Tetlock & Kim, 1987). But generally
overconfidence has only been reduced, not
eliminated, and providing reasons against one's
position is not something that most people do
spontaneously.
One explanation of overconfidence starts with
the assumption that people tend to be good
judges of their knowledge as it relates to
situations they are likely to encounter in
everyday life. This explanation of overconfi-
dence also notes that a minimum requirement
for observing good calibration in experimental
situations is that the questions people are to
answer and that one to be used to judge the
probability of the correctness of their answers

CONFIRMATION BIAS189
must be selected in such a way as to ensure that
valid cues in the natural environment remain
valid in the experimental situation. Juslin (1993)
has argued that certain strategies commonly
used to select items in experiments more or less
ensure that valid knowledge from the partici-
pants'
natural environment will be less valid in
the experimental situation. More specifically,
the argument is that such selection strategies
typically result in sets of items for which cues
leading to wrong answers are overrepresented
relative to their commonness in the natural
environment. Experiments showing good calibra-
tion for items selected at random from a set
assumed to be representative of the natural
environment (Gigerenzer, Hoffrage, & Kleinbolt-
ing, 1991; Juslin, 1993, 1994) support this
explanation.
I believe this argument to be a forceful one.
The evidence is fairly strong that some of the
overconfidence reported, especially in experi-
ments that require people to answer general-
knowledge questions in a forced-choice format,
is an artifact of item-selection procedures that
do not ensure that cues have the same validity in
experimental situations that they have in typical
real-life situations. Not all studies of confidence
or calibration have used general-knowledge
questions and the forced-choice format for
answers, however, and overconfidence has also
been observed in other contexts. Researchers
have shown that assessments of peoples' ability
to recognize faces, for example, correlate poorly
with performance on a face-recognition task
(Baddeley & Woodhead, 1983) and observed
that retrospective judgments of comprehension
of expository texts are higher than justified
(Glenberg, Wilkinson, & Epstein, 1982).
Experts are not immune from the illusion of
validity. Attorneys tend, in the aggregate, to
express confidence of obtaining outcomes better
than those they actually obtain (Loftus &
Wagenaar, 1988; Wagenaar & Keren, 1986).
Other professionals who have been found to be
overconfident when making judgments in their
own areas of expertise include physicians
(Lusted, 1977), psychologists (Oskamp, 1965),
and engineers (Kidd, 1970). Experts appear to
do better when there is a reliable basis for
statistical prediction, such as when predicting
bridge hands (Keren, 1987) or betting odds for
horse racing (Hausch, Ziemba, & Rubenstein,
1981).
On the other hand, despite the fact that
clinical diagnoses based on case statistics tend
to be more accurate than those based on clinical
judgments, clinicians typically have greater
confidence in their own judgments than in those
derived statistically from incidence data (Arkes,
Dawes, & Christensen, 1986; Goldberg, 1968;
Meehl, 1954, 1960; Sawyer, 1966). In contrast,
professional weather forecasters tend to be
relatively well calibrated, at least with respect to
their weather predictions (Murphy & Winkler,
1974,
1977; Winkler & Murphy, 1968); this has
been attributed to the fact that they receive
constant and immediate feedback regarding the
accuracy of their predictions, which is the kind
of information that makes learning feasible.
Griffin and Tversky (1992) have made a
distinction between strength (extremeness) of
evidence and weight (predictive validity) of
evidence. They hypothesized that people tend to
focus primarily on strength and make some
(typically insufficient) adjustments in response
to weight. This hypothesis leads to the expecta-
tion that overconfidence will be the rule
especially when strength is high and weight low,
whereas underconfidence becomes more likely
when the opposite is the case. This account is
consistent with the finding that overconfidence
is the general rule because of the assumed
greater importance attached to evidentiary
strength. The account is even more predictive of
general overconfidence if one assumes that
strong evidence is more common than weighty
evidence, as Griffin
and
Tversky use these terms.
Another account of why people tend to be
overconfident of their own knowledge is that
when one has produced a tentative answer to a
question, one's natural inclination is to search
memory for evidence to support that answer and
to fail to consider possible alternative answers
(Graesser & Hemphill, 1991; Griffin, Dunning,
& Ross, 1990; Hoch, 1985; Koriat et al., 1980;
Shaklee &
Fischhoff,
1982). This is similar to
the explanation already mentioned of why
people sometimes persevere with a belief even
after learning that the information on which the
belief was based was fictitious: after having
formed the belief they sought and found
independent data to corroborate it.
The Confirmation Bias
in Real-World Contexts
As the foregoing review shows, the confirma-
tion bias has been observed in a variety of guises

190RAYMOND S. NICKERSON
in many experimental situations. What makes it
especially important to understand is that it can
have significant consequences in many nonlabo-
ratory contexts. The point is illustrated in what
follows by a few examples.
Number Mysticism
Pythagoras discovered, by experimentation,
how the pitch of a sound emitted by a vibrating
string depends on the length of the string and
was able to state this dependency in terms of
simple numerical ratios: (a) two strings of the
same material under the same tension differ in
pitch by an octave when one of the strings is
twice as long as the other, and (b) two strings the
lengths of which are in the ratio 2 to 3 will
produce a note and its fifth, and so on.
Observation was not the new thing that
Pythagoras did in his study of harmonic
relationships; people had been observing the
heavens and recording what they saw for a long
time.
What he did that was new was manipulate
what he was observing and take notice of the
effects of those manipulations. He has been
called the first experimentalist. Ironically, in-
stead of establishing experimentation as an
especially fruitful way to investigate the proper-
ties of the physical world, Pythagoras's discov-
ery helped to usher in what Bell called "the
golden age of number mysticism" and to delay
the acceptance of experimentation as the pri-
mary method of science for 2000 years (Bell,
1946/1991). Pythagoras's intellectual heirs were
so convinced of the validity of his pronounce-
ment, "everything is number," that many of the
most able thinkers over the next 2 millenia
devoted much of their cognitive energy to the
pursuit of numerology and the confirmation of
its basic assumptions. It took a Galileo to kindle
an interest in experimentation that would not
again sputter and die.
Work done as recently as the mid-19th
century involving the great pyramid of Egypt,
which has extraordinary fascination for modern
observers of artifacts of ancient cultures, illus-
trates the relevance of the confirmation bias to
Pythagorean numerological pursuits. Much of
this fascination is due to certain mathematical
relationships discussed first by John Taylor
(1859) and shortly later by Charles Smyth
(1864/1890). Taylor noted, among other facts,
that the ratio of twice the pyramid's base to its
height was roughly the same as the ratio of the
diameter of a circle to its circumference, which
is to say, IT. Smyth was inspired by Taylor's
observations and set himself the task of
discovering other mathematical relationships of
interest that the monument might hide.
Smyth discovered that the ratio of the
pyramid's base to the width of a casing stone
was 365, the number of days in a year, and that
the pyramid's height multiplied by 109 was
approximately equal to the distance from the
earth to the sun. By comparing pyramid length
measurements in various ways, he was able to
find numbers that correspond to many quantita-
tive properties of the world that were presum-
ably unknown when the pyramid was built.
These include the earth's mean density, the
period of precession of the earth's axis, and the
mean temperature of the earth's surface. Von
Daniken (1969) used the existence of such
relationships as the basis for arguing that the
earth had been visited by intelligent extraterres-
trials in the past.
Gardner (1957) referred to Smyth's book as a
classic of its kind illustrating beautifully "the
ease with which an intelligent man, passionately
convinced of a theory, can manipulate his
subject matter in such a way as to make it
conform to precisely held opinions" (p. 176). He
pointed out that a complicated structure like the
pyramid provides one with a great assortment of
possible length measurements, and that anyone
with the patience to juggle them is quite sure to
find a variety of numbers that will coincide with
some dates or figures that are of interest for
historical or scientific reasons. One simply
makes an enormous number of observations,
tries every manipulation on measurements and
measurement relationships that one can imag-
ine,
and then selects from the results those few
that coincide with numbers of interest in other
contexts. He wrote, "Since you are bound by no
rules,
it would be odd indeed if this search for
Pyramid 'Truths' failed to meet with consider-
able success" (p. 177). The search for pyramid
truths is a striking illustration of how a bias to
confirm is expressed by selectivity in the search
for and interpretation of information.
Witch
Hunting
From a modern vantage point, the convictions
and executions of tens of thousands of individu-

CONFIRMATION BIAS191
als for practicing witchcraft during the 15th,
16th, and 17th centuries in Western Europe and
to a lesser extent in 18th-century New England,
is a particularly horrific case of the confirmation
bias functioning in an extreme way at the
societal level. From the perspective of many,
perhaps most, of
the
people of
the
time, belief
in
witchcraft was perfectly natural and sorcery was
widely viewed as the reason for ills and troubles
that could not otherwise be explained. Execution-
ers meted out punishment for practising witch-
craft—generally the stake or the scaffold—with
appalling regularity. Mackay (1852/1932) put
the number executed in England alone, during
the first 80 years of the 17th century, at 40,000.
People believed so strongly in witchcraft that
some courts had special rules of evidence to
apply only in cases involving it. Mackay
(1852/1932) quoted Bodinus, a 17th-century
French authority, as follows:
The trial of this offense must not be conducted like
other crimes. Whoever adheres to the ordinary course
of justice perverts the spirit of the law, both divine and
human. He who is accused of sorcery should never be
acquitted, unless the malice of
the
prosecutor be clearer
than the sun; for it is so difficult to bring full proof of
this secret crime, that out of a million witches not one
would be convicted if the usual course were followed!
(p.
528)
Torture was an accepted and widely practiced
means of exacting confessions from accused
persons. Failure to denounce a witch was in
some places a punishable offense.
It is hard for those who live in a society that
recognizes the principle that a person accused of
a crime is to be presumed innocent until proven
guilty beyond a reasonable doubt to imagine
what it must have been like to live at a time
when—at least with respect to the accusation of
witchcraft—just the opposite principle held. On
the other hand, it is perhaps too easy to assume
that nothing like the witchcraft mania could
occur in our enlightened age. A moment's
reflection on the instances of genocide or
attempted genocide that have occurred in recent
times should make people wary of any such
assumption. These too can be seen as instances
of what can happen when special rules of
evidence are used to protect and support beliefs
that individuals, groups or nations want, for
whatever reasons, very much to hold. Awareness
of a prevalent bias toward confirmation even
under relatively ideal conditions of evidence
evaluation should make people doubly cautious
about the potential for disaster when circum-
stances encourage the bias to be carried to
excess.
Policy Rationalization
Tuchman (1984) described
a
form of confirma-
tion bias at work in the process of justifying
policies to which a government has committed
itself:
"Once a policy has been adopted and
implemented, all subsequent activity becomes
an effort to justify it" (p. 245). In the context of
a
discussion of the policy that drew the United
States into war in Vietnam and kept the U.S.
military engaged for 16 years despite countless
evidences that it was a lost cause from the
beginning, Tuchman argued that once a policy
has been adopted and implemented by a
government, all subsequent activity of that
government becomes focused on justification of
that policy:
Wooden headedness, the source of self deception is a
factor that plays a remarkably large role in government.
It consists in assessing a situation in terms of
preconceived fixed notions while ignoring or rejecting
any contrary signs. It is acting according to wish while
not allowing oneself to be deflected by the facts. It is
epitomized in a historian's statement about Philip II of
Spain, the surpassing wooden head of all sovereigns:
"no experience of the failure of his policy could shake
his belief in its essential excellence." (p. 7)
Folly, she argued, is a form of self-deception
characterized by "insistence on a rooted notion
regardless of contrary evidence" (p. 209).
At the beginning of this article, I gave
examples of bias in the use of information that
would not be considered illustrative of the
confirmation bias, as that term is used here.
These examples involved intentional selectivity
in the use of information for the conscious
purpose of supporting a position. Another
example is that of politicians taking note of facts
that are consistent with positions they have
taken while intentionally ignoring those that are
inconsistent with them. This is not to suggest,
however, that all selective use of information in
the political arena is knowing and deliberate and
that confirmation bias, in the sense of unwitting
selectivity, is not seen here. To the contrary, I
suspect that this type of bias is especially
prevalent in situations that are inherently
complex and ambiguous, which many political

192RAYMOND S. NICKERSON
situations are. In situations characterized by
interactions among numerous variables and in
which the cause-effect relationships are ob-
scure, data tend to be open to many interpreta-
tions.
When that is the case, the confirmation
bias can have a great effect, and people should
not be surprised to see knowledgeable, well-
intentioned people draw support for diametri-
cally opposed views from the same set of data.
Medicine
The importance of testing theories, hypoth-
eses,
speculations, or conjectures about the
world and the way it works, by understanding
their implications vis-a-vis observable phenom-
ena and then making the observations necessary
to check out those implications, was a common
theme in the writings of the individuals who
gave science its direction in the 16th, 17th, and
18th centuries. This spirit of empirical criticism
had not dominated thinking in the preceding
centuries but was a new attitude. Theretofore
observation, and especially controlled experi-
mentation, had played second fiddle to logic and
tradition.
Consider, for example, the stagnated status of
medical knowledge: "For 1500 years the main
source of European physicians' knowledge
about the human body was not the body itself
... [but] the works of an ancient Greek
physician [Galen]. 'Knowledge' was the barrier
to knowledge. The classic source became a
revered obstacle." Boorstin (1985, p. 344), who
wrote these words, noted the irony of the fact
that Galen himself was an experimentalist and
urged others who wished to understand anatomy
or medicine to become hands-on investigators
and not to rely only on reading what others had
said. But Galen's readers found it easier to rely
on the knowledge he passed on to them than to
follow his advice regarding how to extend it.
Although some physicians did "experiment"
with various approaches to the treatment of
different diseases and ailments, as Thomas
(1979) pointed out, until quite recently, this
experimentation left something to be desired as
a scientific enterprise:
Virtually anything that could be thought up for the
treatment of disease was tried out at one time or
another, and, once tried, lasted decades or even
centuries before being given up. It was, in retrospect,
the most frivolous and irresponsible kind of human
experimentation, based on nothing but trial and error,
and usually resulting in precisely that sequence.
Bleeding, purging, cupping, the administration of
infusions of every known plant, solutions of every
known metal, every conceivable diet including total
fasting, most of these based on the weirdest imaginings
about the cause of disease, concocted out of nothing but
thin air—this was the heritage of medicine up until a
little over a century ago. It is astounding that the
profession survived so long, and got away with so
much with so little outcry. Almost everyone seems to
have been taken in. (p. 159)
How is it that ineffective measures could be
continued for decades or centuries without their
ineffectiveness being discovered? Sometimes
people got better when they were treated;
sometimes they did
not.
And sometimes they got
better when they were not treated at all. It
appears that people's beliefs about the efficacy
of specific treatments were influenced more
strongly by those instances in which treatment
was followed by recovery than in either those in
which it was not or those in which it occurred
spontaneously. A prevailing tendency to focus
exclusively or primarily on positive cases—
cases in which treatment was followed by
recovery—would go a long way toward account-
ing for the fact that the discoveries that certain
diseases have a natural history and people often
recover from them with or without treatment
was not made until the 19th century.
Fortunately such a tendency is no longer
characteristic of medical science as a whole; but
one would be hard pressed to argue that it no
longer influences the beliefs of many people
about the efficacy of various treatments of
medical problems. Every practitioner of a form
of pseudomedicine can point to a cadre of
patients who will testify, in all sincerity, to
having benefited from the treatment. More
generally, people engage in specific behaviors
(take a pill, rest, exercise, think positively) for
the express purpose of bringing about a specific
health-related result. If
the
desired result occurs,
the natural tendency seems to be to attribute it to
what was done for the purpose of causing it;
considering seriously the possibility that the
result might have been obtained in the absence
of the associated "cause" appears not to come
naturally to us but to have to be learned.
Medical diagnosis, as practiced today, has
been the subject of some research. In looking for
causes of
illness,
diagnosticians tend to generate
one or a small set of hypotheses very early in the

CONFIRMATION BIAS193
diagnostic session (Elstein, Shulman, & Sprafka,
1978).
The guidance that a hypothesis in hand
represents for further information gathering can
function as a constraint, decreasing the likeli-
hood that one will consider an alternative
hypothesis if the one in hand is not correct.
Failure to generate a correct hypothesis has been
a common cause of faulty diagnosis in some
studies (Barrows, Feightner, Neufeld, & Nor-
man, 1978; Barrows, Norman, Neufeld, &
Feightner, 1977). A hypothesis in hand also can
bias the interpretation of subsequently acquired
data, either because one selectively looks for
data that are supportive of the hypothesis and
neglects to look for disconfirmatory data (Bar-
rows et al., 1977) or because one interprets data
to be confirmatory that really are not (Elstein et
al.,
1978).
Studies of physicians' estimates of the prob-
ability of specific diagnoses have often shown
estimates to be too high (Christensen-Szalanski
& Bushyhead, 1981/1988; DeSmet, Fryback, &
Thornbury, 1979). Christensen-Szalanski and
Bushyhead (1981/1988) had physicians judge,
on the basis of a medical history and physical
examination, the probability that patients at a
walk-in clinic had pneumonia. Only about 20
percent of the patients who were judged to have
pneumonia with a probability between .8 and .9
actually had pneumonia, as determined by chest
X rays evaluated by radiologists. These investi-
gators also got physicians to rate the various
possible outcomes from such a diagnosis and
found no difference between the values assigned
to the two possible correct diagnoses and no
difference between the values assigned to the
possible incorrect ones. This suggests that the
overly high estimates of probability of disease
were not simply the result of
a
strong preference
of false positive over false negative results.
Results from other studies suggest that
physicians do not do very well at revising
existing probability estimates to take into
account the results of diagnostic tests (Berwick,
Fineberg, & Weinstein, 1981; Cassells, Schoen-
berger, & Grayboys, 1978). A diagnostic finding
that fails to confirm a favored hypothesis may be
discounted on the grounds that, inasmuch as
there is only a probabilistic relationship between
symptoms and diseases, a perfect match is not to
be expected (Elstein & Bordage, 1979).
Judicial Reasoning
In the context of judicial proceedings, an
attempt is made to decouple the process of
acquiring information from that of drawing
conclusions from that information. Jurors are
admonished to maintain open minds during the
part of a trial when evidence is being presented
(before
the
jury-deliberation
phase);
they are not
supposed to form opinions regarding what the
verdict should be until all the evidence has been
presented and they have been instructed by the
judge as to their decision task. During the
jury-deliberation phase, the jury's task is to
review and consider, collectively, the evidence
that has been presented and to arrive, through
discussion and debate, at a consensus on the
verdict. They are to be careful to omit from
consideration any evidence that came to light
during the trial that was deemed inadmissible
and ordered stricken from the record.
The admonition to maintain an open mind
during the evidence-presentation phase of a trial
seems designed to counter the tendency to form
an opinion early in an evidence-evaluation
process and then to evaluate further evidence
with a bias that favors that initial opinion.
Whether jurors are able to follow this admoni-
tion and to delay forming an opinion as to the
truth or falsity of the allegations against the
accused until the jury-deliberation phase is a
matter of some doubt. It is at least a plausible
possibility that individual jurors (and judges)
develop their personal mental models of "what
really happened" as a case develops and
continuously refine and elaborate those models
as evidence continues to be presented (Holstein,
1985).
To the extent that this is the way jurors
actually think, a model, as it exists at any point
in time, may strongly influence how new
information is interpreted. If one has come to
believe that a defendant is guilty (or innocent),
further evidence that is open to various interpre-
tations may be seen as supportive of that
belief.
Opinions formed about a defendant on the basis
of superficial cues (such as demeanor while
giving testimony) can bias the interpretation of
inherently ambiguous evidence (Hendry &
Shaffer, 1989).
Results of mock-trial experiments indicate
that, although there are considerable individual
differences among mock jurors with respect to

194RAYMOND S. NICKERSON
how they approach their task (D. Kuhn et al.,
1994),
jurors often come to favor a particular
verdict early in the trial process (Devine &
Ostrom, 1985). The final verdicts that juries
return are usually the same as the tentative ones
they initially form (Kalven & Zeisel, 1966;
Lawson, 1968). The results of some mock trials
suggest that deliberation following the presenta-
tion of evidence tends to have the effect of
making
a
jury's average predeliberation opinion
more extreme in the same direction (Myers &
Lamm, 1976).
The tendency to stick with initial tentative
verdicts could exist because in most cases the
initial conclusions stand up to further objective
evaluation; there is also the possibility, however,
that the tentative verdict influences jurors'
subsequent thinking and biases them to look for,
or give undo weight
to,
evidence that supports it.
This possibility gains credence from the finding
by Pennington and Hastie (1993) that partici-
pants in mock-jury trials were more likely to
remember statements consistent with their
chosen verdict as having been presented as trial
evidence than statements that were inconsistent
with this verdict. This was true both of
statements that had been presented (hits) and of
those that had not (false positives).
Science
Polya (1954a) has argued that a tendency to
resist the confirmation bias is one of the ways in
which scientific thinking differs from everyday
thinking:
The mental procedures of the trained naturalist are not
essentially different from those of the common man,
but they are more thorough. Both the common man and
the scientist are led to conjectures by a few observa-
tions and they are both paying attention to later cases
which could be in agreement or not with the conjecture.
A case in agreement makes the conjecture more likely,
a conflicting case disproves it, and here the difference
begins: Ordinary people are usually more apt to look
for the first kind of
cases,
but the scientist looks for the
second kind. (p. 40)
If seeking data that would disconfirm a
hypothesis that one holds is the general rule
among scientists, the history of science gives us
many exceptions to the rule (Mahoney, 1976,
1977;
Mitroff,
1974). Michael Faraday was
likely to seek confirming evidence for a
hypothesis and ignore such disconfirming evi-
dence as he obtained until the phenomenon
under study was reasonably well understood, at
which time he would begin to pay more
attention to disconfirming evidence and actively
seek to account for it (Tweney & Doherty,
1983).
Louis Pasteur refused to accept or
publish results of
his
experiments that seemed to
tell against his position that life did not generate
spontaneously, being sufficiently convinced of
his hypothesis to consider any experiment that
produced counterindicative evidence to be
necessarily flawed (Farley & Geison, 1974).
When Robert Millikan published the experimen-
tal work on determining the electric charge of a
single electron, for which he won the Nobel
prize in physics, he reported only slightly more
than half
(58)
of his (107) observations, omitting
from publication those that did not fit his
hypothesis (Henrion &
Fischhoff,
1986).
It is not so much the critical attitude that
individual scientists have taken with respect to
their own ideas that has given science the
success it has enjoyed as a method for making
new discoveries, but more the fact that indi-
vidual scientists have been highly motivated to
demonstrate that hypotheses that are held by
some other scientist(s) are false. The insistence
of science, as an institution, on the objective
testability of hypotheses by publicly scrutable
methods has ensured its relative independence
from the biases of
its
practitioners.
Conservatism among scientists. The fact
that scientific discoveries have often met
resistance from economic, technological, reli-
gious,
and ideological elements outside science
has been highly publicized. That such discover-
ies have sometimes met even greater resistance
from scientists, and especially from those whose
theoretical positions were challenged or invali-
dated by those discoveries, is no less a fact if
less well known (Barber,
1961;
Mahoney, 1976,
1977).
Galileo, for example, would not accept
Kepler's hypothesis that the moon is responsible
for the tidal motions of the earth's oceans.
Newton refused to believe that the earth could
be much older than 6,000 years on the strength
of the reasoning that led Archbishop Usher to
place the date of creation at 4,004 BC. Huygens
and Leibniz rejected Newton's concept of
universal gravity because they could not accept
the idea of a force extending throughout space
not reducible to matter and motion.
Humphrey Davy dismissed John Dalton's
ideas about the atomic structure of matter as

CONFIRMATION BIAS195
more ingenious than important. William Thom-
son (Lord) Kelvin, who died in 1907, some
years after the revolutionary work of Joseph
Thomson on the electron, never accepted the
idea that the atom was decomposable into
simpler components. Lev Landau was willing in
1932 to dismiss the laws of quantum mechanics
on the grounds that they led to such a ridiculous
prediction as the contraction of large burned out
stars to essentially a point. Arthur Eddington
rejected Subrahmanyan Chandrasekhar's predic-
tion in the early 1930s that cold stars with a
mass of more than about one half that of the sun
would collapse to a point. Chandrasekhar was
sufficiently discouraged by Eddington's reaction
to leave off for the better part of
his
professional
career the line of thinking that eventually led to
the now widely accepted theory of black holes.
Theory persistence. The history of science
contains many examples of individual scientists
tenaciously holding on to favored theories long
after the evidence against them had become
sufficiently strong to persuade others without
the same vested interests to discard them. I. B.
Cohen (1985) has documented many of these
struggles in his account of
the
role of revolution
in science. All of them can be seen as examples
of the confirmation bias manifesting itself as an
unwillingness to give the deserved weight to
evidence that tells against a favored view.
Roszak (1986) described the tenacity with
which adherents to the cosmology of Ptolemy
clung to their view in the face of mounting
evidence of
its
untenability in this way:
The Ptolemaic cosmology that prevailed in ancient
times and during the Middle Ages had been compro-
mised by countless contradictory observations over
many generations. Still, it was an internally coherent,
intellectually pleasing idea; therefore, keen minds
stood by the familiar old system. Where there seemed
to be any conflict, they simply adjusted and elaborated
the idea, or restructured the observations in order to
make them fit. If observations could not be made to fit,
they might be allowed to stand along the cultural
sidelines as curiosities, exceptions, freaks of nature. It
was not until a highly imaginative constellation of ideas
about celestial and terrestrial dynamics, replete with
new concepts of gravitation, inertia, momentum, and
matter, was created that the old system was retired,
(p.
91)
Roszak pointed out also that scientists through-
out the 18th and 19th centuries retained other
inherited ideas in the fields of chemistry,
geology, and biology in adjusted forms, despite
increasing evidences of their inadequacies.
Science has held, often for very long times,
some beliefs and theories that could have been
invalidated if a serious effort had been made to
show them to be false. The belief that heavier
bodies fall faster than lighter ones, for example,
prevailed from the time of Aristotle until that of
Galileo. The experiments that Galileo per-
formed to demonstrate that this belief was false
could have been done at any time during that
2000-year period. This is a particularly interest-
ing example of a persisting false belief because
it might have been questioned strictly on the
basis of reasoning, apart from any observations.
Galileo posed a question that could have been
asked by Aristotle or by anybody who believed
that heavier bodies fall faster than lighter ones:
If a 10 pound weight falls faster than a 1 pound
weight, what will happen when the two are tied
together? Will the 11 pound combination fall
faster than the 10 pound weight, or will it fall
more slowly because the 1 pound weight will
hold back the 10 pound one?
Hawking (1988) argued that the fact that the
universe is expanding could have been predicted
from Newton's theory of gravity at any time
after the late 17th century, and noted that
Newton himself realized that the idea of
universal gravity begged an explanation as to
why the stars did not draw together. The
assumption that the universe was static was a
strong and persistent one, however. Newton
dealt with the problem by assuming the universe
was infinite and consequently had no center onto
which it could collapse. Others introduced a
notion that at very great distances gravity
became repulsive instead of attractive. Einstein,
in order to make his general theory of relativity
compatible with the idea of a static universe,
incorporated a "cosmological constant" in the
theory which, in effect, nullified the otherwise
expected contraction. Einstein later was embar-
rassed by this invention and saw it as his greatest
mistake.
None of this is to suggest that scientists
accept evidences of the inadequacy of an
established theory with equanimity. Rather, I
note that the typical reaction to the receipt of
such evidences is not immediately to discard the
theory to which the inadequacies relate but to
find a way to defend it. The bias is definitely in
the direction of giving the existing theory the

196RAYMOND S. NICKERSON
benefit of the doubt, so long as there is room for
doubt and, in some cases, even when there is
not. The usual strategy for dealing with
anomalous data is first to challenge the data
themselves. If they prove to be reliable, the next
step is to complicate the existing theory just
enough to accommodate the anomalous result
to,
as T. S. Kuhn (1970) put it, "devise
numerous articulations and ad hoc modifica-
tions of [the] theory in order to eliminate any
apparent conflict" (p. 78). If that proves to be
too difficult, one may decide simply to live with
the anomaly, at least for a while. When a theory
is confronted with too many anomalies to be
accommodated in this way—or when, as a
consequence of a series of modifications the
theory becomes too convoluted to manage and
an alternative theory becomes available—there
is the basis of a paradigm shift and a
revolutionary reorientation of thinking.
Overconfidence. Overconfidence in experi-
mental results has manifested itself in the
reporting of a higher-than-warranted degree of
certainty or precision in variable measurements.
Scientific investigators often have underesti-
mated the uncertainty of their measurements and
thus reported errors of estimate that have not
stood the test of time. Fundamental constants
that have been reported with uncertainty esti-
mates that later proved too small include the
velocity of light, the gravitational constant, and
the magnetic moment of the proton (Henrion &
Fischhoff,
1986).
The 1919 British expedition to West Africa to
take advantage of a solar eclipse in order to test
Einstein's prediction that the path of light would
be bent by a gravitational field represents an
especially noteworthy case of the reporting of a
higher-than-warranted degree of precision in
measurement. Einstein had made the prediction
in the 1915 paper on the general theory of
relativity. Scientists later discovered that the
error of measurement was as great as the effect
that was being measured so that, as Hawking
(1988) put it, "The British team's measurement
had been sheer luck, or a case of knowing the
result they wanted to get, not an uncommon
occurrence in science" (p. 32).
The predictions have subsequently been
verified with observations not subject to the
same measurement problems, but as first made
and reported, they suggest the operation a
confirmation bias of considerable strength. In a
detailed account of the event, Collins and Pinch
(1993) noted that Eddington's data were noisy,
that he had to decide which photographs to
count and which to ignore, and that he used
Einstein's theory to make these decisions. As
they put it:
Eddington could only claim to have confirmed Einstein
because he used Einstein's derivations in deciding what
his observations really were, while Einstein's deriva-
tions only became accepted because Eddington's
observation seemed to confirm them. Observation and
prediction were linked in a circle of mutual confirma-
tion rather than being independent of each other as we
would expect according to the conventional idea of an
experimental test. (p. 45)
Collins and Pinch's account of the reporting
of the results of the 1919 expedition and of the
subsequent widespread adoption of relativity as
the new standard paradigm of physics represents
scientific advance as somewhat less inexorably
determined by the cold objective assessment of
theory in the light of observational fact than it is
sometimes assumed to be.
Henrion and Fischhoff (1986) suggested that
the overconfidence associated with the estimates
they considered could have resulted from
scientists overlooking, for one reason or an-
other, specific sources of uncertainty in their
measurements. This possibility is consistent
with the results of laboratory studies of judg-
ment showing that people typically find it easier
to think of reasons that support a conclusion
they have drawn than to think of reasons that
contradict it and that people generally have
difficulty in thinking of reasons why their best
guess might be wrong (Koriat et al., 1980).
By way of rounding out this discussion of
confirmation bias in science, it is worth noting
that prevailing attitudes and opinions can
change rapidly within scientific communities, as
they can in other communities. Today's revolu-
tionary idea is tomorrow's orthodoxy. Ideas
considered daring, if not bizarre or downright
ridiculous when first put forward, can become
accepted doctrine or sometimes obvious truths
that no reasonable person would contest in
relatively short periods of time. According to
Lakatos (1976)
Newton's mechanics and theory of gravitation was put
forward as a daring guess which was ridiculed and
called "occult" by Leibniz and suspected even by
Newton
himself.
But a few decades later—in absence
of refutations—his axioms came to be taken as
indubitably true. Suspicions were forgotten, critics

CONFIRMATION BIAS197
branded "eccentric" if not "obscurantist"; some of his
most doubtful assumptions came to be regarded as so
trivial that textbooks never even stated them. (p. 49,
Footnote 1)
One can see a confirmation bias both in the
difficulty with which new ideas break through
opposing established points of view and in the
uncritical allegiance they are often given once
they have become part of the established view
themselves.
Explanations of the Confirmation Bias
How is one to account for the confirmation
bias and its prevalence in so many guises? Is it a
matter of protecting one's ego, a simple
reluctance to consider the possibility that a
belief one holds or a hypothesis that one is
entertaining is wrong? Is it a consequence of
specific cognitive limitations? Does it reflect a
lack of understanding of logic? Does it persist
because it has some functional value? That is,
does it provide some benefits that are as
important as, or in some situations more
important than, an attempt to determine the truth
in an unbiased way would be?
The Desire to Believe
Philosophers and psychologists alike have
observed that people find it easier to believe
propositions they would like to be true than
propositions they would prefer to be false. This
tendency has been seen as one manifestation of
what has been dubbed the Pollyanna principle
(Matlin & Stang, 1978), according to which
people are likely to give preferential treatment
to pleasant thoughts and memories over unpleas-
ant ones.
Finding a positive correlation between the
probability that one will believe a proposition to
be true and the probability that one will consider
it to be desirable (Lefford, 1946; McGuire,
1960;
Weinstein, 1980, 1989) does not, in
itself,
establish a causal link between desirability and
perceived truth. The correlation could reflect a
relationship between truth and desirability in the
real world, whereby what is likely to be true is
likely also to be desirable, and the same is
conversely true. On the other hand, the evidence
is strong that the correlation is the result, at least
to some degree, of beliefs being influenced by
preferences. The continuing susceptibility of
people to too-good-to-be-true promises of quick
wealth is but one illustration of the fact that
people sometimes demand very little in the way
of compelling evidence to drive them to a
conclusion that they would like to accept.
Although beliefs can be influenced by prefer-
ences,
there is a limit to how much influence
people's preferences can have. It is not the case,
for most of
us
at least, that we are free to believe
anything we want; what we believe must appear
to us believable. We can be selective with
respect to the evidence we seek, and we can tilt
the scales when we weigh what we find, but we
cannot completely ignore counterindicative evi-
dence of which we are aware. Kunda (1990) has
made this argument persuasively. The very fact
that we sometimes seek to ignore or discount
evidence that counts against what we would like
to believe bears witness to the importance we
attach to holding beliefs that are justified.
More generally, one could view, somewhat
ironically perhaps, the tendency to treat data
selectively and partially as a testament to the
high value people attach to consistency. If
consistency between beliefs and evidence were
of no importance, people would have no reason
to guard beliefs against data that are inconsistent
with them. Consistency is usually taken to be an
important requirement of rationality, possibly
the most important such requirement. Paradoxi-
cally, it seems that the desire to be consistent can
be so strong as to make it difficult for one to
evaluate new evidence pertaining to a stated
position in an objective way.
The quote from Mackay (1852/1932) that is
used as an epigraph at the beginning of this
article stresses the importance of motivation in
efforts to confirm favored views. Some investi-
gators have argued, however, that the basic
problem is not motivational but reflects limita-
tions of
a
cognitive nature. For example, Nisbett
and Ross (1980) held that, on the whole,
investigators have been too quick to attribute the
behavior of participants in experimental situa-
tions to motivational biases when there were
equally plausible alternative interpretations of
the findings:
One wonders how strongly the theory of self-serving
bias must have been held to prompt such uncritical
acceptance of empirical evidence. ... We doubt that
careful investigation will reveal ego-enhancing or
ego-defensive biases in attribution to be as pervasive or

198RAYMOND S. NICKERSON
potent as many lay people and most motivational
theorists presume them to be. (p. 233)
This argument is especially interesting in the
present context, because it invokes a form of
confirmation bias to account for the tendency of
some investigators to attribute certain behaviors
to motivational causes and to ignore what, in
Nisbett and Ross's view, are equally likely
alternative explanations.
The role of motivation in reasoning has been
a subject of debate for some time. Kunda (1990)
noted that many of the phenomena that once
were attributed to motivational variables have
been reinterpreted more recently in cognitive
terms;
according to this interpretation, conclu-
sions that appear to be drawn only because
people want to draw them may be drawn
because they are more consistent with prior
beliefs and expectancies. She noted too that
some theorists have come to believe that
motivational effects are mediated by cognitive
processes. According to this view, "[p]eople
rely on cognitive processes and representations
to arrive at their desired conclusions, but
motivation plays a role in determining which of
these will be used on a given occasion" (Kunda,
1990,
p.
480).
Kunda defended this view, arguing that the
evidence to date is consistent with the assump-
tion that motivation affects reasoning, but it
does so through cognitive strategies for access-
ing, constructing, and evaluating beliefs:
Although cognitive processes cannot fully account for
the existence of self-serving biases, it appears that they
play a major role in producing these biases in that they
provide the mechanisms through which motivation
affects reasoning. Indeed, it is possible that motivation
merely provides an initial trigger for the operation of
cognitive processes that lead to the desired conclusions,
(p.
493)
The primary cognitive operation hypoth-
esized to mediate motivational effects is the
biased searching of memory. Evidence of
various types converges, she argued, on the
conclusion that "goals enhance the accessibility
of those knowledge structures—memories, be-
liefs,
and rules—that are consistent with desired
conclusions" (p. 494); "Motivation will cause
bias,
but cognitive factors such as the available
beliefs and rules will determine the magnitude
of the bias" (p. 495).
Several of the accounts of confirmation bias
that follow stress the role of cognitive limita-
tions as causal factors. It is possible, however,
and probable, in my view, that both motivational
and cognitive factors are involved and that each
type can mediate effects of the other.
Information-Processing Bases
for Confirmation Bias
The confirmation bias is sometimes attributed
in part to the tendency of people to gather
information about only one hypothesis at a time
and even with respect to that hypothesis to
consider only the possibility that the hypothesis
is true (or only the possibility that it is false) but
not to consider both possibilities simultaneously
(Tweney, 1984; Tweney & Doherty, 1983).
Doherty and Mynatt (1986) argued, for ex-
ample, that people are fundamentally limited to
think of only one thing at a time, and once
having focused on a particular hypothesis, they
continue to do so. This, they suggested, explains
why people often select nondiagnostic over
diagnostic information in Bayesian decision
situations. Suppose that one must attempt to
decide which of two diseases, A or B, a patient
with Symptoms X and Y
has.
One is informed of
the relative frequency of Symptom X among
people who have Disease
A
and is then given the
choice of obtaining either of the following items
of information: the relative frequency of people
with A who have Symptom Y or the relative
frequency of people with B who have symptom
X. Most people who have been given choices of
this sort opt for the first; they continue to focus
on the hypothesis that the patient has A, even
though learning the relative frequency of Y
given A does not inform the diagnosis, whereas
learning the relative frequency of X given B
does.
Assuming a restricted focus on a single
hypothesis, it is easy to see how that hypothesis
might become strengthened even if
it
is false. An
incorrect hypothesis can be sufficiently close to
being correct that it receives a considerable
amount of positive reinforcement, which may be
taken as further evidence of the correctness of
the hypothesis in hand and inhibit continued
search for an alternative. In many contexts
intermittent reinforcement suffices to sustain the
behavior that yields it.
People also can increase the likelihood of
getting information that is consistent with
existing beliefs and decrease the likelihood of

CONFIRMATION BIAS199
getting information that is inconsistent with
them by being selective with respect to where
they get information (Frey, 1986). The idea that
people tend to expose themselves more to
information sources that share their beliefs than
to those that do not has had considerable
credibility among social psychologists (Fes-
tinger, 1957; Klapper, 1960). Sears and Freed-
man (1967) have challenged the conclusiveness
of much of the evidence that has been evoked in
support of
this
idea. They noted that, when given
a choice of information that is supportive of a
view one holds and information that is support-
ive of an opposing view, people sometimes
select the former and sometimes the latter, and
sometimes they show no preference. Behavior
in these situations seems to depend on a number
of factors in addition to the polarity of the
information with respect to one's existing views,
such as people's level of education or social
status and the perceived usefulness of the
information that is offered.
Sears and Freedman (1967) stopped short,
however, of concluding that people are totally
unbiased in this respect. They noted the
possibility that "dramatic selectivity in prefer-
ences may not appear at any given moment in
time,
but, over a long period, people may
organize their surroundings in a way that
ensures de facto selectivity" (p. 213). People
tend to associate, on a long-term basis, with
people who think more or less as they do on
matters important to them; they read authors
with whom they tend to agree, listen to news
commentators who interpret current events in a
way that they like, and so on. The extent to
which people choose their associates because of
their beliefs versus forming their beliefs because
of their associates is an open question. But it
seems safe to assume that it goes a bit in both
directions. Finding lots of support for one's
beliefs and opinions would be a natural
consequence of principally associating with
people with whom one has much in common.
Gilovich (1991) made the important point that
for many beliefs or expectations confirmatory
events are likely to be more salient than
nonconfirmatory
ones.
If
a
fortune teller predicts
several events in one's life sometime during the
indefinite future, for example, the occurrence of
any predicted event is more likely to remind one
of the original prediction of that event than is its
nonoccurrence. Events predicted by a fortune
teller illustrate one-sided events. Unlike two-
sided events, which have the characteristic that
their nonoccurrence is as noticeable as their
occurrence, one-sided events are likely to be
noticed while their nonoccurrence is not. (An
example of a two-sided event would be the toss
of a coin following the prediction of
a
head. In this
case the nonoccurrence of the predicted out-
come would be as noticeable as its occurrence.)
Sometimes decision policies that rule out the
occurrence of certain types of events preclude
the acquisition of information that is counter-
indicative with respect to a hypothesis. Con-
sider, for example, the hypothesis that only
students who meet certain admission require-
ments are likely to be successful as college
students. If colleges admit only students who
meet those requirements, a critical subset of the
data that are necessary to falsify the hypothesis
(the incidence of students who do not meet the
admission requirements but are nevertheless
successful college students) will not exist
(Einhorn & Hogarth, 1978). One could argue
that this preclusion may be justified if the
hypothesis is correct, or nearly so, and if the
negative consequences of one type of error
(admitting many students who will fail) are
much greater than those of the other type
(failing to admit a few students who would
succeed). But the argument is circular because it
assumes the validity of the hypothesis in
question.
Some beliefs are such that obtaining evidence
that they are false is inherently impossible. If I
believe, for example, that most crimes are
discovered sooner or later, my belief may be
reinforced every time a crime is reported by a
law enforcement agency. But by definition,
undiscovered crimes are not discovered, so there
is no way of knowing how many or them there
are.
For the same reason, if I believe that most
crimes go undiscovered, there is no way to
demonstrate that this belief is wrong. No matter
how many crimes are discovered, the number of
undiscovered crimes is indeterminable because
being undiscovered means being uncounted.
Some have also given information-processing
accounts of why people, in effect, consider only
the probability of
an
event, assuming the truth of
a hypothesis of interest, and fail to consider the
probability of the same event, assuming the
falsity of that hypothesis. Evans (1989) argued

200RAYMOND S. NICKERSON
that one need not assume the operation of a
motivational bias—a strong wish to con-
firm—in order to account for this failure. It
could signify, according to Evans, a lack of
understanding of the fact that, without a
knowledge of p(D\~H), p(D\H) gives one no
useful information about p(H\D). That is,
p(D\H),
by
itself,
is not diagnostic with respect
to the truth or falsity of H. Possibly people
confuse p(D\H) with p(H\D) and take its
absolute value as an indication of the strength of
the evidence in favor of H. Bayes's rule of
inverse probability, a formula for getting from
p(D\H) to p(H\D) presumably was motivated,
in part, to resolve this confusion.
Another explanation of why people fail to
consider alternatives to a hypothesis in hand is
that they simply do not think to do so. Plausible
alternatives do not come to mind. This is seen by
some investigators to be, at least in part, a matter
of inadequate effort, a failure to do a sufficiently
extensive search for possibilities (Baron, 1985,
1994;
Kanouse, 1972).
Positive-Test Strategy or Positivity Bias
Arguing that failure to distinguish among
different senses of confirmation in the literature
has contributed to misinterpretations of both
empirical findings and theoretical prescriptions,
Klayman and Ha (1987) have suggested that
many phenomena of human hypothesis testing
can be accounted for by the assumption of a
general positive-test
strategy.
Application of this
strategy involves testing a hypothesis either by
considering conditions under which the hypoth-
esized event is expected to occur (to see if it
does occur) or by examining known instances of
its occurrence (to see if the hypothesized
conditions prevailed). The phenomenon bears
some resemblance to the finding that, in the
absence of compelling evidence one way or the
other, people are more inclined to assume that a
statement is true than to assume that it is false
(Clark & Chase, 1972; Gilbert, 1991; Trabasso,
Rollins, & Shaughnessy, 1971; Wallsten &
Gonzalez- Vallejo, 1994).
Baron, Beattie, and Hershey (1988), who
referred to the positive-test strategy as the
congruence heuristic, have shown that the
tendency to use it can be reduced if people are
asked to consider alternatives, but that they tend
not to consider them spontaneously. The fact
that people show a preference for questions that
would yield a positive answer if the hypothesis
is correct over questions that would yield a
negative answer if the hypothesis is correct
demonstrates that the positive-test strategy is not
a simple consequence of the confirmation bias
(Baron et al., 1988; Devine, Hirt, & Gehrke,
1990;
Skov & Sherman, 1986).
One could view the results that Wason (1960)
originally obtained with the number-triplet task,
which constituted the point of departure for
much of the subsequent work on confirmation
bias,
as a manifestation of the positive-test
strategy, according to which one tests cases one
thinks likely to have the hypothesized property
(Klayman & Ha, 1987). As already noted, this
strategy precludes discovering the incorrectness
of a hypothesized rule when instances that
satisfy the hypothesized rule constitute a subset
of those that satisfy the correct one, but it is an
effective strategy when the instances that satisfy
the correct rule constitute a subset of those that
satisfy the hypothesized one.
Suppose, for example, that the hypothesized
rule is successive even numbers and the correct
one is increasing numbers. All triplets that
satisfy the hypothesized rule also satisfy the
correct one, so using only such triplets as test
cases will not reveal the incorrectness of the
hypothesized rule. But if the hypothesized rule
is increasing numbers and the correct rule is
successive even numbers, the positive-test strat-
egy—which, in this case means trying various
triplets of increasing numbers—is likely to
provide the feedback necessary to discover that
the hypothesized rule is wrong. In both of the
examples considered, the strategy is to select
instances for testing that satisfy the hypoth-
esized rule; it is effective in revealing the rule to
be wrong in the second case, not because the
tester intentionally selects instances that will
show the rule to be wrong if it is wrong, but
because the relationship between hypothesized
and correct rules is such that the tester is likely
to discover the hypothesized rule to be wrong by
selecting test cases intended to show that it is
right.
Klayman and Ha (1987) analyzed various
possible relationships between the sets of
triplets delimited by hypothesized and correct
rules in addition to the two cases in which one
set is a proper subset of the other—overlapping
sets,
disjoint sets, identical sets—and showed

CONFIRMATION BIAS201
that the likely effectiveness of positive-test
strategy depends on which relationship pertains.
They also analyzed corresponding cases in
which set membership is probabilistic and drew
a similar conclusion. With respect to disconfir-
mation, Klayman and Ha argued the importance
of distinguishing between two strategies, one
involving examination of instances that are
expected not to have the target property, and the
other involving examination of instances that
one expects to falsify, rather than verify, the
hypothesis. Klayman and Ha contended that
failure to make this distinction clearly in the past
has been responsible for some confusion and
debate.
Several investigators have argued that a
positive-test strategy should not necessarily be
considered a biased information-gathering tech-
nique because questions prompted by this
strategy generally do not preclude negative
answers and, therefore, falsification of the
hypothesis being tested (Bassock & Trope,
1984;
Hodgins & Zuckerman, 1993; Skov &
Sherman, 1986; Trope & Mackie, 1987). It is
important to distinguish, however, between
obtaining information from a test because the
test was intended to yield the information
obtained and obtaining information adventi-
tiously from a test that was intended to yield
something other than what it did. Consider again
the number-triplet task. One might select, say,
6-7-8 for either of the following reasons,
among others: (a) because one believes the rule
to be increasing numbers and wants a triplet that
fits the rule, or (b) because one believes the rule
to be successive even numbers and wants to
increase one's confidence in this belief by
selecting a triplet that fails to satisfy the rule.
The chooser expects the experimenter's re-
sponse to the selected triplet to be positive in the
first case and negative in the second. In either
case,
the experimenter's response could be
opposite from what the chooser expects and
show the hypothesized rule to be wrong; the
response is adventitious because the test yielded
information that the chooser was not seeking
and did not expect to obtain.
The fact that people appear to be more likely
than not to test a hypothesized rule by selecting
cases that they believe will pass muster (that fit
the hypothesized rule) and lend credence to the
hypothesis by doing so justifies describing
typical performance on find-the-rule tasks like
the triplet task as illustrative of a confirmation
bias.
People appear to be much less likely to
attempt to get evidence for a hypothesized rule
by choosing a case that they believe does not fit
it (and expecting an informative-negative re-
sponse) or to select cases with the intended
purpose of ruling out one or more currently
plausible hypotheses from further consideration.
When a test that was expected to yield an
outcome that is positive with respect to a
hypothesized rule does not do so, it seems
appropriate to say that the positive-test strategy
has proved to be adventitiously informative.
Clearly, it is possible to select an item that is
consistent with a hypothesized rule for the
purpose of revealing an alternative rule to be
wrong, but there is little evidence that this is
often done. It seems that people generally select
test items that are consistent with the rule they
believe to be correct and seldom select items
with falsification in mind.
Klayman and Ha (1987) argued that the
positive-test strategy is sometimes appropriate
and sometimes not, depending on situational
variables such as the base rates of the phenom-
ena of interest, and that it is effective under
commonly occurring conditions. They argued
too,
however, that people tend to rely on it
overly much, treating it as a default strategy to
be used when testing must be done under
less-than-ideal conditions, and that it accounts
for many of the phenomena that are generally
interpreted as evidence of a pervasive confirma-
tion bias.
Evans (1989) has proposed an explanation of
the confirmation bias that is similar in some
respects to Klayman and Ha's (1987) account
and also discounts the possibility that people
intentionally seek to confirm rather than falsify
their hypotheses. Cognitive failure, and not
motivation, he argued, is the basis of the
phenomenon:
Subjects confirm, not because they want
to,
but because
they cannot think of the way to falsify. The cognitive
failure is caused by a form of selective processing
which is very fundamental indeed in cognition—a bias
to think about positive rather than negative informa-
tion, (p. 42)
With respect to Wason's (1960) results with
the number-triplet task, Evans suggested that
rather than attempting to confirm the hypotheses
they were entertaining, participants may simply
have been unable to think of testing them in a

202RAYMOND S. NICKERSON
negative manner; from a logical point of view,
they should have used potentially disconfirming
test cases, but they failed to think to do so.
Evans (1989) cited the results of several
efforts by experimenters to modify hypothesis-
testing behavior on derivatives of Wason's
number-set task by instructing participants
about the importance of seeking negative or
disconfirming information. He noted that al-
though behavioral changes were sometimes
induced, more often performance was not
improved. This too was taken as evidence that
results that have been attributed to confirmation
bias do not stem from a desire to confirm, but
rather from the difficulty people have in thinking
in explicitly disconfirmatory terms.
Evans used the same argument to account for
the results typically obtained with Wason's
(1966,
1968) selection task that have generally
been interpreted as evidence of the operation of
a confirmation bias. Participants select named
items in this task, according to this view,
because these are the only ones that come to
mind when they are thinking about what to do.
The bias that is operating is not that of wanting
to confirm a tentative hypothesis but that of
being strongly inclined to think only of informa-
tion that is explicitly provided in the problem
statement. In short, Evans (1989) distinguished
between confirmatory behavior, which he ac-
knowledges, and confirmatory intentions, which
he denies. The "demonstrable deficiencies in the
way in which people go about testing and
eliminating hypotheses," he contended, "are a
function of selective processing induced by a
widespread cognitive difficulty in thinking
about any information which is essentially
negative in its conception" (p. 63). The
tendency to focus on positive information and
fail to consider negative information is regarded
not as a conscious cognitive strategy but as the
result of preattentive processes. Positive is not
synonymous with confirmatory, but as most
studies have been designed, looking for positive
cases is tantamount to looking for confirmation.
The idea that people have a tendency to focus
more on positive than on negative information,
like the idea of a confirmation bias, is an old
one.
An observation by Francis Bacon (1620/
1939) can again illustrate the point: "It is the
peculiar and perpetual error of the human
understanding to be more moved and excited by
affirmatives than negatives; whereas it ought
properly to hold itself indifferently disposed
towards both alike" (p. 36). Evans's (1989)
argument that such a bias can account, at least in
part, for some of the phenomena that are
attributed to a confirmation bias is an intuitively
plausible one. A study in which Perkins et al.,
(1983) classified errors of reasoning made in
informal arguments constructed by over 300
people of varying age and educational level
supports the argument. Many of the errors
Perkins et al. identified involved participants'
failure to consider lines of reasoning that could
be used to defeat or challenge their conclusions.
I will be surprised if
a
positivity bias turns out
to be adequate to account for all of the ways in
which what has here been called a confirmation
bias manifests
itself,
but there are many
evidences that people find it easier to deal with
positive information than with negative: it is
easier to decide the truth or falsity of positive
than of negative sentences (Wason, 1959,1961);
the assertion that something is absent takes
longer to comprehend than the assertion that
something is present (Clark, 1974); and infer-
ences from negative premises require more time
to make or evaluate and are more likely to be
erroneous or evaluated incorrectly than are those
that are based on positive premises (Fodor,
Fodor, & Garrett, 1975). How far the idea can be
pushed is a question for research. I suspect that
failure to try to construct counterarguments or to
find counterevidence is a major and relatively
pervasive weakness of human reasoning.
In any case, the positivity bias itself requires
an explanation. Does such a bias have some
functional value? Is it typically more important
for people to be attuned to occurrences than to
nonoccurrences of possible events? Is language
processed more effectively by one who is
predisposed to hear positive rather than negative
assertions? Is it generally more important to be
able to make valid inferences from positive than
from negative premises? It would not be
surprising to discover that a positivity bias is
advantageous in certain ways, in which case
Bacon's dictum that we should be indifferently
disposed toward positives and negatives would
be wrong.
There is also the possibility that the positivity
bias is, at least in part, motivationally based.
Perhaps it is the case that the processing of
negative information generally takes more effort
than does the processing of positive information

CONFIRMATION BIAS203
and often we are simply not willing to make the
effort that adequate processing of the negative
information requires. As to why the processing
of negative information should require more
effort than the processing of positive informa-
tion, perhaps it is because positive information
more often than not is provided by the situation,
whereas negative information must be actively
sought, from memory or some other source. It is
generally clear from the statement of a hypoth-
esis,
for example, what a positive instance of the
hypothesized event would be, whereas that
which constitutes a negative instance may
require some thought.
Conditional Reference Frames
Several investigators have shown that when
people are asked to explain or imagine why a
hypothesis might be true or why a possible event
might occur, they tend to become more con-
vinced that the hypothesis is true or that the
event will occur, especially if they have not
given much thought to the hypothesis or event
before being asked to do so (Campbell & Fairey,
1985;
Hirt & Sherman, 1985; Sherman et al.,
1983).
In some cases, people who were asked to
explain why a particular event had occurred and
then were informed that the event did not occur
after they did so, still considered the event more
"likely" than did others who were not asked to
explain why it might occur (Ross et al., 1977).
Koehler (1991), who has reviewed much of
the work on how explanations influence beliefs,
has suggested that producing an explanation is
not the critical factor and that simply coming up
with a focal hypothesis is enough to increase
one's confidence in it. Anything, he suggested,
that induces one to accept the truth of a
hypothesis temporarily will increase one's
confidence that it is, in fact, true. Calling
attention to a specified hypothesis results in the
establishment of a focal hypothesis, and this in
turn induces the adoption of a conditional
reference frame, in which the focal hypothesis is
assumed to be true.
Adoption of a conditional reference frame
influences subsequent hypothesis-evaluation pro-
cesses in three ways, Koehler (1991) suggested:
it affects the way the problem is perceived, how
relevant evidence is interpreted, and the direc-
tion and duration of information search. Accord-
ing to this author,
Once a conditional reference frame has been induced
by an explanation task, a certain inertia sets in, which
makes it more difficult to consider alternative hypoth-
eses impartially. In other words, the initial impression
seems to persist despite the person's efforts to ignore it
while trying to give fair consideration to an alternative
view. (p. 503)
Hoch's (1984) findings regarding people who
were asked to generate reasons for expecting a
specified event and reasons against expecting it
support Koehler's conclusion: in Hoch's study
those who generated the pro reasons first and the
con reasons later considered the event more
probable than did those who generated the pro
and con reasons in the opposite order. Koehler
related the phenomenon to that of mental set or
fixedness that is sometimes described in discus-
sions of problem solving. He argued that
adopting a conditional reference frame to
determine confidence in a hypothesis is prob-
ably a good general method but that, like other
heuristic methods, it also can yield overconfi-
dence in some instances.
In a recent study of gambling behavior,
Gibson, Sanbonmatsu, and Posavac (1997)
found that participants who were asked to
estimate the probability that a particular team
would win the NBA basketball championship
made higher estimates of that team's probability
of winning than did control participants who
were not asked to focus on a single team; the
focused participants also were more willing to
bet on the focal team. This suggests that
focusing on one among several possible event
outcomes, even as a consequence of being
arbitrarily forced to do so, can have the effect of
increasing the subjective likelihood of that
outcome.
Pragmatism and Error Avoidance
Much of the discussion of confirmation bias is
predicated on the assumption that, in the
situations in which it has generally been
observed, people have been interested in deter-
mining the truth or falsity of some hypoth-
esises) under consideration. But determining its
truth or falsity is not the only, or necessarily
even the primary, objective one might have with
respect to a hypothesis. Another possibility is
that of guarding against the making of certain
types of mistakes.
In many real-life situations involving the
evaluation of a meaningful hypothesis, or the

204RAYMOND S. NICKERSON
making of a choice with an outcome that really
matters to the one making it, some ways of
being wrong are likely to be more regretable
than others. Investigators have noted that this
fact makes certain types of biases functional in
specific situations (Cosmides, 1989; Friedrich,
1993;
Hogarth, 1981; Schwartz, 1982). When,
for example, the undesirable consequences of
judging a true hypothesis to be false are greater
than those of judging a false hypothesis to be
true,
a bias toward confirmation is dictated by
some normative models of reasoning and by
common sense.
Friedrich (1993) argued that "our inference
processes are first and foremost pragmatic,
survival mechanisms and only secondarily truth
detection strategies" (p. 298). In this view,
peoples' inferential strategies are well suited to
the identification of potential rewards and the
avoidance of costly errors, but not to the
objective of hypothesis testing in accordance
with the logic of science. Inference strategies
that are often considered to be seriously flawed
not only may have desired effects in real-world
contexts, but may also be seen as correct when
judged in terms of an appropriate standard.
To illustrate the point, Friedrich (1993) used
the example of an employer who wants to test
the hunch that extroverts make the best sales-
people. If the employer checked the sales
performance only of extroverts, found it to be
very good and, on this basis, decided to hire only
extroverts for sales positions, one would say that
she had not made an adequate test of her hunch
because she did not rule out the possibility that
introverts might do well at sales also. But if her
main objective was to avoid hiring people who
will turn out to be poor at sales, satisfying
herself that extroverts make good sales people
suffices; the fact that she has not discovered that
introverts can be good at sales too could mean
that she will miss some opportunities by not
hiring them, but it does not invalidate the
decision to hire extroverts if the objective is to
ensure that poor performers do not get hired.
Schwartz (1982) also argued that when
responses have consequences that really matter,
people are more likely to be concerned about
producing desirable outcomes than about deter-
mining the truth or falsity of hypotheses.
Contingent reinforcement may create functional
behavioral units that people tend to repeat
because the behaviors have worked in the past,
and a bias toward confirmation is one of the
stereotyped forms of behavior in which the
operation of these units manifests
itself.
In
performing a rule-discovery task, one may be
attempting to maximize the probability of
getting a positive response, which is tantamount
to seeking a rule that is sufficient but not
necessary to do so. Given that one has identified
a condition that is sufficient for producing
desired outcomes, there may be no compelling
reason to attempt to determine whether that
condition is also necessary. Schwartz pointed
out too that, especially in social situations such
as some of those studied by Snyder and
colleagues attempting to evaluate hypotheses by
falsification would require manipulating people
and could involve considerable social cost.
Baron (1994) noted that truth seeking or
hypothesis testing often may be combined with
one or more other goals, and that one's behavior
then also must be interpreted in the light of the
other goal(s). If, for example, one is curious as
to why a cake turned out well despite the fact
that certain ingredients were substituted for
those called for by the recipe, one may be
motivated to explore the effects of the substitu-
tions in such a way that the next experimental
cake is likely to turn out well too.
When using a truth-seeking strategy would
require taking a perceived risk, survival is likely
to take precedence over truth finding, and it is
hard to argue that rationality would dictate
otherwise. It would seem odd to consider
irrational the refusal, say, to eat mushrooms that
one suspected of being poison because the
decision is calculated to preserve one's well-
being rather than to shed light on the question of
whether the suspicion is indeed true. In general,
the objective of avoiding disastrous errors may
be more conducive to survival than is that of
truth determination.
The desire to avoid a specific type of error
may coincidentally dictate the same behavior as
would the intention to determine the truth or
falsity of a hypothesis. When this is the case, the
behavior itself does not reveal whether the
individual's intention is to avoid the error or to
test the hypothesis. Friedrich (1993) suggested
that some behavior that has been taken as
evidence of people's preference for normative
diagnostic tests of hypotheses and their interest
in accuracy could have been motivated instead
by the desire to avoid specific types of
errors.
In

CONFIRMATION BIAS205
other words, even when behavior is consistent
with the assumption of truth seeking, it some-
times may be equally well interpreted, accord-
ing to this view, in terms of error-minimizing
strategies.
The assumption that decisions made or
conclusions drawn in many real-life situations
are motivated more by a desire to accomplish
specific practical goals or to avoid certain types
of errors than by the objective of determining
the truth or falsity of hypotheses is a plausible
one.
Pragmatic considerations of this sort could
often lead one to accept a hypothesis as true—to
behave as though it were true—on less than
compelling evidence that it is so, thus constitut-
ing a confirmation bias of sorts.
Educational Effects
At all levels of education, stress is placed on
the importance of being able to justify what one
believes. I do not mean to question the
appropriateness of this stress, but I do want to
note the possibility that, depending on how it is
conveyed, it can strengthen a tendency to seek
confirming evidence selectively or establish
such a tendency if it does not already exist. If
one is constantly urged to present reasons for
opinions that one holds and is not encouraged
also to articulate reasons that could be given
against them, one is being trained to exercise a
confirmation bias.
Narveson (1980) noted that when students
write compositions, they typically evaluate their
claims by considering supporting evidence only.
He argued that standard methods for teaching
composition foster this. The extent to which the
educational process makes explicit the distinc-
tion between case-building and evidence-
weighing deserves more attention. If
the
distinc-
tion is not made and what is actually case-
building passes for the impartial use of evidence,
this could go some way toward accounting for
the pervasiveness and strength of the confirma-
tion bias among educated adults.
Ideally, one would like students, and people
in general, to evaluate evidence objectively and
impartially in the formation and evaluation of
hypotheses. If, however, there are fairly perva-
sive tendencies to seek or give undue weight to
evidence that is confirmatory with respect to
hypotheses that people already hold and to avoid
or discount evidence that is disconfirmatory
with respect to them, there is a need to be
especially sensitive to the educational practices
that could serve to strengthen an already strong
bias.
Utility of Confirmation Bias
Most commentators, by far, have seen the
confirmation bias as a human failing, a tendency
that is at once pervasive and irrational. It is not
difficult to make a case for this position. The
bias can contribute to delusions of many sorts, to
the development and survival of superstitions,
and to a variety of undesirable states of mind,
including paranoia and depression. It can be
exploited to great advantage by seers, soothsay-
ers,
fortune tellers, and indeed anyone with an
inclination to press unsubstantiated claims. One
can also imagine it playing a significant role in
the perpetuation of animosities and strife
between people with conflicting views of the
world.
Even if one accepts the idea that the
confirmation bias is rooted more in cognitive
limitations than in motivation, can anyone doubt
that whenever one finds oneself engaged in a
verbal dispute it becomes very strong indeed? In
the heat of an argument people are seldom
motivated to consider objectively whatever
evidence can be brought to bear on the issue
under contention. One's aim is to win and the
way to do that is to make the strongest possible
case for one's own position while countering,
discounting, or simply ignoring any evidence
that might be brought against
it.
And what is true
of one disputant is generally true of the other,
which is why so few disputes are clearly won or
lost. The more likely outcome is the claim of
victory by each party and an accusation of
recalcitrance on the part of one's opponent.
But whenever an apparently dysfunctional
trait or behavior pattern is discovered to be
pervasive, the question arises as to how, if it is
really dysfunctional, did it get to be so
widespread. By definition, dysfunctional tenden-
cies should be more prone to extinction than
functional ones. But aspects of reasoning that
are viewed as flawed from one perspective
sometimes can be considered appropriate, per-
haps because they are adaptively useful in
certain real-world situations from another per-
spective (Arkes, 1991; Funder, 1987; Green-
wald, 1980). Does the confirmation bias have

206RAYMOND S. NICKERSON
some adaptive value? Does it serve some useful
purpose(s)?
Utility in Science
According to the principle of falsifiability
(Popper, 1959), an explanation (theory, model,
hypothesis) cannot qualify as scientific unless it
is falsifiable in principle. This is to say there
must be a way to show the explanation to be
false if in fact it is false. Popper focused on
falsifiability as the distinguishing characteristic
of the scientific method because of a conviction
that certain theories of the day (in particular,
Marx's theory of history, Freud's theory of
psychoanalysis, and Adler's individual psychol-
ogy) "appeared to be able to explain practically
everything that happened within the fields to
which they referred" (Popper, 1962/1981, p.
94).
Thus subscribers to any one of these
theories were likely to see confirming evidence
anywhere they looked. According to Popper
(1959),
the most characteristic element in this
situation seemed to be the incessant stream of
confirmations, of observations which 'verified'
the theories in question; and this point was
constantly emphasized by their adherents" (p.
94).
There was, in Popper's view, no conceiv-
able evidence that could be brought to bear on
any of these theories that would be viewed by an
adherent as grounds for judging it to be false.
Einstein's theory of relativity impressed Popper
as being qualitatively different in the important
respect that it made risky predictions, which is
to say predictions that were incompatible with
specific possible results of observation. This
theory was, in principle, refutable by empirical
means and therefore qualified as scientific
according to Popper's criterion.
Although Popper articulated the principle of
falsifiability more completely than anyone
before him, the idea has many antecedents in
philosophy and science. It is foreshadowed, for
example, in the Socratic method of refutation
(elenchos),
according to which what is to be
taken as truth is whatever survives relentless
efforts at refutation (Maclntyre, 1988). Lakatos
(1976,
1978) and Polya (1954a, 1954b) have
discussed the importance of this attitude in
reasoning in mathematics—especially in
proof-
making—at length. The principle of falsifiabil-
ity was also anticipated by T. H. Huxley
(1894/1908), who spoke of "a beautiful hypoth-
esis killed by an ugly fact," and by David
Hartley (1748/1981), who proposed a rule of
false. According to this rule, the acceptability of
any supposition or hypothesis should be its
ability to provide the basis for the deduction of
observable phenomena: "He that forms hypoth-
eses from the first, and tries them by the facts,
soon rejects the most unlikely ones; and being
freed from these, is better qualified for the
examination of those that are probable" (p. 90).
Hypotheses are strengthened more when
highly competent scientists make concerted
efforts to disprove them and fail than when
efforts at disproof are made by less competent
investigators or in are made half-hearted ways.
As Polya (1954a) put it, "the more danger, the
more honor." What better support could Ein-
stein's corpuscular theory of light have received
than Millikan's failure to show it to be wrong,
despite 10 years of experimentation aimed at
doing so? (It is interesting to note that
throughout this period of experimentation,
Millikan continued to insist on the untenability
of the theory despite his inability to show by
experiment its predictions to be in error.)
Despite the acceptance of the falsifiability
principle by the scientific community as a
whole, one would look long and hard to find an
example of a well-established theory that was
discarded when the first bit of disconfirming
evidence came to light. Typically an established
theory has been discarded only after a better
theory has been offered to replace it. Perhaps
this should not be surprising. What astronomer,
Waismann (1952) asked, would abandon Ke-
pler's laws on the strength of a single observa-
tion? Scientists have not discarded the idea that
light travels at a constant speed of about 300,000
kilometers per second and that nothing can
travel faster simply because of the discovery of
radio sources that seem to be emanating from a
single quasar and moving away from each other
at more than nine times that speed (Gardner,
1976).
It appears that, the principle of falsifiabil-
ity notwithstanding, "Science proceeds on
preponderance of evidence, not on finality"
(Drake, 1980, p. 55).
Application of the falsifiability principle to
the work of individual scientists seems to
indicate that when one comes up with a new
hypothesis, one should immediately try to
falsify it. Common sense suggests this too; if the
hypothesis is false, the sooner one finds that out,

CONFIRMATION BIAS207
the less time one will waste entertaining it. In
fact, as has already been noted, there is little
evidence that scientists work this way. To the
contrary, they often look much harder for
evidence that is supportive of a hypothesis than
for evidence that would show it to be false.
Kepler's laborious effort to find a connection
between the perfect polyhedra and the planetary
orbits is a striking example of a search by a
scientist for evidence to confirm a favored
hypothesis. Here is his account of the connec-
tion he finally worked out and his elation upon
finding it, as quoted in Boorstin (1985):
The earth's orbit is the measure of all things;
circumscribe around it a dodecahedron, and the circle
containing this will be Mars; circumscribe around Mars
a tetrahedron, and the circle containing this will be
Jupiter; circumscribe around Jupiter a cube, and the
circle containing this will be Saturn. Now inscribe
within the earth an icosahedron, and the circle
contained in it will be Mercury. You now have the
reason for the number of planets.... This was the
occasion and success of my labors. And how intense
was my pleasure from this discovery can never be
expressed in words. I no longer regretted the time
wasted. Day and night I was consumed by the
computing, to see whether this idea would agree with
the Copernican orbits, or if my joy would be carried
away by the wind. Within a few days everything
worked, and I watched as one body after another fit
precisely into its place among the planets, (p. 310)
People are inclined to make light of this
particular accomplishment of Kepler's today,
but it was a remarkable intellectual feat. The
energy with which he pursued what he saw as an
intriguing clue to how the world works is
inspiring. Bell (1946/1991) argued that it was
Kepler's "Pythagorean faith in a numerical
harmony of
the
universe" that sustained him "in
his darkest hours of poverty, domestic tragedy,
persecution, and twenty-two years of discourage-
ment as he calculated, calculated, calculated to
discover the laws of planetary orbits" (p. 181).
The same commitment that kept Kepler in
pursuit of confirmation of his polyhedral model
of planetary orbits yielded the three exquisitly
beautiful—and correct—laws of planetary mo-
tion for which he is honored today.
My point is not to defend the confirmation
bias as an effective guide to truth or even as a
heuristically practical principle of logical think-
ing. It is simply to note that the quest to find
support for a particular idea is a common
phenomenon in science (I. B. Cohen, 1985;
Holton, 1973), that such a quest has often
provided the motivation to keep scientists
working on demanding intellectual problems
against considerable odds, and that the resulting
work has sometimes yielded lasting, if unex-
pected, results.
Students of the scientific process have noted
the conservatism of science as an institution
(I.
B. Cohen, 1985; T. S. Kuhn, 1970), and
illustrations of it were given in an earlier part of
this article. This conservatism can be seen as an
institutional confirmation bias of sorts. Should
we view such a bias as beneficial overall or
detrimental to the enterprise? An extensive
discussion of this question is beyond the scope
of this article. However, it can be argued that a
degree of conservativism plays a stabilizing role
in science and guards the field against uncritical
acceptance of so-called discoveries that fail to
stand the test of time.
Price (1963) referred to conservatism in the
body of science as "a natural counterpart to the
open-minded creativity that floods it with too
many new ideas" (p. 64). Justification for a
certain degree of conservatism is found in the
embarrassment that the scientific community
has occasionally experienced as a consequence
of not being sufficiently sceptical of new
discoveries. The discovery of magnetic mono-
poles,
which was widely publicized before a
close examination of the evidence forced more
guarded interpretations, and that of polywater,
which motivated hundreds of research projects
over decade following its discovery in the
1960s, are examples.
The scientific community's peremtory rejec-
tion of Wegener's (1915/1966) theory of conti-
nental drift when it was first put forth is often
held out as an especially egregious example of
excessive—and self-serving—conservatism on
the part of scientists. The view has also been
expressed, however, that the geologists who
dismissed Wegener's theory, whatever their
motivations, acted in a way that was conducive
to scientific success. Solomon (1992), who took
this position, acknowledged that the behavior
was biased and motivated by the desire to
protect existing beliefs, but she argued that
"bias and belief perseverance made possible the
distribution of effort, and this in turn led to the
advancement of the debate over [continental]
drift" (p. 443).
Solomon's (1992) review of this chapter in
the history of geological research makes it clear

208RAYMOND S. NICKERSON
that the situation was not quite as simple as
some accounts that focus on the closed-
mindedness of the geologists at the time would
lead one to believe. The idea of continental drift
was not entirely new with Wegener, for
example, although Wegener was the first to
propose a well-developed theory. A serious
limitation of
the
theory was its failure to identify
a force of sufficient magnitude to account for the
hypothesized movement of continents. (The
notion of plate tectonics and evidence regarding
sea-floor spreading came much later; LeGrand,
1988.)
Solomon (1992) argued that it was, in part,
because Wegener was not trained as a geologist
and therefore not steeped in the "stabilist"
theories of the time, that his thinking, relatively
unconstrained by prior beliefs about the stability
of continents, could easily embrace a possibility
that was so contrary to the prevailing view. She
pointed out too that when geologists began to
accept the notion of drift, as evidence favoring it
accumulated, it was those with low publication
rates who were the most likely to do so: "their
beliefs were less entrenched (cognitively speak-
ing) than those who had reasoned more and
produced more, so belief perseverance was less
of
an
impediment to acceptance of drift"
(p.
449).
Although Solomon (1992) argued that bias
and belief perseverance were responsible for
much of the distribution of research effort that
led finally to the general acceptance of the
theory of continental drift, and to that of plate
tectonics to which it led in turn, she does not
claim that a productive distribution could not
have been effected without the operation of
these factors. The question of whether these
factors facilitated or impeded progress in
geology remains an unanswered one; it is not
inconceivable that progress could have been
faster if the distribution of effort were deter-
mined on some other basis.
In any case, it can be argued that a certain
degree of conservativism serves a useful stabiliz-
ing role in science and is consistent with, if not
dictated by, the importance science attaches to
testability and empirical validation. Moreover, if
Ziman (1978) is right, the vast majority of the
new hypotheses put forward by scientists prove
to be wrong:
Even in physics, there is no infallible procedure for
generating reliable knowledge. The calm order and
perfection of well-established theories, accredited by
innumerable items of evidence from a thousand
different hands, eyes and brains, is not characteristic of
the front-line of research, where controversy, conjec-
ture,
contradiction and confusion are rife. The physics
of undergraduate test-books is 90% true; the contents of
the primary research journals of physics is 90% false,
(p.
40)
"According to temperament," Ziman noted,
"one may be impressed by the coherence of
well-established theories, or horrified by the
contradictions of knowledge in the making" (p.
100).
Fischhoff and Beyth-Marom (1983) made a
related point when commenting on Mahoney's
(1977) finding that scientists tended to be less
critical of a fictitious study that reported results
supportive of the dominant hypothesis in their
field than of one that reported results that were
inconsistent with it. They noted that a reluctance
by scientists to relinquish pet beliefs is only one
interpretation that could be put on the finding.
Another possibility is that what appears to be
biased behavior reflects "a belief that investiga-
tors who report disconfirming results tend to use
inferior research methods (e.g., small samples
leading to more spurious results), to commit
common mistakes in experimental design, or,
simply, to be charlatans" (Fischoff and Beyth-
Marom, 1983, p. 251). To the extent that such a
belief is accurate, a bias against the ready
acceptance of results that are disconfirming of
prevailing hypotheses can be seen as a safeguard
against precipitous changes of view that may
prove to be unjustified. It does not follow, of
course, that this is the only reason for a
confirmation bias in science or the only effect.
Is Belief Perseverance Always Bad?
It is easy to see both how the confirmation
bias helps preserve existing beliefs, whether true
or false, and how the perseverance of unjustified
beliefs can cause serious problems. Is there
anything favorable to be said about a bias that
tends to perpetuate beliefs independently of
their factuality? Perhaps, at least from the
narrow perspective of an individual's mental
health. It may help, for example, to protect one's
ego by making one's favored beliefs less
vulnerable than they otherwise would be.
Indeed, it seems likely that a major reason why
the confirmation bias is so ubiquitous and so
enduring is its effectiveness in preserving

CONFIRMATION BIAS209
preferred beliefs and opinions (Greenwald,
1980).
But even among people who might see some
benefit to the individual in a confirmation bias,
probably few would contest the claim that when
the tendency to persevere in a belief
is
so strong
that one refuses to consider evidence that does
not support that
belief,
it is irrational and offends
our sense of intellectual honesty. That is not to
say that dogmatic confidence in one's own
beliefs and intolerance of opposing views can
never work to one's advantage. Boorstin (1958)
argued, for example, that it was precisely these
qualities that permitted the 17th-century New
England Puritans to establish a society with the
ingredients necessary for survival and prosper-
ity. He wrote,
Had they spent as much of their energy in debating with
each other as did their English contemporaries, they
might have lacked the single-mindedness needed to
overcome the dark, unpredictable perils of a wilder-
ness.
They might have merited praise as precursors of
modern liberalism, but they might never have helped
found a nation, (p. 9)
Contrary to the popular stereotype of the
Puritans, they were not preoccupied with
religious dogma but rather with more practical
matters because, as Boorstin noted, they had no
doubts and allowed no dissent. They worried
about such problems as how to select leaders
and representatives, the way to establish the
proper limits of political power, and how to
construct a feasible federal organization.
The question of the conditions under which
one should retain, reject, or modify an existing
belief is a controversial one (Cherniak, 1986;
Harman, 1986; Lycan, 1988). The controversy is
not likely to be settled soon. Whatever the
answer to the question is, the confirmation bias
must be recognized as a major force that works
against easy and frequent opinion change.
Probably very few people would be willing to
give up long-held and valued beliefs on the first
bit of contrary evidence found. It is natural to be
biased in favor of one's established beliefs.
Whether it is rational is a complicated issue that
can too easily be treated simplistically; however,
the view that a person should be sufficiently
objective and open minded to be willing to toss
out any belief upon the first bit of evidence that
it is false seems to me wrong for several reasons.
Many, perhaps most, of the beliefs that matter
to individuals tend not to be the type that can be
falsified, in the Popperian sense, by a single
counterindicative bit of
data.
They tend rather to
be beliefs for which both supportive and
counterindicative evidence can be found, and
the decision as to whether to hold them is
appropriately made on the basis of the relative
weights or merits of the pro and con arguments.
Second, it is possible to hold a belief for good
and valid reasons without being able to produce
all of those reasons on demand. Some beliefs are
shaped over many years, and the fact that one
cannot articulate every reason one has or has
ever had for a particular one of them does not
mean that it is unfounded. Also, as Nisbett and
Ross (1980) pointed out, there are practical time
constraints that often limit the amount of
processing of new information one can do. In
view of these limitations, the tendency to
persevere may be a stabilizing hedge against
overly frequent changes of view that would
result if one were obliged to hold only beliefs
that one could justify explicitly at a moment's
notice. This argument is not unlike the one
advanced by Blackstone (1769/1962) in defense
of not lightly scuttling legal traditions.
Third, for assertions of the type that represent
basic beliefs, there often are two ways to be
wrong: to believe false ones, or to disbelieve
true ones. For many beliefs that people hold,
these two possibilities are not equally accept-
able,
which is to say that an individual might
consider it more important to avoid one type of
error than the other. This is, of course, the
argument behind Pascal's famous wager.
To argue that it is not necessarily irrational to
refuse to abandon a long-held belief upon
encountering some evidence that appears contra-
dictory is not to deny that there is such a thing as
holding on to cherished beliefs too tenaciously
and refusing to give a fair consideration to
counterindicative evidence. The line between
understandable conservativism with respect to
changing established beliefs and obstinate closed-
mindedness is not an easy one to draw. But
clearly, people sometimes persevere beyond
reason. Findings such as those of Pitz (1969),
Pitz et al. (1967), Lord et al. (1979), and
especially Ross et al. (1975), who showed that
people sometimes persevere in beliefs even
when the evidence on which the beliefs were
initially formed has been demonstrated to them
to be fraudulent, have provided strong evidence
of that fact.

210RAYMOND S. NICKERSON
Confirmation Bias Compounding
Inadequate Search
The idea that inadequate effort is a basic
cause of faulty reasoning is common among
psychologists. Kanouse (1972) suggested that
people may be satisfied to have an explanation
for an event that is sufficient and not feel the
need to seek the best of all possibilities. Nisbett
and Ross (1980) supported the same idea and
suggested that it is especially the case when
attempting to come up with
a
causal explanation:
The lay scientist seems to search only until a plausible
antecedent is discovered that can be linked to the
outcome through some theory in the repertoire. Given
the richness and diversity of that repertoire, such a
search generally will be concluded quickly and easily.
A kind of vicious cycle results. The subjective ease of
explanation encourages confidence, and confidence
makes the lay scientist stop searching as soon as a
plausible explanation is adduced, so that the complexi-
ties of the task, and the possibilities for "alternative
explanations" no less plausible than the first, are never
allowed
to
shake the lay scientist's confidence,
(p.
119,120)
Perkins and his colleagues expressed essen-
tially the same idea with their characterization
of people as make-sense epistimologists (Per-
kins et al., 1983, 1991). The idea here is that
people think about a situation only to the extent
necessary to make sense—perhaps superficial
sense—of it:
When sense is achieved, there is no need to continue.
Indeed, because further examination of an issue might
produce contrary evidence and diminish or cloud the
sense of one's first pass, there is probably reinforce-
ment for early closure to reduce the possibility of
cognitive dissonance. Such a makes-sense approach is
quick, easy, and, for many purposes, perfectly ad-
equate. (Perkins et al.,
1991,
p. 99)
Baron (1985, 1994) and Pyszczynski and
Greenberg (1987) also emphasized insufficient
search as the primary reason for the premature
drawing of conclusions.
All of these characterizations of the tendency
of people to do a less-than-thorough search
through the possibilities before drawing conclu-
sions or settling on causal explanations are
consistent with Simon's (1957,1983/1990) view
of humans as satisficers, as opposed to optimiz-
ers or maximizers. The question of interest in
the present context is that of how the criterion
for being satisfied should be set. Given that
search is seldom exhaustive and assuming that,
in many cases, it cannot
be,
how much should be
enough? How should one decide when to stop?
Without at least tentative answers to these
types of questions, it is difficult to say whether
any particular stopping rule should be consid-
ered rational. Despite this vagueness with
respect to criteria, I believe that the prevailing
opinion among investigators of reasoning is that
people often stop—come to conclusions, adopt
explanations—before they should, which is not
to deny that they may terminate a search more
quickly when time is at a premium and search
longer when accuracy is critical (Kruglanski,
1980;
Kruglanski & Ajzen, 1983; Kruglanski &
Freund, 1983). The search seems to be not only
less than extensive but, in many cases, minimal,
stopping at the first plausible endpoint.
If this view is correct, the operation of a
confirmation bias will compound the problem.
Having once arrived at a conclusion,
belief,
or
point of view, however prematurely, one may
thereafter seek evidence to support that position
and interpret newly acquired information in a
way that is partial to it, thereby strengthening it.
Instead of making an effort to test an initial
hypothesis against whatever counterindicative
evidence might be marshalled against it, one
may selectively focus on what can be said in its
favor. As the evidence favoring the hypothesis
mounts, as it is bound to do if one gives
credence to evidence that is favorable and
ignores or discounts that that is not, one will
become increasingly convinced of the correct-
ness of the belief one originally formed.
Concluding Comments
We are sometimes admonished to be tolerant
of
the
beliefs or opinions of
others
and critical of
our own. Laplace (1814/1956), for example,
gave this eloquent advice:
What indulgence should we not have . . . for opinions
different from ours, when this difference often depends
only upon the various points of view where circum-
stances have placed us! Let us enlighten those whom
we judge insufficiently instructed; but first let us
examine critically our own opinions and weigh with
impartiality their respective probabilities, (p. 1328)
But can we assess the merits of our own
opinions impartially? Is it possible to put a
belief that one holds in the balance with an
opposing belief that one does not hold and give
them a fair weighing? I doubt that it is. But that

CONFIRMATION BIAS211
is not to say that we cannot hope to learn to do
better than we typically do in this regard.
In the aggregate, the evidence seems to me
fairly compelling that people do not naturally
adopt a falsifying strategy of hypothesis testing.
Our natural tendency seems to be to look for
evidence that is directly supportive of hypoth-
eses we favor and even, in some instances, of
those we are entertaining but about which are
indifferent. We may look for evidence that is
embarrassing to hypotheses we disbelieve or
especially dislike, but this can be seen as
looking for evidence that is supportive of the
complementary hypotheses. The point is that we
seldom seem to seek evidence naturally that
would show a hypothesis to be wrong and to do
so because we understand this to be an effective
way to show it to be right if it really is right.
The question of the extent to which the
confirmation bias can be modified by training
deserves more research than it has received.
Inasmuch as a critical step in dealing with any
type of
bias
is recognizing its existence, perhaps
simply being aware of the confirmation bias—of
its pervasiveness and of the many guises in
which it appears—might help one both to be a
little cautious about making up one's mind
quickly on important issues and to be somewhat
more open to opinions that differ from one's
own than one might otherwise be.
Understanding that people have a tendency to
overestimate the probable accuracy of their
judgments and that this tendency is due, at least
in part, to a failure to consider reasons why these
judgments might be inaccurate provides a
rationale for attempting to think of reasons for
and (especially) against a judgment that is to be
made. Evidence that the appropriateness of
people's confidence in their judgments can be
improved as a consequence of such efforts is
encouraging (Arkes, Faust, Guilmette, & Hart,
1988;
Hoch, 1984,1985; Koriatetal., 1980).
The knowledge that people typically consider
only one hypothesis at a time and often make the
assumption at the outset that that hypothesis is
true leads to the conjecture that reasoning might
be improved by training people to think of
alternative hypotheses early in the hypothesis-
evaluation process. They could be encouraged
to attempt to identify reasons why the comple-
ment of the hypothesis in hand might be true.
Again, the evidence provides reason for opti-
mism that the approach can work (C. A.
Anderson, 1982; C. A. Anderson & Sechler,
1986;
Lord, Lepper, & Preston, 1984).
To the extent that what appear to be biases are
sometimes the results of efforts to avoid certain
types of decision errors (Friedrich, 1993),
making these other types of possible errors more
salient may have a debiasing effect. On the other
hand, if the errors that one is trying to avoid are,
in fact, more costly than bias errors, such
debiasing might not be desirable in all instances.
Here the distinction between the objective of
determining the truth or falsity of a hypothesis
and that of avoiding an undesirable error (at the
expense of accepting the possibility of commit-
ting a less undesirable one) is an important one
to keep in mind.
Finally, I have argued that the confirmation
bias is pervasive and strong and have reviewed
evidence that I believe supports this claim. The
possibility will surely occur to the thoughtful
reader that what I have done is itself an
illustration of the confirmation bias at work. I
can hardly rule the possibility out; to do so
would be to deny the validity of what I am
claiming to be a general rule.
References
Alloy, L. B.,
&
Abramson, L.
Y.
(1980). The cognitive
component of human helplessness and depression:
A critical analysis. In J. Garber & M. E. P.
Seligman (Eds.), Human helplessness: Theory and
applications. New York: Academic Press.
Alloy, L. B., & Tabachnik, N. (1984). Assessment of
covariation by humans and animals: The joint
influence of prior expectations and current situ-
ational information. Psychological Review, 91,
112-148.
Anderson,
C.
A.
(1982). Inoculation and counterexpla-
nation: Debiasing techniques in the perseverance
of social theories. Social
Cognition,
1, 126-139.
Anderson, C. A., & Sechler, E. S. (1986). Effects of
explanation and counterexplanation on the develop-
ment and use of social theories. Journal of
Personality and Social
Psychology,
50, 24-34.
Anderson, N. H., & Jacobson, A. (1965). Effect of
stimulus inconsistency and discounting instruc-
tions in personality impression formation. Journal
of Personality and Social Psychology, 2, 531-539.
Arkes, H. R. (1991). Costs and benefits of judgment
errors:
Implications for debiasing. Psychological
Bulletin,
110,
486-498.
Arkes, H. R., Dawes, R. M., & Christensen, C.
(1986).
Factors influencing the use of a decision
rule in a probabilistic task. Organizational Behav-
ior and Human Decision
Processes,
37, 93-110.

212RAYMOND S. NICKERSON
Arkes, H. R., Faust, D., Guilmette, T. J., & Hart, K.
(1988).
Elimination of the hindsight bias. Journal
of Applied
Psychology,
73, 305-307.
Bacon, F. (1939). Novum organum. In Burtt, E. A.
(Ed.),
The English philosophers from Bacon to Mill
(pp.
24-123). New
York:
Random House. (Original
work published in 1620)
Baddeley, A. D., & Woodhead, M. (1983). Improving
face recognition ability. In S. M. A. Lloyd-Bostock
& B. R. Clifford (Eds.), Evaluating witness
evidence. Chichester, England: Wiley.
Barber, B. (1961). Resistence by scientists to
scientific discovery. Science, 134, 596-602.
Baron, J. (1985). Rationality and intelligence. New
York: Cambridge University Press.
Baron, J. (1991). Beliefs about thinking. In J. F. Voss,
D.
N. Perkins, & J. W. Segal (Eds.), Informal
reasoning and education (pp. 169-186). Hillsdale,
NJ: Erlbaum.
Baron, J. (1994). Thinking and deciding (2nd ed.).
New York: Cambridge University Press.
Baron, J. (1995). Myside bias in thinking about
abortion. Thinking and
reasoning,
7, 221-235.
Baron, J., Beattie, J., & Hershey, J. C. (1988).
Heuristics and biases in diagnostic reasoning II:
Congruence, information, and certainty. Organiza-
tional Behavior and Human Decision Processes,
42,
88-110.
Barrows, H. S., Feightner, J. W., Neufeld, V. R., &
Norman, G. R. (1978). Analysis of the clinical
methods of medical students and physicians.
Hamilton, Ontario, Canada: McMaster University
School of Medicine.
Barrows, H. S., Norman, G. R., Neufeld, V. R., &
Feightner, J. W. (1977). Studies of the clinical
reasoning process of medical students and physi-
cians.
Proceedings of
the
sixteenth annual
confer-
ence on research in medical education. Washing-
ton,
DC:
Association of American Medical Colleges.
Bassock, M., & Trope, Y. (1984). People's strategies
for testing hypotheses about another's personality:
Confirmatory or diagnostic? Social Cognition, 2,
199-216.
Beattie, J., & Baron, J. (1988). Confirmation and
matching biases in hypothesis testing. Quarterly
Journal of Experimental Psychology, 40A, 269-
298.
Beck, A. T. (1976). Cognitive therapy and the
emotional disorders. New York: International
Universities Press.
Bell, E. T. (1991). The magic of numbers. New York:
Dover. (Original work published 1946)
Berwick, D. M., Fineberg, H. V., & Weinstein, M. C.
(1981).
When doctors meet numbers. American
Journal of Medicine, 71, 991.
Beyth-Marom, R., &
Fischhoff,
B.
(1983). Diagnostic-
ity and pseudodiagnosticity. Journal of Personality
and Social
Research,
45, 1185-1197.
Blackstone, W. (1962). Commentaries on the laws of
England of public wrongs. Boston: Beacon.
(Original work published 1769)
Boorstin, D. J. (1958). The Americans: The colonial
experience. New York: Vintage Books.
Boorstin, D. J. (1985). The discoverers: A history of
man's search to know his world and
himself.
New
York: Vintage Books.
Bruner, J. S., Goodnow, J. J., & Austin, G. A. (1956).
A study of
thinking.
New
York:
Wiley.
Bruner, J. S., & Potter, M. C. (1964). Interference in
visual recognition. Science, 144, 424—425.
Camerer, C. (1988). Illusory correlations in percep-
tions and predictions of organizational traits.
Journal of Behavioral Decision
Making,
1, 11-94.
Campbell, J. D., & Fairey, P. J. (1985). Effects of
self-esteem, hypothetical explanations, and verbal-
ization of expectancies on future performance.
Journal of Personality and Social Psychology, 48,
1097-1111.
Cassells, W., Schoenberger, A., & Grayboys, T. B.
(1978).
Interpretation by physicians of clinical
laboratory results. New England Journal of Medi-
cine, 299, 999.
Chapman, L. J. (1967). Illusory correlation in
observational report. Journal of Verbal Learning
and
Verbal
Behavior,
6, 151-155.
Chapman, L. J., & Chapman, J. P. (1959). Atmo-
sphere effect reexamined. Journal of Experimental
Psychology, 58, 220-226.
Chapman, L. J., & Chapman, J. P. (1967a). Genesis of
popular but erroneous psychodiagnostic observa-
tions.
Journal of Abnormal Psychology, 72, 193-
204.
Chapman, L. J., & Chapman, J. P. (1967b). Illusory
correlation as an obstacle to the use of valid
psychodiagnostic signs. Journal of Abnormal
Psychology, 74, 271-280.
Chapman, L. J. & Chapman, J. P. (1969). Illusory
correlation as an obstacle to the use of valid
psychodiagnostic signs. Journal of Abnormal
Psychology, 74, 271-280.
Cheng, P. W., & Holyoak, K. J. (1985). Pragmatic
reasoning schemas. Cognitive Psychology, 17,
391-416.
Chernev, A. (1997). The effect of common features on
brand choice: Moderating the effect of attribute
importance. Journal of Consumer Research, 23,
304-311.
Cherniak, C. (1986). Minimal
rationality.
Cambridge,
MA: MIT Press.
Christensen-Szalanski, J. J., & Bushyhead, J. B.
(1988).
Physicians' use of probabilistic information
in a real clinical setting. In J. Dowie & A. Elstein
(Eds.),
Professional
judgment.
A reader in clinical
decision making (pp. 360-373). Cambridge, En-
gland: Cambridge University Press. (Original work
published 1981)
Clark, H. H. (1974). Semantics and comprehension.
In
T.
A. Sebeok (Ed.), Current trends in linguistics.

CONFIRMATION BIAS213
Volume 12: Linguistics and adjacent arts and
sciences. The Hague, Netherlands: Mouton.
Clark, H. H., & Chase, W. B. (1972). On the process
of comparing sentences against pictures. Cognitive
Psychology, 3, 472-517.
Cohen, I. B. (1985). Revolution in science. Cam-
bridge, MA: Harvard University Press.
Cohen, L. J. (1981). Can human irrationality be
experimentally demonstrated?
Behavioral
and Brain
Sciences, 4,
317-331.
Collins, S., & Pinch, J. (1993). The Golem: What
everyone should know about science. New York:
Cambridge University Press.
Cosmides, L. (1989). The logic of social exchange:
Has natural selection shaped how humans reason?
Studies with the Wason selection task. Cognition,
31,
187-276.
Cosmides, L., & Tooby, J. (1992). Cognitive adapta-
tions for social exchange. In J. Barkow, L.
Cosmides, & J. Tooby (Eds.), The adapted
mind:
Evolutionary psychology and the generation of
culture (pp. 162-228). New York: Oxford Univer-
sity Press.
Crocker, J. (1981). Judgment of covariation by social
perceivers. Psychological Bulletin, 90, 272-292.
Darley, J. M., & Fazio, R. H. (1980). Expectancy
confirmation processes arising in the social interac-
tion sequence. American Psychologist, 35, 867-
881.
Darley, J. M., & Gross, P. H. (1983). A hypothesis-
confirming bias in labelling effects. Journal of
Personality and Social
Psychology,
44,
20-33.
DeSmet, A. A., Fryback, D. G., & Thornbury, J. R.
(1979).
A second look at the utility of radiographic
skull examinations for trauma. American Journal
of Roentgenology, 132, 95.
Devine, P. G., Hirt, E. R., & Gehrke, E. M. (1990).
Diagnostic and confirmation strategies in trait
hypothesis testing. Journal of Personality and
Social
Psychology,
58, 952-963.
Devine, P. G., & Ostrom, T. M. (1985). Cognitive
mediation of inconsistency discounting. Journal of
Personality and Social
Psychology,
49, 5-21.
Doherty, M. E., & Mynatt, C. R. (1986). The magical
number one. In D. Moates & R. Butrick (Eds.),
Inference Ohio
University
Interdisciplinary Confer-
ence 86 (Proceedings of the Interdisciplinary
Conference on Inference; pp. 221-230). Athens:
Ohio University.
Doherty, M. E., Mynatt, C. R., Tweney, R. D., &
Schiavo, M. D. (1979). Pseudodiagnosticity. Acta
Psychologica, 43,
111-121.
Drake, S. (1980). Galileo. New York: Oxford
University Press.
Duncan, B. L. (1976). Differential social perception
and attribution of intergroup violence: Testing the
lower limits of stereotyping of Blacks. Journal of
Personality and Social
Psychology,
34, 590-598.
Dusek, J. B. (1975). Do teachers bias children's
learning? Review of Educational Research, 45,
661-684.
Einhorn, H. J., & Hogarth, R. M. (1978). Confidence
in judgment: Persistence of the illusion of validity.
Psychological
Review,
85, 395—416.
Elstein, A. S., & Bordage, G. (1979). Psychology of
clinical reasoning. In G. Stone, F. Cohen, & N.
Adler (Eds.) Health psychology: A handbook. San
Francisco: Jossey-Bass.
Elstein, A. S., Shulman, L. S., & Sprafka, S. A.
(1978).
Medical problem solving: An analysis of
clinical reasoning. Cambridge, MA: Harvard
University Press.
Evans, J. St. B. T. (1972). On the problems of
interpreting reasoning data: Logical and psychologi-
cal approaches. Cognition, 1, 373-384.
Evans, J. St. B. T. (1982). The psychology of
deductive reasoning. London: Routledge & Kegan
Paul.
Evans, J. St. B. T. (1989). Bias in human reasoning:
Causes and consequences. Hillsdale, NJ: Erlbaum.
Evans, J. St. B. T., & Lynch, J. S. (1973). Matching
bias in the selection task. British Journal of
Psychology, 64, 391-397.
Evans, J. St., B. P., Newstead, E., & Byrne, R. M. J.
(1993).
Human reasoning: The psychology of
deduction. Hove, England: Erlbaum.
Farley, J., & Geison, G. L. (1974). Science politics
and spontaneous generation in nineteenth-century
France: The Pasteur-Pouchet debate. Bulletin for
the History of Medicine, 48, 161-198.
Feldman, J. M., Camburn, A., & Gatti, G. M. (1986).
Shared distinctiveness as a source of illusory correla-
tion in performance appraisal.
Organizational
Behav-
ior and
Human Decision
Process,
37,
34-59.
Festinger, L. (1957). A theory of cognitive disso-
nance. Stanford, CA: Stanford University Press.
Fischhoff,
B. (1977). Perceived informativeness of
facts.
Journal of Experimental Psychology: Human
Perception and Performance, 3, 349-358.
Fischhoff,
B. (1982). Debiasing. In D. Kahneman, P.
Slovic, & A. Tversky (Eds.), Judgment under
uncertainty: Heuristics and biases (pp. 422—444).
Cambridge, England: Cambridge University Press.
Fischhoff,
B., & Beyth-Marom, R. (1983). Hypoth-
esis evaluation from a Bayesian perspective.
Psychological
Review,
90, 239-260.
Fodor, J. D., Fodor, J. A., & Garrett, M. F. (1975). The
psychological unreality of semantic representa-
tions.
Linguistic
Inquiry,
4,
515-531.
Forer, B. (1949). The fallacy of personal validation: A
classroom demonstration of
gullibility.
Journal of
Abnormal and Social
Psychology,
44, 118-123.
Foster, G., Schmidt, C, & Sabatino, D. (1976).
Teacher expectancies and the label "learning
disabilities." Journal of Learning Disabilities, 9,
111-114.
Freedman, J. L. (1964). Involvement, discrepancy,
and change. Journal of Abnormal and Social
Psychology, 69, 290-295.

214RAYMOND S. NICKERSON
Frey, D. (1986). Recent research on selective
exposure to information. In L. Berkowitz (Ed.),
Advances in experimental social psychology (Vol.
19,
pp. 41-80). New York: Academic Press.
Friedrich, J. (1993). Primary error detection and
minimization (PEDMIN) strategies in social cogni-
tion: A reinterpretation of confirmation bias phe-
nomena. Psychological
Review,
100, 298-319.
Funder, D. C. (1987). Errors and mistakes: Evaluating
the accuracy of social judgment. Psychological
Bulletin, 101, 79-90.
Gardner, M. (1957). Fads and fallacies in the name of
science. New York: Dover.
Gardner, M. (1976). The relativity explosion. New
York: Vintage Books.
Gibson, B., Sanbonmatsu, D. M., & Posavac, S. S.
(1997).
The effects of selective hypothesis testing
on gambling. Journal of Experimental Psychology:
Applied,
3, 126-142.
Gigerenzer, G., Hoffrage, U., & Kleinbolting, H.
(1991).
Probabilistic mental models: A Brun-
swikian theory of confidence. Psychological Re-
view,
98, 506-528.
Gigerenzer, G., & Hug, K. (1992). Domain-specific
reasoning: Social contracts, cheating, and perspec-
tive change. Cognition, 43,
127-171.
Gigerenzer, G., Swijtink, Z., Porter, T., Daston, L.,
Beatty, J., & Kriiger, L. (1989). The empire of
chance:
How probability changed science
and every-
day life. New York: Cambridge University Press.
Gilbert, D. T. (1991). How mental systems believe.
American Psychologist, 46, 107-119.
Gilovich, T. (1983). Biased evaluation and persis-
tence in gambling. Journal of Personality and
Social
Psychology,
44, 1110-1126.
Gilovich, T. (1991). How we know what isn't so: The
fallibility of human reason in everyday life. New
York: Free Press.
Glenberg, A. M., Wilkinson, A. C, & Epstein, W.
(1982).
The illusion of knowing: Failure in the
self-assessment of comprehension. Memory and
Cognition, 10, 597-602.
Goldberg, L. R. (1968). Simple models or simple
processes? Some research in clinical judgment.
American Psychologist, 23, 483—496.
Golding, S. L., & Rorer, L. G. (1972). Illusory
correlation and subjective judgement. Journal of
Abnormal
Psychology,
80, 249-260.
Goodman, N. (1966). The structure of appearance
(2nd ed.). Indianapolis, IN: Bobbs-Merrill.
Graesser, A. C, & Hemphill, D. (1991). Question
answering in the context of scientific mechanisms.
Journal of Memory and
Language,
30, 186-209.
Greenwald, A. G. (1980). The totalitarian ego:
Fabrication and revision of personal history.
American Psychologist, 35, 603-618.
Griffin, D. W., Dunning, D., & Ross, L. (1990). The
role of construal processes in overconfident predic-
tions about the self and others. Journal of
Personality
and Social
Psychology,
59,
1128-1139.
Griffin, D. W., & Tversky, A. (1992). The weighing of
evidence and the determinants of confidence.
Cognitive
Psychology,
24, 411-435.
Griggs, R. A., & Cox, J. R. (1993). Permission
schemas and the selection task. In J. St. B. T. Evans
(Ed.),
The cognitive psychology of reasoning (pp.
637-651). Hillsdale, NJ: Erlbaum.
Hamilton, D. L. (1979). A cognitive attributional
analysis of stereotyping. In L. Berkowitz (Ed.),
Advances in Experimental Social
Psychology,
(Vol.
12).
New York: Academic Press.
Hamilton, D. L., Dugan, P. M., & Trolier, T. K.
(1985).
The formation of stereotypic beliefs:
Further evidence for distinctiveness-based illusory
correlations. Journal of Personality and Social
Psychology, 48, 5-17.
Harman, G. (1986). Change in view: Principles of
reasoning. Cambridge, MA: MIT Press.
Hartley, D. (1981). Hypotheses and the "rule of the
false."
In R. D. Tweney, M. E. Doherty, & C. R.
Mynatt (Eds.), Scientific thinking (pp. 89-91). New
York: Columbia University Press. (Original work
published 1748)
Hasdorf,
A. H., & Cantril, H. (1954). They saw a
game. Journal of Abnormal and Social Psychology,
49, 129-134.
Hausch, D. B., Ziemba, W. T., & Rubenstein, M.
(1981).
Efficiency of the market for racetrack
betting. Management
Science,
27, 1435-1452.
Hawking, S. W. (1988). A brief history of time: From
the big bang to black holes. New York: Bantam
Books.
Hayden, T., & Mischel, W. (1976). Maintaining trait
consistency in the resolution of behavioral inconsis-
tency: The wolf in sheep's clothing? Journal of
Personality, 44, 109-132.
Hempel, C. (1945). Studies in the logic of confirma-
tion.
Mind,
54(213), 1-26.
Hendry, S. H., & Shaffer, D. R. (1989). On testifying
in one's own
behalf:
Interactive effects of eviden-
tial strength and defendant's testimonial demeanor
on jurors' decisions. Journal of Applied Psychol-
ogy, 74, 539-545.
Henle, M. (1962). On the relation between logic and
thinking. Psychological
Review,
69, 366-378.
Henrion, M., &
Fischhoff,
B. (1986). Assessing
uncertainty in physical constants. American Jour-
nal of Physics, 54, 791-798.
Hirt, E. R., & Sherman, S. J. (1985). The role of prior
knowledge in explaining hypothetical events.
Journal of Experimental Social Psychology, 21,
519-543.
Hoch, S. J. (1984). Availability and inference in
predictive judgment. Journal of Experimental
Psychology: Learning, Memory, and Cognition,
10, 649-662.

CONFIRMATION BIAS215
Hoch, S. J. (1985). Counterfactual reasoning and
accuracy in predicting personal events. Journal of
Experimental Psychology:
Learning,
Memory, and
Cognition,
11,
719-731.
Hoch, S. J., & Tschirgi, J. E. (1983). Cue redundancy
and extra logical inferences in a deductive
reasoning task. Memory and Cognition, 11, 200-
209.
Hodgins, H. S., & Zuckerman, M. (1993). Beyond
selecting information: Baises in spontaneous ques-
tions and resultant conclusions. Journal of Experi-
mental Social
Psychology,
29, 387^07.
Hogarth, R. M. (1981). Beyond discrete biases:
Functional and dysfunctional aspects of judgmen-
tal heuristics. Psychological Bulletin, 90, 197-217.
Hollis, M. (1970). Reason and ritual. In B. R. Wilson
(Ed.),
Rationality (pp. 221-239). Oxford, England:
Blackwell.
Holstein, J. A. (1985). Jurors' interpretations and jury
decision making. Law and Human Behavior, 9,
83-99.
Holton, G. (1973). Thematic origins of scientific
thought.
Cambridge, MA: Harvard University
Press.
Huxley, T. H. (1908). Discourses, biological and
geological. In Collected essays. (Vol. 8). London:
MacMillan and Company. (Original work pub-
lished 1894)
Hyman, R. (1977). Cold reading. The Skeptical
Inquirer, 1, 18-37.
Jennings, D., Amabile, T. M., & Ross, L. (1982).
Informal covariation assessment: Data-based ver-
sus theory-based judgments. In A. Tversky, D.
Kahneman, & P. Slovic (Eds.), Judgment under
uncertainty: Heuristics and biases. New York:
Cambridge University Press.
Johnson-Laird, P. N., Legrenzi, P., & Legrenzi, M. S.
(1972).
Reasoning and a sense of reality. British
Journal of Psychology, 63, 395-400.
Jones,
E. E., & Goethals, G. (1972). Order effects in
impression formation: Attribution context and the
nature of the entity. In E. E. Jones and others
(Eds.),
Attribution: Perceiving the causes of
behavior. Morristown, NJ: General Learning Press.
Jones,
E. E., Rock, L., Shaver, K. G., Goethals, G. R.,
& Ward, L. M. (1968). Pattern of performance and
ability attribution: An unexpected primacy effect.
Journal of Personality and Social Psychology, 10,
317-340.
Juslin, P. (1993). An explanation of the hard-easy
effect in studies of realism of confidence in one's
general knowledge. European Journal of Cognitive
Psychology, 5,
55-71.
Juslin, P. (1994). The overconfidence phenomenon as
a consequence of informal experimenter-guided
selection of almanac items. Organizational Behav-
ior and Human Decision Processes, 57, 226-246.
Kahneman, D., & Tversky, A. (1973). On the
psychology of prediction. Psychological Review,
80,
237-251.
Kalven, H., & Zeisel, H. (1966). The American jury.
Boston: Little, Brown.
Kanouse, D. E. (1972). Language, labeling, and
attribution. In E. E. Jones, and others (Eds.),
Attribution: Perceiving the causes of behavior.
Morristown, NJ: General Learning Press.
Kelley, H. H. (1950). The warm-cold variable in first
impressions of
persons.
Journal of Personality, 18,
431^39.
Keren, G. B. (1987). Facing uncertainty in the game
of bridge: A calibration study. Organizational
Behavior and Human Decision Processes, 39,
98-114.
Kern, L., & Doherty, M. E. (1982). "Pseudodiagnos-
ticity" in an idealized medical problem-solving
environment. Journal of Medical Education, 57,
100-104.
Kidd, J. B. (1970). The utilization of subjective
probabilities in production planning. Ada Psycho-
logica, 34, 338-347.
Kirby, K. N. (1994a). False alarm: A reply to Over
and Evans. Cognition, 52, 245-250.
Kirby, K. N. (1994b). Probabilities and utilities of
fictional outcomes in Wason's four-card selection
task. Cognition, 51, 1-28.
Klapper, J. T. (1960). The effects of mass communica-
tions. Glencoe, IL: Free Press.
Klayman, J., & Ha, Y-W. (1987). Confirmation,
disconfirmation, and information in hypothesis
testing. Psychological
Review,
94, 211-228.
Koehler, D. J. (1991). Explanation, imagination, and
confidence in judgment. Psychological Bulletin,
110,499-519.
Koriat, A., Lichtenstein, S., &
Fischhoff,
B. (1980).
Reasons for confidence. Journal of Experimental
Psychology: Human Learning and Memory, 6,
107-118.
Kroger, J. K., Cheng, P. W., & Holyoak, K. J. (1993).
Evoking the permission schema: The impact of
explicit negation and a violation-checking context.
In J. St. B. T. Evans (Ed.), The cognitive
psychology of
reasoning
(pp. 615-635). Hillsdale,
NJ: Erlbaum.
Kruglanski, A. W. (1980). Lay epistemology process
and contents. Psychological
Review,
87, 70-87.
Kruglanski, A. W., & Ajzen, I. (1983). Bias and error
in human judgment. European Journal of Social
Psychology, 13, 1-44.
Kruglanski, A. W., & Freund, T. (1983). The freezing
and unfreezing of lay-inferences: Effects on
impressional primacy, ethnic stereotyping, and
numerical anchoring. Journal of Experimental
Social
Psychology,
19, 448^68.
Kuhn, D. (1989). Children and adults as intuitive
scientists. Psychological
Review,
96, 674-689.
Kuhn, D., Weinstock, M., & Flaton, R. (1994). How

216RAYMOND S. NICKERSON
well do jurors reason? Competence dimensions of
individual variations in a juror reasoning task.
Psychological
Science,
5, 289-296.
Kuhn, T. S. (1970). The structure of scientific
revolutions (2nd ed). Chicago: University of
Chicago Press.
Kunda, Z. (1990). The case for motivated reasoning.
Psychological
Bulletin,
108, 480-498.
Kunda, Z., & Nisbett, R. E. (1986). The psychomet-
rics of everyday life. Cognitive Psychology, 18,
195-224.
Lakatos, I. (1976). Proofs and refutations: The logic
of mathematical discovery (J. Worrall & E. Zahar,
Eds.).
New
York:
Cambridge University Press.
Lakatos, I. (1978). Falsification and the methodology
of scientific research programmes. In I. Lakatos
The methodology of scientific research pro-
grammes (J. Worrall & G. Currie, Eds.; pp. 8-101).
New
York:
Cambridge University Press.
Langer, E. J., & Abelson, R. P. (1974). A patient by
any other name... : Clinical group differences in
labeling bias. Journal of Consulting and Clinical
Psychology, 42, 4-9.
Laplace,
P.
S. (1956). Concerning probability. In J. R.
Newman (Ed.), The world of mathematics (Vol. 2;
pp.
1325-1333). New York: Simon and Schuster.
(Original work published 1814)
Lawson, R. (1968). Order of presentation as a factor
in jury persuasion. Kentucky Law Journal, 56,
523-555.
Lefford, A. (1946). The influence of emotional
subject matter on logical reasoning. Journal of
General
Psychology,
34,
127-151.
LeGrand, H. E. (1988). Drifting continents and
shifting theories:
The
modern revolution in geology
and scientific change. Cambridge, England: Cam-
bridge University Press.
Legrenzi, P. (1970). Relations between language and
reasoning about deductive rules. In G. B. Flores
d'Arcais & W. J. M. Levelt (Eds.), Advances in
psychologistics (pp. 322-333). Amsterdam: North
Holland.
Lenski, G. E., & Leggett, J. C. (1960). Caste, class,
and deference in the research interview. American
Journal of Sociology, 65, 463^4-67.
Levine, M. (1970). Human discrimination learning.
The subset-sampling assumption. Psychological
Bulletin, 74, 397-404.
Liberman, N., & Klar, Y. (1996). Hypothesis testing
in Wason's selection task: Social exchange cheat-
ing detection or task understanding. Cognition, 58,
127-156.
Lichtenstein, S., &
Fischhoff,
B. (1977). Do those
who know more also know more about how much
they know? Organizational Behavior and Human
Performance, 20, 159-183.
Lichtenstein, S.,
Fischhoff,
B., & Phillips, L. D.
(1977).
Calibration of probabilities: The state of
the art. In H. Jungermann & G. de Zeeuw (Eds.),
Decision making and change in human affairs (pp.
275-324). Dordrecht, Netherlands: Reidel.
Lingle, J. H., & Ostrom, T. M. (1981). Principles of
memory and cognition in attitude formation. In
R. E. Petty, T. M. Ostrom, & T. C. Brock (Eds.),
Cognitive responses in persuasive communica-
tions: A text in attitude change (pp. 399-420).
Hillsdale, NJ: Erlbaum.
Loftus, E. F, & Wagenaar, W. A. (1988). Lawyers'
predictions of success. Jurimetrics Journal, 28,
437^53.
Lord, C. G., Lepper, M. R., & Preston, E. (1984).
Considering the opposite: A corrective strategy for
social judgment. Journal of Personality and Social
Psychology, 47, 1231-1243.
Lord, C, Ross, L., & Lepper, M. R. (1979). Biased
assimilation and attitude polarization: The effects
of prior theories on subsequently considered
evidence. Journal of Personality and Social
Psychology, 37, 2098-2109.
Luchins, A. S. (1942). Mechanization in problem
solving: The effect of Einstellung. Psychological
Monographs, 54, 1-95.
Luchins, A. S. (1957). Experimental attempts to
minimize the impact of first impressions. In C. I.
Hovland (Ed.), The order of presentation in
persuasion. New Haven, CT: Yale University
Press.
Lusted, L. B. (1977). A study of the efficacy of
diagnostic reaiologic procedures: Final report on
diagnostic
efficacy.
Chicago: Efficacy Study Com-
mittee of the American College of Radiology.
Lycan,
W.
C. (1988). Judgment and justification. New
York: Cambridge University Press.
Maclntyre,
A.
(1988). Whose justice? Which rational-
ity?
Notre Dame,
IN:
University of Notre Dame Press.
Mackay, C. (1932). Extraordinary popular delusions
and
the
madness of crowds (2nd
ed.).
Boston: Page.
(Original second edition published 1852)
Mahoney, M. J. (1976). Scientist as subject: The
psychological imperative. Cambridge, MA: Ball-
inger.
Mahoney, M. J. (1977). Publication prejudices.
Cognitive Therapy and Research, 1, 161-175.
Manktelow, K. I., & Over, D. E. (1990). Deontic
thought and the selection task. In K. J. Gilhooly,
M. T. G. Keane, R. H. Logic, & G. Erdos. (Eds.),
Lines of thinking (Vol. 1). London: Wiley.
Manktelow, K. I., & Over, D. E. (1991). Social roles
and utilities in reasoning with deontic conditionals.
Cognition, 39, 85-105.
Manktelow, K. I., & Over, D. E. (1992). Utility and
deontic reasoning: Some comments on Johnson-
Laird and Byrne. Cognition, 43, 183-188.
Markovits, H., & Savary, F. (1992). Pragmatic
schemas and the selection task. Quarterly Journal
of Experimental
Psychology,
45A, 133-148.

CONFIRMATION BIAS217
Matlin, M. W., & Stang, D. J. (1978). The Pollyanna
principle: Selectivity in language, memory and
thought. Cambridge, MA: Shenkman.
McGuire, W. J. (1960). A syllogistic analysis of
cognitive relationships. In M. J. Rosenberg, C. I.
Hovland, W. J. McGuire, R. P. Abelson, & J. W.
Brehm (Eds.), Attitude organization and change
(pp.
65-110). New Haven, CT: Yale University
Press.
Meehl, P. (1954). Clinical versus statistical predic-
tion:
A theoretical analysis and a review of the
evidence. Minneapolis: University of Minnesota
Press.
Meehl, P. (1960). The cognitive activity of the
clinician. American Psychologist, 15, 19-27.
Meichenbaum, D. H., Bowers, K. S., & Ross, R. R.
(1969).
A behavioral analysis of teacher expec-
tancy effect. Journal of Personality and Social
Psychology, 13, 306-316.
Merton, R. K. (1948). The self-fulfilling prophecy.
Antioch
Review,
8, 193-210.
Merton, R. K. (1957). Priorities in scientific discov-
ery: A chapter in the sociology of science.
American Sociological
Review,
22, 635-659.
Millward, R. B., & Spoehr, K. T. (1973). The direct
measurement of hypothesis-testing strategies. Cog-
nitive Psychology, 4, 1-38.
Mischel, W. (1968). Personality and assessment.
New York: Wiley.
Mischel, W., Ebbesen, E., & Zeiss, A. (1973).
Selective attention to the
self:
Situational and
dispositional determinants. Journal of Personality
and Social
Psychology,
27, 129-142.
Mischel, W., & Peake, P. K. (1982). Beyond deja vu
in the search for cross-situational consistency.
Psychological
Review,
89, 730-755.
Mitroff,
I. (1974). The subjective side of science.
Amsterdam: Elsevier.
Murphy, A. H., & Winkler, R. L. (1974). Subjective
probability forecasting experiments in meteorol-
ogy: Some preliminary results. Bulletin of the
American Meteorological Society, 55, 1206-1216.
Murphy, A. H., & Winkler, R. L. (1977). Can weather
forecasters formulate reliable probability forecasts
of precipitation and temperature? National Weather
Digest, 2, 2-9.
Myers, D. G., & Lamm, H. (1976). The group
polarization phenomenon. Psychological Bulletin,
83,
602-627.
Mynatt, C. R., Doherty, M. E., & Tweney, R. D.
(1977).
Confirmation bias in a simulated research
environment: An experimental study of scientific
inferences. Quarterly Journal of Experimental
Psychology, 29, 85-95.
Narveson, R. D. (1980). Development and learning:
Complementary or conflicting aims in humanities
education? In R. G. Fuller, R. F. Bergstrom, E. T.
Carpenter, H. J. Corzine, J. A. McShance, D. W.
Miller, D. S. Moshman, R. D. Narveson, J. L. Petr,
M. C. Thornton, & V. G. Williams (Eds.),
Piagetian programs in higher education (pp.
79-88).
Lincoln, NE: ADAPT Program.
Nickerson, R. S. (1996). Hempel's paradox and
Wason's selection task: Logical and psychological
puzzles of confirmation. Thinking and reasoning,
2,
1-31.
Nisbett, R. E., & Ross, L. (1980). Human inference:
Strategies and shortcomings of social judgement.
Englewood Cliffs, NJ: Prentice-Hall.
Oaksford, M., & Chater, N. (1994). A rational
analysis of the selection task as optimal data
selection. Psychological
Review,
101,
608-631.
Oskamp, S. (1965). Overconfidence in case study
judgments. Journal of Consulting Psychology, 29,
261-265.
Over, D. E., & Evans, J. St. B. T. (1994). Hits and
misses: Kirby on the selection task. Cognition, 52,
235-243.
Pennebaker, J.
W.,
& Skelton,
J.
A.
(1978).
Psychologi-
cal parameters of physical symptoms. Personality
and Social Psychology Bulletin, 4, 524-530.
Pennington, N., & Hastie, R. (1993). The story model
for juror decision making. In R. Hastie (Ed.), Inside
the juror:
The
psychology of juror decision making
(pp.
192-221). New York: Cambridge University
Press.
Perkins, D. N., Allen, R., & Hafner, J. (1983).
Difficulties in everyday reasoning. In W. Maxwell
(Ed.),
Thinking: The frontier expands. Hillsdale,
NJ: Erlbaum.
Perkins, D. N., Farady, M., & Bushey, B. (1991).
Everyday reasoning and the roots of intelligence.
In J. F. Voss, D. N. Perkins, & J. W. Segal (Eds.),
Informal reasoning and education (pp. 83-106).
Hillsdale, NJ: Erlbaum.
Peterson, C. R., & DuCharme, W. M. (1967). A
primacy effect in subjective probability revision.
Journal of Experimental
Psychology,
73, 61-65.
Pitz, G. F. (1969). An inertia effect (resistance to
change) in the revision of opinion. Canadian
Journal of Psychology, 23,
24-33.
Pitz, G. F. (1974). Subjective probability distributions
for imperfectly know quantities. In L. W. Gregg
(Ed.),
Knowledge and cognition. New York:
Lawrence Erlbaum Associates.
Pitz, G. F, Downing, L., & Reinhold, H. (1967).
Sequential effects in the revision of subjective
probabilities. Canadian Journal of Psychology, 21,
381-393.
Politzer, G. (1986). Laws of language use and formal
logic.
Journal of Psycholinguistic Research, 15,
47-92.
Poly a, G. (1954a). Mathematics and plausible
reasoning. Volume 1: Induction and analogy in
mathematics. Princeton, NJ: Princeton University
Press.

218RAYMOND S. NICKERSON
Polya, G. (1954b). Mathematics and plausible
reasoning. Volume 2: Patterns of plausible infer-
ence. Princeton, NJ: Princeton University Press.
Popper, K. (1959). The logic of scientific discovery.
New York: Basic Books.
Popper, K. (1981). Science, pseudo-science, and
falsifiability. In R. D. Tweney, M. E. Doherty, &
C. R. Mynatt (Eds.), Scientific thinking (pp.
92-99).
New York: Columbia University Press.
(Original work published in 1962)
Price, D. J. de S. (1963). Little science, big science.
New York: Columbia University Press.
Pyszczynski, T., & Greenberg, J. (1987). Toward an
integration of cognitive and motivational perspec-
tives on social inference: A biased hypothesis-
testing model. Advances in experimental social
psychology (pp. 297-340). New York: Academic
Press.
Ray, J. J. (1983). Reviving the problem of acquies-
cence response bias. Journal of Social Psychology,
121,
81-96.
Revlis, R. (1975a). Syllogistic reasoning: Logical
decisions from a complex data base. In R. J.
Falmagne (Ed.), Reasoning: Representation and
process. New York: Wiley.
Revlis, R. (1975b). Two models of syllogistic
inference: Feature selection and conversion. Jour-
nal of Verbal Learning and Verbal Behavior, 14,
180-195.
Rhine, R. J., & Severance, L. J. (1970). Ego-
involvement, discrepancy, source credibility, and
attitude change. Journal of Personality and Social
Psychology, 16, 175-190.
Rist, R. C. (1970). Student social class and teacher
expectations: The self-fulfilling prophecy in ghetto
education. Harvard Educational
Review,
40, 411-
451.
Rosenhan, D. L. (1973). On being sane in insane
places. Science, 179, 250-258.
Rosenthal, R. (1974). On the social psychology of
self-fulfilling prophecy: Further
evidence
for Pyg-
malion effects and their mediating mechanisms.
New
York:
MSS Modular Publications, Module 53.
Rosenthal, R., & Jacobson, L. (1968) Pygmalion in
the classroom. New York: Hold, Rinehart and
Winston.
Ross,
L. (1977). The intuitive psychologist and his
shortcomings. In L. Berkowitz (Ed.), Advances in
experimental social psychology, 10, New York:
Academic Press.
Ross,
L.,
&
Anderson, C. (1982). Shortcomings in the
attribution process: On the origins and mainte-
nance of erroneous social assessments. In A.
Tversky, D. Kahneman, & P. Slovic (Eds.),
Judgement under uncertainty: Heursitics and
biases. Cambridge, England: Cambridge Univer-
sity Press.
Ross,
L., & Lepper, M. R. (1980). The perseverance
of beliefs: Empirical and normative considerations.
In R. Shweder & D. Fiske (Eds.), New directions
for methodology of social and behavioral science:
Fallibel judgement in behavioral research (Vol. 4,
pp.
17-36). San Francisco: Jossey-Bass.
Ross,
L., Lepper, M. R., & Hubbard, M. (1975).
Perserverance in self perception and social percep-
tion: Biased attributional processes in the
debrief-
ing paradigm. Journal of Personality and Social
Psychology, 32, 880-892.
Ross,
L., Lepper, M. R., Strack, F, & Steinmetz, J. L.
(1977).
Social explanation and social expection:
The effects of real and hypothetical explanations
upon subjective likelihood. Journal of Personality
and Social
Psychology,
35, 817-829.
Roszak, T. (1986). The cult of information: The
folklore of computers and the true art of thinking.
New York: Pantheon Books.
Salmon, W. C. (1973). Confirmation. Scientific
American, 228(5),
75-83.
Sawyer, J. (1966). Measurement and prediction,
clinical and statistical. Psychological Bulletin, 66,
178-200.
Schuman, H., & Presser, S. (1981). Questions and
answers in attitude surveys. New York: Academic
Press.
Schwartz, B. (1982). Reinforcement-induced behav-
ioral stereotypy: How not to teach people to
discover rules. Journal of Experimental Psychol-
ogy: General,
111,
23-59.
Sears,
D. O., & Freedman, J. L. (1967). Selective
exposure to information: A critical review. Public
Opinion
Quarterly,
31, 194-213.
Shaklee, H., &
Fischhoff,
B. (1982). Strategies of
information search in causal analysis. Memory and
Cognition, 10, 520-530.
Sherman, S. J., Zehner, K. S., Johnson, J., & Hirt,
E. R. (1983). Social explanation: The role of
timing, set, and recall on subjective likelihood
estimates. Journal of Personality and Social
Psychology, 44, 1127-1143.
Simon, H. A. (1957). Models of man: Social and
rational. New
York:
Wiley.
Simon, H. A. (1990). Alternative visions of rational-
ity. In P. K. Moser (Ed.), Rationality in action:
Contemporary approaches (pp. 189-204). New
York: Cambridge University Press. (Original work
published 1983)
Skov, R. B., & Sherman, S. J. (1986). Information-
gathering processes: Diagnosticity, hypothesis con-
firmatory strategies and perceived hypothesis
confirmation. Journal of Experimental Social
Psychology, 22,
93-121.
Slovic, P.,
Fischhoff,
B., & Lichtenstein, S. (1977).
Behavioral decision theory. Annual Review of
Psychology, 28, 1-39.
Smyth, C. P. (1890). Our inheritance in the great

CONFIRMATION BIAS219
pyramid (5th ed.). New York:
Randolf.
(Original
work published 1864)
Snyder, M. (1981). Seek and ye shall find: Testing
hypotheses about other people. In E. T. Higgins,
C. P. Heiman, & M. P. Zanna (Eds.), Social
cognition: The Ontario symposium on personality
and social psychology (pp. 277-303). Hillsdale,
NJ: Erlbaum.
Snyder, M. (1984). When belief creates reality. In L.
Berkowitz (Ed.), Advances in experimental social
psychology (Vol. 18). New York: Academic Press.
Snyder, M., & Campbell, B. H. (1980). Testing
hypotheses about other people: The role of the
hypothesis. Personality and Social Psychology
Bulletin, 6, 421^26.
Snyder, M, & Gangestad, S. (1981). Hypotheses-
testing processes. New directions in attribution
research (Vol. 3). Hillsdale, NJ: Erlbaum.
Snyder, M., & Swann, W. B. (1978a). Behavioral
confirmation in social interaction: From social
perception to social reality. Journal of Experimen-
tal Social
Psychology,
14, 148-162.
Snyder, M., & Swann, W. B. (1978b). Hypothesis-
testing processes in social interaction. Journal of
Personality and Social Psychology, 36, 1202-
1212.
Snyder, M, Tanke, E. D., & Berscheid, E. (1977).
Social perception and interpersonal behavior: On
the self-fulfilling nature of social stereotypes.
Journal of Personality and Social Psychology, 35,
656-666.
Snyder, M., & Uranowitz, S. W. (1978). Reconstruct-
ing the past: Some cognitive consequences of
person perception. Journal of Personality and
Social
Psychology,
36, 941-950.
Solomon, M. (1992). Scientific rationality and human
reasoning. Philosophy of Science, 59, 439—455.
Strohmer, D. C, & Newman, L. J. (1983). Counselor
hypothesis-testing strategies. Journal of Counsel-
ing Psychology, 30, 557-565.
Swann, W. B., Jr., Giuliano, T., & Wegner, D. M.
(1982).
Where leading questions can lead: The
power of conjecture in social interaction. Journal
of Personality and Social Psychology, 42, 1025-
1035.
Taplin, J. E. (1975). Evaluation of hypotheses in
concept identification. Memory and Cognition, 3,
85-96.
Taylor, J. (1859). The great
pyramid:
Why was it
built? And who built it? London: Longman, Green,
Longman & Roberts.
Tetlock,
P.
E., & Kim, J. I. (1987). Accountability and
judgment processes in a personality prediction
task. Journal of Personality and Social Psychol-
ogy, 52, 700-709.
Thomas, L. (1979). The Medusa and the snail: More
notes of a biology watcher. New York: Viking
Press.
Thurstone, L. L. (1924). The nature of intelligence.
London: Routledge & Kegan Paul.
Tishman, S., Jay, E., & Perkins, D. N. (1993).
Teaching thinking dispositions: From transmission
to enculturation. Theory into practice, 32, 147-
153.
Trabasso, T., Rollins, H., & Shaughnessey, E. (1971).
Storage and verification stages in processing
concepts. Cognitive Psychology, 2, 239-289.
Trope, Y, & Bassock, M. (1982). Confirmatory and
diagnosing strategies in social information gather-
ing. Journal of Personality and Social Psychology,
43,
22-34.
Trope, Y, & Bassock, M. (1983). Information-
gathering strategies in hypothesis-testing. Journal
of Experimental Social
Psychology,
19, 560-576.
Trope, Y, Bassock, M., & Alon, E. (1984). The
questions lay interviewers ask. Journal of Person-
ality, 52, 90-106.
Trope, Y, & Mackie, D. M. (1987). Sensitivity to
alternatives in social hypothesis-testing. Journal of
Experimental Social
Psychology,
23, 445-459.
Troutman, C. M., & Shanteau, J. (1977). Inferences
based on nondiagnostic information. Organiza-
tional Behavior and Human Performance, 19,
43-55.
Tuchman, B. W. (1984). The march of folly: From
Troy
to
Vietnam.
New York: Ballantine Books.
Tweney, R. D. (1984). Cognitive psychology and the
history of science: A new look at Michael Faraday.
In H. Rappart, W. van Hoorn, & S. Bern. (Eds.),
Studies in the history of psychology and the social
sciences (pp. 235-246). Hague, The Netherlands:
Mouton.
Tweney, R. D., & Doherty, M. E. (1983). Rationality
and the psychology of inference. Synthese, 57,
139-161.
Tweney, R. D., Doherty, M. E., Worner, W. J., Pliske,
D.
B., Mynatt, C. R., Gross, K. A., & Arkkelin,
D.
L. (1980). Strategies of rule discovery in an
inference task. Quarterly Journal of Experimental
Psychology, 32, 109-123.
Valentine, E. R. (1985). The effect of instructions on
performance in the Wason selection task. Current
Psychological Research and Reviews, 4, 214-223.
Von Daniken, E. (1969). Chariots of
the
gods? New
York: Putnam.
Wagenaar, W. A., & Keren, G. B. (1986). Does the
expert know? The reliability of predictions and
confidence ratings of experts. In E. Hollnagel, G.
Maneine, & D. Woods (Eds), Intelligent decision
support in process environments (pp. 87-107).
Berlin: Springer.
Waismann, F. (1952). Verifiability. In A. G. N. Flew
(Ed.),
Logic and
language.
Oxford: Basil Blackwell.
Wallsten, T. S., & Gonzalez-Vallejo, C. (1994).
Statement verification: A stochastic model of

220RAYMOND S. NICKERSON
judgment and response. Psychological Review,
101,
490-504.
Wason, P. C. (1959). The processing of positive and
negative information. Quarterly Journal of Experi-
mental
Psychology,
11,
92-107.
Wason, P. C. (1960). On the failure to eliminate
hypotheses in a conceptual task. Quarterly Journal
of Experimental
Psychology,
12, 129-140.
Wason, P. C. (1961). Response to affirmative and
negative binary statements. British Journal of
Psychology, 52, 133-142.
Wason, P. C. (1962). Reply to Wetherick. Quarterly
Journal of Experimental
Psychology,
14, 250.
Wason, P. C. (1966). Reasoning. In B. M. Foss (Ed.),
New horizons in psychology I, Harmondsworth,
Middlesex, England: Penguin.
Wason, P. C. (1968). Reasoning about a rule.
Quarterly Journal of Experimental
Psychology,
20,
273-281.
Wason, P. C. (1977). "On the failure to eliminate
hypotheses...."—A second look. In
P.
N.
Johnson-
Laird &
P.
C. Wason (Eds.),
Thinking:
Readings in
cognitive science (pp. 307-314). Cambridge, En-
gland: Cambridge University Press. (Original work
published 1968)
Wason, P. C, & Johnson-Laird, P. N. (1972).
Psychology of
reasoning:
Structure and
content.
Cambridge, MA: Harvard University Press.
Wason, P. C, & Shapiro, D. (1971). Natural and
contrived experience in a reasoning problem.
Quarterly Journal of Experimental
Psychology,
23,
63-71.
Webster, E. C. (1964). Decision making in the
employment interview. Montreal, Canada: Indus-
trial Relations Center, McGill University.
Wegener, A. (1966). The origin of continents and
oceans (4th ed.; J. Biram, Trans.) London: Dover.
(Original work published in 1915)
Weinstein, N. D. (1980). Unrealistic optimism about
future life events. Journal of Personality and
Social
Psychology,
39, 806-820.
Weinstein, N. D. (1989). Optimistic biases about
personal risks. Science, 246, 1232-1233.
Wetherick, N. E. (1962). Eliminative and enumerative
behaviour in a conceptual task. Quarterly Journal
of Experimental
Psychology,
14, 246-249.
Wilkins, W. (1977). Self-fulling prophecy: Is there a
phenomenon to explain? Psychological Bulletin,
84, 55-56.
Winkler, R. L., & Murphy, A. H. (1968). "Good"
probability assessors. Journal of Applied
Meteorol-
ogy, 1, 751-758.
Woods, S., Matterson, J., & Silverman, J. (1966).
Medical students' disease: Hypocondriasis in
medical education. Journal of Medical Education,
41,
785-790.
Yachanin, S. A., & Tweney, R. D. (1982). The effect
of thematic content on cognitive strategies in the
four-card selection task. Bulletin of the Psycho-
nomic
Society,
19, 87-90.
Zanna, M. P., Sheras, P., Cooper, J., & Shaw, C.
(1975).
Pygmalion and Galatea: The interactive
effect of teacher and student expectancies. Journal
of Experimental Social
Psychology,
11, 279-287.
Ziman, J. (1978). Reliable knowledge. Cambridge,
England: Cambridge University Press.
Zuckerman, M., Knee, R., Hodgins, H. S., & Miyake,
K. (1995). Hypothesis confirmation: The joint
effect of positive test stratecy and acquiescence
response set. Journal of Personality and Social
Psychology, 68, 52-60.
Received August 1, 1997
Revision received December 16, 1997
Accepted December 18, 1997