Breaking NEWz you can UzE...
Three days of hearings in murder case
Mille Lacs County Times, MN - Aug 29, 2008
The professor testified on the validity of fingerprints. Cole has written a book on the history of fingerprint identification. “Uniqueness is not enough to ...
Jury sequestered in cabbie-killing case
Austin American-Statesman, TX - Aug 28, 2008
After Vallejo's acquittal, the case went cold until 2004, when an Austin police fingerprint examiner entered prints found on a plastic bag in Hinojosa's cab ...
Innocent man's jailing called 'honest mistake'
Annapolis Capital, MD - Aug 28, 2008
Those charges were based largely on Detective Tate's assertion the county's crime lab had matched Mr. Jonassen's fingerprints to those found at the scene. ...
Bank robber pleads guilty
Corvallis Gazette Times, OR - Aug 27, 2008
Police were able to lift a fingerprint, which was matched to Baird. A comparison with fingerprints in a law enforcement database identified Baird, ...
Recent CLPEX Posting Activity
containing new posts
Moderated by Steve Everist and Charlie Parker
Moderated by Steve Everist
Evidence Fabrication in South Africa
1 ... 17, 18, 19by Pat A. Wertheim on Fri Nov 30, 2007 12:48 pm 274
Replies 31344 Views Last post by Pat A. Wertheim
on Sun Aug 31, 2008 3:40 pm
Bottom Up Analysis
by Charles Parker on Sat Aug 30, 2008 10:39 pm 2 Replies 63 Views
Last post by Charles Parker
on Sun Aug 31, 2008 1:47 pm
Is Latent Print Evidence Infallible
by Big Wullie on Thu Aug 28, 2008 7:40 pm 6 Replies 178 Views Last
post by Michele
on Sun Aug 31, 2008 11:44 am
Calls for Inquiry to be scrapped
1 ... 30, 31, 32by Daktari on Tue Sep 11, 2007 7:28 am 476 Replies
41472 Views Last post by Pat A. Wertheim
on Sun Aug 31, 2008 10:28 am
Portable axial lighting kits?
by Heather Baxter on Tue Aug 26, 2008 6:49 pm 7 Replies 147 Views
Last post by Heather Baxter
on Sat Aug 30, 2008 4:49 pm
statistics and fingerprints
by Michele on Fri Aug 29, 2008 2:02 pm 0 Replies 67 Views Last post
on Fri Aug 29, 2008 2:02 pm
What's new in Print Challenges and Tech?
by L.J.Steele on Fri Aug 29, 2008 10:16 am 0 Replies 60 Views Last
post by L.J.Steele
on Fri Aug 29, 2008 10:16 am
from the known to the unknown
1, 2by Michele on Wed Aug 27, 2008 11:38 am 18 Replies 376 Views
Last post by Gerald Clough
on Fri Aug 29, 2008 9:07 am
Yet, another interesting article
by Red on Fri Aug 29, 2008 7:48 am 0 Replies 62 Views Last post by
on Fri Aug 29, 2008 7:48 am
Where's the Weekly Detail?
by Michele on Thu Aug 28, 2008 9:47 pm 1 Replies 87 Views Last post
by Pat A. Wertheim
on Fri Aug 29, 2008 6:17 am
The Lockerbie Connection.
1 ... 13, 14, 15 by Iain McKie on Wed Jun 20, 2007 11:10 am 219
Replies 43363 Views Last post by Fallible-Guy
on Thu Aug 28, 2008 1:08 pm
Fingerprint technology tackles USA cold cases
by charlton97 on Thu Aug 28, 2008 8:55 am 3 Replies 105 Views Last
post by Pat A. Wertheim
on Thu Aug 28, 2008 10:40 am
What Is A Latent Print Examination?
by Charles Parker on Tue Aug 26, 2008 4:45 pm 2 Replies 213 Views
Last post by Charles Parker
on Tue Aug 26, 2008 11:36 pm
Another Interesting Article
1, 2by Pat A. Wertheim on Sun Aug 24, 2008 8:05 am 24 Replies 639
Views Last post by Charles Parker
on Tue Aug 26, 2008 11:30 pm
Validation for Lightning Powder reference pads
by Heather Baxter on Tue Aug 26, 2008 6:52 pm 0 Replies 62 Views
Last post by Heather Baxter
on Tue Aug 26, 2008 6:52 pm
IAI Conference Topics -
Louisville, Kentucky 2008:
Moderator: Steve Everist
No new posts
Documentation issues as they apply to latent prints
Moderator: Charles Parker
No new posts
Historical topics related to latent print examination
Moderator: Charles Parker
No new posts
Updated the Fingerprint Interest Group (FIG) page
with FIG #59; Compression; submitted by Charlie Parker. You can send your example of unique distortion to
For discussion, visit the CLPEX.com forum FIG thread.
Updated the forum Keeping Examiners Prepared for
thread with KEPT #33; Evaluation: Absolute or 100%
by Michelle Triplett. You can send your
questions on courtroom topics to Michelle Triplett:
Updated the Detail Archives
we looked at the latest version of the Department of Defense, Biometrics Task
Force "Biometric Scan" newsletter, portions of which mentioned latent prints
or latent print related projects.
we look at a new 2008 book chapter on bias.
Cognitive Biases in Human Perception,
Judgment, and Decision Making: Bridging Theory and the Real World
by ITIEL E. DROR AND PETER A.
to be published in: Criminal Investigative Failures, edited by Kim Rossmo,
Scientific research into human cognition is well established by decades of
rigorous behavioral experimentation, studies of the human brain, and
computer simulations. All of these converge to provide scientific insights
into perception, judgment, and decision making (Dror & Thomas, 2005; Kosslyn
& Koenig, 1995). Many of these theoretical insights play an important role
in our understanding of how humans behave in the real world. The scientific
research has important bearings on how human perception, judgment, and
decision making can be enhanced, as well as how both lay people and experts
can (and do) make mistakes. Bridging scientific theory to the real world can
assist our understanding of human performance and error and help us evaluate
the reliability of humans. Furthermore, it has implications on how to
minimize such error through proper selection and training, best practices,
and utilizing technology (Dror, 2007, in press). In this chapter, scientific
findings about human cognition are discussed and linked to practical issues
in the real world of investigations.
We first must understand the theoretical and conceptual framework of
perception, judgment, and decision making (Lindsay & Norman, 1977; Marr,
1982; Rumelhart & McClelland, 1986). Information comes to us from the
outside world via sensory input (vision, hearing, touch, etc.). As
information is received, it is processed; for example, we try to identify
and make sense of it, interpret and assign it meaning, compare it to
information already stored in memory, and so on. One of the fundamental and
established cornerstones of human cognition is that people do not passively
receive and encode information. The mind is not a camera. We actively
interact with the incoming information in a variety of ways. What we see not
only reflects the pure and raw data from the input provided by the external
world, but it is, to a large degree, a product of how we interpret interact
and with the incoming data. Perception is far from perfection (Dror, 2005)
because our perception and judgment are influenced by a variety of cognitive
processes that are not dominated by the actual data.
In this regard, it is important to distinguish between bottom-up data-driven
processes versus top-down processes that are guided and driven by factors
distinct from the actual data provided by the external world. The existence
and power of such top-down processes in shaping the identification of visual
and other patterns has been demonstrated time and again in a number of
different studies using a variety of different scientific methodologies, all
confirming subjective effects on perception and judgment (e.g., Balcetis &
Dunning, 2006; Humphreys, Riddoch, & Price, 1997; McClelland & Rumelhart,
1981; Zhaoping & Guyader, 2007). Top-down influences include, among other
things, contextual information, expectation, what we already know (or think
we know), hope, motivation, and state of mind. Although top-down processing
is essential for human cognition and is a sign of expertise, it can also
interfere and contaminate our perception, judgment, and decision-making
processes. These biases and distortions arise from a long and well-studied
list of cognitive and psychological phenomena (e.g., Evans, 1989; Gilovich,
Griffin, & Kahneman, 2002; Hogarth, 1980; Kahneman, Slovic, & Tversky, 1982;
Nickerson, 1998; Nisbett & Ross, 1980). These well-established cognitive and
psychological phenomena (e.g., confirmation bias, cognitive dissonance,
self-fulfilling prophecies, motivated reasoning, hindsight bias, escalation
of commitment, etc.) cause people to lose objectivity.
Subjectivity arises when we no longer examine data purely by itself,
evaluating it on its own merit without cognitive influences. When we examine
information in light of such influences, we unavoidably and unconsciously
perceive and judge it differently. When cognitive biases exist, we interact
differently and subjectively with the information. This is manifested in a
variety of ways. For example, during our examination of the data we are more
likely to notice and focus on characteristics that validate and conform to
extraneous information or context, a belief or a hope. Thus, the way we
search and allocate attention to the data is selective and biased.
Confirming data are emphasized and weighted highly, and when data quality is
low (and therefore ambiguous and open to different interpretation), the
existence of an extraneous influence will make people interpret the data in
ways that are consistent with them. We tend to avoid and ignore data that
conflict and contradict such biases and disconfirm data that we notice are
ignored. Finally, data that do not fit the bias or context and cannot easily
be ignored are dismissed and explained away, and weighting of disconfirming
data is low.
These and other manifestations of bias and cognitive influences can make
perception, judgment, and decision making unreliable. They are well
researched and documented by many scientific studies (e.g., Balcetis &
Dunning, 2006; Cordelia, 2006; Ditto & Lopez, 1992; Edwards & Smith, 1996;
Evans, 1989; Gilovich et al., 2002; Haselton, Nettle, & Andrews, 2005;
Hogarth, 1980; Kahneman et al., 1982; Koriat, Lichtenstein, & Fischhoff,
1980; Kunda, 1990; Nickerson, 1998; Nisbett & Ross, 1980; Tversky & Kahneman,
1974; Zhaoping & Guyader, 2007). The criminal justice system, for example,
has in many ways adopted and taken on board these and other cognitive and
psychological findings to improve investigations (e.g., Ask & Granhag, 2005;
Risinger & Loop, 2002; Stelfox & Pease, 2005). A clear case is the way in
which line-ups are conducted. Rather than biasing eyewitnesses by presenting
them with the suspect (the target), eyewitnesses are presented with a range
of targets that include the suspect as well as numerous decoys. The line-up
procedures have been drastically improved by taking into account issues of
bias and other cognitive and psychological influences (e.g., Charman &
Wells, 2006; Turtle, Lindsay, & Wells, 2003; Wells & Olson, 2003). In this
chapter we present cognitive theory and bridge it to practical situations in
the real world of investigations. Of course, within the scope of this
chapter we can only bring examples, as illustrations, to convey the complex
issues at hand.
Initial Impressions and Accountability
Research indicates that early impressions have considerable influence on our
final evaluations. Indeed, it is common for people to maintain preexisting
beliefs despite dissonant or even contradictory evidence. Nisbett and Ross
(1980) describe the phenomenon as belief perseverance. It has been
demonstrated in many areas, including problem solving (Luchins, 1942), and
attitudes to change, as well as stereotype perseverance (Allport, 1954;
Hamilton, 1979). Tetlock (1983) provides an example of one such study. In
his experiment, participants viewed evidence from a criminal case and then
assessed the guilt of a defendant. The information provided was identical in
content; however, the order of the presented information was manipulated
between participants. The results showed that the participants who were
given the prosecution evidence first were more likely to find the defendant
guilty than the participants who were given the evidence for defense first.
Interestingly, this effect disappeared when participants were initially told
that they were expected to justify their decision or that they would be held
accountable for their decision. However, if the participants were shown the
information and were only told afterward that they would have to justify
their decision, then the order effect persisted. This suggests that our
judgments are strongly influenced by initial information. Furthermore,
influences and effects prior to information collection appear to strongly
affect the way the information is perceived and interpreted, and hence how
it is remembered and judged. All of this is further influenced by issues of
During the early 1990s, it was generally considered that the police were
immune from their actions when they were engaged in the detection and
suppression of crime. Indeed, in the case of Hill v. Chief Constable of West
Yorkshire (1989), the mother of one of the victims of the Yorkshire Ripper
sought damages in response to the police’s failure to apprehend Peter
Sutcliffe prior to the murder of her daughter. The House of Lords found that
no duty of care arose where there is no special relationship between the
victim of crime and the police, and as a result there is no liability in
negligence. Moreover, it was considered dangerous as it diverted police
resources from fighting crime. However, the cost of error has been shown to
increase accuracy in judgment and reduce the effect of biasing factors such
as order effects, ethnic stereotyping, and anchoring (Freund, Kruglanski, &
Shpitzajzen, 1985; Kruglan-ski & Freund, 1983). However, it also increases
deliberation time (McAllister, Mitchell, & Beach, 1979). Indeed, Kunda
(1990) argues that accuracy is a product of deeper processing, resulting
from accuracy motives that affect the initial encoding and processing of
information. Tetlock (1983, 1985) showed that accuracy-promoting
manipulations reduce bias when they are delivered before information
presentation, but not after.
Time pressures can increase biasing effects (Freund et al., 1985; Kruglanski
& Freund, 1983), perhaps because information selectivity is higher and
decision criteria thresholds are lower (Dror, Busemeyer, & Basola, 1999).
Although accuracy motivation through accountability appears to increase the
quality of decision making, in several studies the biases are not entirely
eliminated (Fischhoff, 1977; Kahneman & Tversky 1972; Lord, Lepper, &
Preston, 1984; Tversky & Kahneman, 1973). These, as well as other biasing
countermeasures, most often reduce and minimize bias but do not eliminate it
altogether. Accountability plays a major role in a variety of domains that
rely on perception, judgment, and decision making, for example, in the
perception of risk and the decision to use force by police (Dror, 2008). In
sum, it appears that initial impressions and preconceptions can bias our
perception and judgment, which can be detrimental to achieving high-quality,
evidence-based decisions. This problem can be reduced by accountability and
the cost of error; however, it is never entirely eliminated, and time
pressure in particular has a detrimental effect on the ability to ignore
biasing factors. It is important to note that these biasing effects are
examples of honest mistakes brought about by our cognitive build, which
affect us all and are not representative of a conscious, malicious desire to
draw one conclusion over another. On the contrary, many times the motivation
to “help” and solve a case, to “do justice,” clouds our judgments and our
ability to reach objective conclusions.
The tendency to confirm an initial theory or preconception and avoid
disconfirming information is known as confirmation bias. An example of this
is demonstrated by Wason’s (1960) selection task. Participants were given a
three-number sequence that followed a certain rule. They were required to
deduce this rule by proposing potential sequences. They were then given
feedback as to whether their proposed sequences followed the rule. The rule
was simply “any ascending sequence,” yet the rules suggested by participants
were generally far more complex. Participants appeared to formulate a
potential rule and then only generate sequences that conformed to their
rule. If enough sequences were accepted, then the theory would be accepted.
Surprisingly, participants tended not to try to falsify their theories.
This phenomenon has also been observed in other areas. We often appear to
prefer information that is biased toward previously held beliefs, desired
outcomes, or expectations (Jonas, Schulz-Hardt, Frey, & thelen, 2001) or
appear to support our expectations in negotiations (Pinkley, Griffth, &
Northcraft, 1995), our outlooks and attitudes (Lundgren & Prislin, 1998),
our self-serving conclusions (Frey, 1981), or our social stereotypes
(Johnston, 1996). Our mind does not seem to be designed to optimize and find
the perfect solution to any given problem. Instead, it merely aims to feel
sufficiently satisfied with a solution (Simon, 1956, 1982). Therefore,
decision makers have a criterion level, a threshold that must be met before
a conclusion can be reached. Once this threshold has been reached, it is a
winner takes all process in which a final and decisive decision is reached (Dror
et al., 1999). Investigators will search for and process information until
this threshold is reached (Busemeyer & Townsend, 1993; Nosofsky & Palmeri,
1997; Ratcliff& Smith, 2004). Moreover, decision factors such as time
pressure can influence this threshold level (Dror et al., 1999).
In the investigative process this means that once a conclusion is
reached-for example, who committed the crime—it is cognitively adopted.
Additional information is then gathered to confirm the decision (for
example, build the best case possible against the person believed to have
perpetrated the crime). At this stage, all information is weighted in a
biasing context, which means, for example, that information proving the
innocence of the person may be ignored or explained away. This is in
addition to the problem that the initial determination can be biased because
of preconceptions, initial theory, contextual evidence, or even just a
hunch. It is quite possible for the initial theory to only be corroborated
by confirmatory investigative search patterns and never be truly challenged.
this chain of cognitive influences may render the investigative conclusions
questionable, if not altogether unreliable.
Forensic Examination: We See What We Expect to See
Interestingly, initial information affects how we perceive visual
information as well as facts and figures. Bruner and Potter (1964) provided
participants with blurred images that were gradually brought into focus. If
the image was initially extremely blurry, it was harder for participants to
finally identify the image, even when it was fully brought into focus, than
if it began less blurry. People who use weak evidence to form initial
hypotheses have difficulty correctly interpreting subsequent, more detailed,
information. this has implications for a wide range of forensic evidence,
such as fingerprints and closed-circuit television images, where initial
information can be of low quality. Top-down processing uses past knowledge,
current emotional state, and/or expectations to facilitate perception and
judgment, resulting in faster but more subjective impressions. An example of
this is waiting for a friend in a crowd and mistaking a stranger for the
friend. In this case, our expectations cause us to interpret visual
information in a certain way, and what we see conforms to our expectations.
Dror and Rosenthal (2008) established that expert forensic examiners can
have their judgments biased by extraneous contextual information (see also
Dror & Charlton, 2006; Dror, Charlton, & Peron, 2006; Dror, Peron, Hind, &
Charlton, 2005). In a number of studies, fingerprint experts were asked to
compare prints that had been presented in a biased context. The circumstance
affected their judgments, resulting in most of the examiners reaching
differing conclusions on identical prints that had been presented within
differing contexts. the visual information was processed in a way that
conformed to their expectations.
These effects were not due to the experts having varying philosophies,
training, or procedures because the conflicting conclusions were reached by
the same experts on the same prints; the only difference was the context in
which the prints were presented. Indeed, such biases occurred in the
investigation of the 2004 Madrid train bombings. Brandon Mayfield’s
fingerprints were alleged to have been identified against those found on a
bag of detonators found in Spain. A senior fingerprint expert from the FBI
matched the latent print from the crime scene to Mayfield, who was a Muslim
convert and had a military background (see Figure 5.1). The identification
was further verified by two additional senior FBI fingerprint experts. Even
an independent expert appointed by the court on behalf of the defense
matched the print to Mayfield. All experts concluded with 100% certainty
that the latent print was Mayfield’s (see Stacey, 2004). After the incorrect
identification was exposed by coincidence, the FBI’s report on this error,
as well as a report by the U.S. Department of Justice’s Offce of the
Inspector General, concluded that circular reasoning and confirmation bias
played a role in the erroneous identification.
Motivation is another element that can introduce bias. Charlton, Dror, and
Fraser-Mackenzie (2008) highlighted the potential of motivational bias in a
study in which they interviewed forensic examiners to explore motivational
and emotional experiences in routine and high-profile cases. Examiners
reported a heightened emotional state both during the search for and on the
finding of a match, especially during serious and high-profile cases. For
example: “that [the feeling] was, that was great, I mean, to be involved in
such a high profile case and finally get a match” and “oh it’s a buzz. It’s
a definite buzz. … When you get one, especially from the search, the buzz is
there” (Charlton et al., 2008).
Figure 5.1 Print A on the left belongs to Brandon Mayfleld. Print B on the
right was found at the crime scene.
The research suggests that this could quite possibly have contributed to the
erroneous matching of Brandon Mayfield’s prints. Such failures may be more
likely in serious, high-profile cases than in high-volume, day-to-day
crimes. Moreover, such crimes carry the heaviest penalties and thus the
greatest cost of making an error. Indeed, the Menezes Case highlights this
The Menezes Case: Context Can Kill
On July 22, 2005, Jean Charles de Menezes, an innocent man, was shot dead at
Stockwell Station on the London Underground because he was incorrectly
identified as a suicide bomber (see Figure 5.2). His housing complex was
under police surveillance because Hussain Osman, suspected of being a
potential suicide bomber, lived there. As Menezes left his home, he was
followed by police officers who thought he may be their suspect, Osman.
Menezes took a bus to a tube station, where he was observed getting off the
bus and then getting on another bus. the surveillance team interpreted his
actions as an attempt to lose them, when in fact he was going to another
tube station only because this one was closed. At Stockwell Station, he
boarded a train that had pulled up to the platform. Offcers were convinced
that he was a suicide bomber and shot him numerous times.
Initial contextual information suggested that Menezes could be the terror
suspect. Subsequent neutral information and even disconfirming information
was present but appears to have been processed incorrectly. Furthermore, the
potential threat of a suicide bombing on a crowded Underground would have
induced stress and time pressure. Stressors such as time pressure can affect
our decision-making threshold (Dror et al., 1999) as well as increase the
biasing effect of erroneous initial information (Freund et al., 1985;
Kruglanski & Freund, 1983). Many people will be surprised to learn such
mistakes can happen; however, for cognitive experts, it is clear why such
errors are made, especially when police officers do not receive proper
training on cognitive issues.
Figure 5.2 Photograph A on the left is of Jean Charles de Menezes.
B on the right is of Hussain Osman.
The Presentation of Evidence and Emotional Effects
Due to the importance of information context and framing, it follows that
the presentation of evidence is vital. The impression of forensic evidence
is that it is infallible, scientifically proven, undeniable truth. It
therefore has considerable impact on judges and juries. For instance, Sir
Roy Meadow’s evidence in the Sally Clark sudden infant death case suggested
that the chance of Sally Clark having two sudden infant deaths in the family
was one in 73 million (see Chapter 4). The probability of a sudden infant
death is 1 in 8,543, and Meadows simply squared this value to calculate the
probability of two sudden infant deaths in the same household.
Statistically, however, this would only be valid if both cases were
independent of each other. The findings of a sudden infant death gene
rendered the evidence invalid. Nevertheless, the expert evidence had great
impact on the case. Forensic evidence in particular is seen under this
golden halo effect when in reality “there can be genuine disagreement
between forensic scientists just as there can be disagreement between
nuclear physicists or art historians” (Roberts & Willmore, 1993).
The presentation of erroneous information not only biases judgments, but
seemingly innocuous changes in the way evidence is presented during a trial
can have dramatic outcomes on the verdict. For example, descriptions of a
psychiatric patient might affect expert forensic psychologist’s and
psychiatrist’s evaluations of whether the patient should be released from a
hospital. These descriptions can either be given in frequency terms (e.g.,
“of every 100 patients similar to Mr. Jones, ten are estimated to commit an
act of violence to others”) or in statistical terms (e.g., “patients similar
to Mr. Jones are estimated to have a 10% chance of committing an act of
violence to others”). Research revealed that clinicians who were given such
information in frequency terms labeled the patient as being more dangerous
than when the same information was presented in statistical terms (Slovic,
Monahan, & MacGregor, 2000). Thus, it appears as though alternative ways in
which information can be represented, which have no logical or numerical
difference, can result in different judgments. This suggests that in some
cases, and perhaps more than we are aware, it is not the information itself
that is important as much as how it is packaged and processed by the human
An important determinant of how we package information is our emotional
state. Research has suggested that the interpretation and selection of
information can be greatly influenced by affect. For example, the processing
of facial expressions corresponds to the emotional state of the perceiver (Niedenthal,
Halberstandt, Margolin, & Innesker, 2000; Shiffenbauer, 1974). Even
lexically ambiguous sounds are interpreted in a way that conforms to the
person’s own emotional state (Pincus, Pearce, & Perrott, 1996). This
demonstrates that a person’s internal context affects how information is
perceived and judged, as well as the decision making that follows.
Research by Zajonc (1980, 1984a, 1984b), Bargh (1984), and LeDoux (1996)
shows that affective reactions to stimuli are often more basic than
cognitive evaluations (Loewenstein, Weber, Hsee, & Welch, 2001). However,
these very processes can be responsible for the erroneous processing of
information. Therefore, the emotional context of an investigation could
potentially influence the processing of evidence and investigative decision
Logic versus Believability
Despite all the research described above, it might still be argued that we
can use logical reasoning to override such cognitive and psychological
biases. For example, investigators could be made aware of these issues and
be asked to keep an open mind, listen only to the facts, free themselves
from bias, prejudice, and sympathy, and remain uninfluenced by preconceived
ideas and extraneous information. Unfortunately, even logical reasoning is
not immune to psychological effects. Evans, Barston, and Pollard (1983)
attempted to compare directly the extent to which context and past knowledge
interfere with logical thought in simple reasoning tasks. In their
experiment, they gave participants statements and conclusions that were
either believable or unbelievable and either valid or invalid by logic and
reasoning. Participants were asked to decide whether they agreed with the
conclusions, using only strict logic and reasoning. Table 5.1 shows how
participants were more inclined to support believable conclusions and ignore
logic and reasoning.
Table 5.1 Evidence of Belief Bias in Syllogisms with Percentage of
Acceptance of Conclusions as Valid
Logically Valid and Believable 89%
Logically Valid but Unbelievable 56%
Logically Invalid but Believable 71%
Logically Invalid and Unbelievable 10%
Source: Evans, Barston, & Pollard, 1983.
It appears that people use past experience more so than logic and
rationality to guide their decision making. These systematic deviations from
logic are unavoidable cognitive performance restrictions and errors
(Johnson- Laird & Byrne, 1991; Kahneman et al., 1982; Oaksford, & Chater,
2001; Rips, 1994). People avoid cognitively taxing processes, preferring the
faster and less cognitively involved process of relying on what is
believable. Police often encounter inaccurate information presented as fact,
for example, conscious misdirection by a guilty party or erroneous evidence
from a witness. Accordingly, to the investigator or examiner, the
believability heuristic is forefront in their cognitive processing.
In this chapter, we discussed the influence of extraneous contextual
information on data. Scientific research as well as actual cases (such as
the Brandon Mayfield and Menezes incidents) have demonstrated time and again
how cognitive bias can cause errors in real world situations. Our minds are
not designed to optimize, and it is important to ensure that we have reached
a correct conclusion instead of just adopting a “satisfactory” solution.
Changes have already occurred in the investigative profession. Dixon (1999)
found that detectives who arrest on a hunch or give weak cases “a run” have
less status than those who collect conclusive evidence prior to making an
arrest. However, many forensic examiners and police officers have not
received proper training in cognitive biases, and appropriate procedures and
best practices to deal with these issues are needed. Although it is
impossible to avoid the influence of extraneous factors on our perception,
judgment, and decision making, there is plenty of room to drastically reduce
such biases (Dror, in press).
Allport, G. W. (1954). fie nature of prejudice. Reading MA: Addison Wesley.
Ask, K., & Granhag, P. A. (2005). Motivational sources of confirmation bias
in criminal investigations: the need for cognitive closure. Journal of
Psychology and Oflender Proffling, 2, 43–63.
Balcetis, E., & Dunning, D. (2006). See what you want to see: Motivational
influences on visual perception. Journal of Personality and Social
Psychology, 91, 612–625.
Bargh, J. A. (1984). Automatic and conscious processing of social
information. In R. S. Wyer & T. K. Srull (Eds.), Handbook of social
cognition (Vol. 3, pp. 1–43). Hillsdale, NJ: Erlbaum.
Bruner, J., & Potter, M. (1964). Inference in visual recognition, Science,
Busemeyer, J. R., & Townsend, J. T. (1993). Decision field theory: A
dynamic-cognitive approach to decision making in an uncertain environment.
Psychological Review, 100, 432–459.
Charlton, D., Dror, I. E., & Fraser-Mackenzie, P. A. F. (2008). A
qualitative study investigating the emotional rewards and motivating factors
associated with forensic ffngerprint analysis. Technical report, University
of Southampton, School of Psychology, Southampton, UK.
Charman, S. D., & Wells, G. L. (2006). Applied lineup theory. In R. C. L.
D. F. Ross, J. D. Read, & M. P. Toglia (Eds.), Handbook of eyewitness
psychology: Memory for people (pp. 219–254). Mahwah, NJ: Lawrence Erlbaum.
Cordelia, F. (2006). A mind of its own: How your brain distorts and
deceives. Cambridge, UK: Icon Books.
Ditto, P. H., & Lopez, D. F. (1992). Motivated skepticism: Use of
differential decision criteria for preferred and nonpreferred conclusions.
Journal of Personality and Social Psychology, 63, 568–584.
Dixon, D. (1999). Police investigative procedures: Changing legal and
political contexts of policing practices. In C. Walker & K. Starmer (Eds.),
Miscarriages of justice: A review of justice in error (pp. 65–82). Oxford:
Oxford University Press.
Dror, I. E. (2005). Perception is far from perfection: the role of the brain
and mind in constructing realities. Brain and Behavioural Sciences, 28, 763.
Dror, I. E. (2007). Land mines and gold mines in cognitive technologies. In
I. E. Dror (Ed.), Cognitive technologies and the pragmatics of cognition
(pp. 1–7). Amsterdam: John Benjamin Press.
Dror, I. E. (2008). Perception of risk and decision to use force. Policing,
Dror, I. E. (in press). How to manage cognitive biases. Forensic sciences
policy and management.
Dror, I. E., Busemeyer, J. R., & Basola, B. (1999). Decision making under
time pressure: An independent test of sequential sampling models. Memory and
Cognition, 27, 713–725.
Dror, I. E., & Charlton, D. (2006). Why experts make errors. Journal of
Forensic Identification, 56, 600–616.
Dror, I. E., Charlton, D., & Peron, A. (2006). Contextual information
renders experts vulnerable to making erroneous identifications. Forensic
Science International, 156, 74–78.
Dror, I. E., Peron, A., Hind, S., & Charlton, D. (2005). When emotions get
the better of us: the effect of contextual top-down processing on matching
fingerprints. Applied Cognitive Psychology, 19, 799–809.
Dror, I. E., & Rosenthal, R. (2008). Meta-analytically quantifying the
reliability and biasability of forensic experts. Journal of Forensic
Sciences, 53, 900–903.
Dror, I. E., & thomas, R. D. (2005). the cognitive neuroscience laboratory:
A framework for the science of the mind. In C. Erneling & D. Johnson (Eds.),
the mind as a scientific object: Between brain and culture (pp. 283–292).
Oxford: Oxford University Press.
Edwards, K., & Smith, E. E. (1996). A disconfirmation bias in the evaluation
of arguments. Journal of Personality and Social Psychology, 71, 5–24.
Evans, J. St. B. T. (1989). Bias in human reasoning: Causes and
consequences. Hills-dale, NJ: Erlbaum.
Evans, J. St. B. T., Barston, J. L., & Pollard, P. (1983). On the conflict
between logic and belief in syllogistic reasoning. Memory and Cognition, 11,
Fischhoff, B. (1977). Perceived informativeness of facts. Journal of
Experimental Psychology: Human Perception and Performance, 3, 349–358.
Freund, T., Kruglanski, A. W., & Shpitzajzen, A. (1985). the freezing and
unfreezing of impressional primacy: Effects of the need for structure and
the fear of invalidity.
Frey, D. (1981). the effect of negative feedback about oneself and the cost
of information on preferences for information about the source of this
feedback. Journal of Experimental Social Psychology, 17, 42–50.
Gilovich, T., Griffn, D., & Kahneman, D. (2002). Heuristics and biases: fie
psychology of intuitive judgment. New York: Cambridge University Press.
Hamilton, D. L. (1979). A cognitive attributional analysis of stereotyping.
In L. Berkowitz (Ed.), Advances in experimental social psychology (Vol. 12,
pp. 53–84). New York: Academic Press.
Haselton, M. G., Nettle, D., & Andrews, P. W. (2005). the evolution of
cognitive bias. In D. M. Buss (Ed.), Handbook of evolutionary psychology
(pp. 724–746). Hoboken, NJ: Wiley.
Hill v. Chief Constable of West Yorkshire (1989) 1 AC 53.
Hogarth, R. (1980). Judgement and choice. New York: John Wiley.
Humphreys, G. W., Riddoch, M. J., & Price, C. J. (1997). Top-down processes
in object identification: Evidence from experimental psychology,
neuropsychology, and functional anatomy. Philosophical Transactions of the
Royal Society, London, 352, 1275–1282.
Johnson-Laird, P. N., & Byrne, R. M. J. (1991). Deduction. Hillsdale, NJ:
Johnston, L. (1996). Resisting change: Information-seeking and stereotype
change. European Journal of Social Psychology, 26, 799–825.
Jonas, E., Schulz-Hardt, S., Frey, D., & thelen, N. (2001). Confirmation
bias in sequential information search after preliminary decisions: An
expansion of dissonance theoretical research on “selective exposure to
information.” Journal of Personality and Social Psychology, 80, 557–571.
Kahneman, D., Slovic, P., & Tversky, A. (1982). Judgment under uncertainty:
Heuristics and biases. Cambridge: Cambridge University Press.
Kahneman, D., & Tversky, A. (1972). Subjective probability: A judgment of
representativeness. Cognitive Psychology, 3, 430–454.
Koriat, A., Lichtenstein, S., & Fischhoff, B. (1980). Reasons for
confidence. Journal of Experimental Psychology: Human Learning and Memory,
Kosslyn, S. M., & Koenig, O. (1995). Wet mind: fie new cognitive
neuroscience. New York: Free Press.
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, 448–468.
Kunda, Z. (1990). the case for motivated reasoning. Psychological Bulletin,
LeDoux, J. (1996). fie emotional brain. New York: Simon and Schuster.
Lindsay, P. H., & Norman, D. A. (1977). Human information processing. New
York: Academic Press.
Loewenstein, G. F., Weber, E. U., Hsee, C. K., & Welch, E. S. (2001). Risk
as feelings. Psychological Bulletin, 127, 267–286.
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.
Luchins, A. S. (1942). Mechanisation in problem solving: the effect of
Einstellung. Psychological Monographs, 54, 1–95.
Lundgren, S. R., & Prislin, R. (1998). Motivated cognitive processing and
attitude change. Personality and Social Psychology Bulletin, 24, 715–726.
Marr, D. (1982). Vision. New York: W. H. Freeman.
McAllister, D. W., Mitchell, T. R., & Beach, L. R. (1979). the contingency
model for the selection of decision strategies: An empirical test of the
effects of significance, accountability, and reversibility. Organizational
Behavior and Human Performance, 24, 228–244.
McClelland, J. L., & Rumelhart, D. E. (1981). An interactive activation
model of context effects in letter perception: Part 1. An account of basic
findings. Psychological Review, 88, 375–407.
Nickerson, R. S. (1998). Confirmation bias: A ubiquitous phenomenon in many
guises. Review of General Psychology, 2, 175–220.
Niedenthal, P. M., Halberstandt, J. B., Margolin, J., & Innes-ker, A. H.
(2000). Emotional state and the detection of change in facial expressions of
emotion. European Journal of Social Psychology, 30, 211–222.
Nisbett, R. E., & Ross, L. D. (1980). Human inference: Strategies and
shortcomings of social judgment. Englewood Cliffs, NJ: Prentice-Hall.
Nosofsky, R. M., & Palmeri, T. J. (1997). An exemplar based random walk
model of speeded classification. Psychological Review, 104, 266–300.
Oaksford, M., & Chater, N. (2001). the probabilistic approach to human
reasoning. Trends in Cognitive Sciences, 5, 349–357.
Pincus, T., Pearce, S., & Perrott, A. (1996). Pain patients’ bias in the
interpretation of ambiguous homophones. British Journal of Medical
Psychology, 69, 259–266.
Pinkley, R. L., Griffth, T. L., & Northcraft, G. B. (1995). “Fixed pieffa la
mode: Information availability, information processing, and the negotiation
of suboptimal agreements. Organizational Behavior and Human Decision
Processes, 62, 101–112.
Ratcliff, R., & Smith, P. L. (2004). A comparison of sequential sampling
models for two-choice reaction time. Psychological Review, 111, 333–367.
Rips, L. (1994). fie psychology of proof. Cambridge, MA: MIT Press.
Risinger, D. M., & Loop, J. L. (2002). three card monte, Monty Hall, modus
operandi and “offender profiling”: Some lessons of modern cognitive science
for the law of evidence. Cardozo Law Review, 24, 193–285.
Roberts, P., & Willmore, C. (1993). the role of forensic science evidence in
criminal proceedings. Royal Commission on Criminal Justice Research, Study
No 11. London: HMSO.
Rumelhart, D. E., & McClelland, J. L. (1986). Parallel distributed
processing: Explorations in the microstructure of cognition. Cambridge, MA:
Shiffenbauer, A. (1974). Effect of observer’s emotional state on judgments
of the emotional state of others. Journal of Personality and Social
Psychology, 30, 31–35.
Simon, H. A. (1956). Rational choice and the structure of the environment.
Psychological Review, 63, 129–138.
Simon, H. A. (1982). Models of bounded rationality. Cambridge, MA: MIT
Slovic, P., Monahan, J., & MacGregor, D. G. (2000). Violence risk assessment
and risk communication: the effects of using actual cases, providing
instruction, and employing probability versus frequency formats. Law and
Human Behavior, 24, 271–296.
Stacey R. B. (2004). Report on the erroneous fingerprint individualization
in the Madrid train bombing case. Journal of Forensic Identiffcation, 54,
Stelfox, P., & Pease, K. (2005). Cognition and detection: Reluctant
bedfellows? In M. J. Smith & N. Tilley (Eds.), Crime science: New approaches
to preventing and detecting crime (pp. 191–207). Cullompton, Devon: Willan.
Tetlock, P. E. (1983). Accountability and the perseverance of first
impressions. Social Psychology Quarterly, 46, 285–292.
Tetlock, P. E. (1985). Accountability: A social check on the fundamental
attribution error. Social Psychology Quarterly, 48, 227–236.
Turtle, J. W., Lindsay, R. C. L., & Wells, G. L. (2003). Best practice
recommendations for eyewitness evidence procedures: New ideas for the oldest
way to solve a case. Canadian Journal of Police and Security Services, 1,
Tversky, A., & Kahneman, D. (1973). Availability: A heuristic for judging
frequency and probability. Cognitive Psychology, 5, 207–232.
Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics
and biases. Science, 185, 1124–1131.
Wason, P. C. (1960). On the failure to eliminate hypotheses in a conceptual
task. Quarterly Journal of Experimental Psychology, 12, 129–140.
Wells, G. L., & Olson, E. (2003). Eyewitness identification. Annual Review
of Psychology, 54, 277–295.
Zajonc, R. B. (1980). Feeling and thinking: Preferences need no inference.
American Psychologist, 35, 151–175.
Zajonc, R. B. (1984a). the interaction of affect and cognition. In K. R.
Scherer & P. Ekman (Eds.), Approaches to emotion (pp. 239–246). Hillsdale,
Zajonc, R. B. (1984b). On primacy of affect. In K. R. Scherer & P. Ekman
(Eds.), Approaches to emotion (pp. 259–270). Hillsdale, NJ: Erlbaum.
Zhaoping, L., & Guyader, N. (2007). Interference with bottom-up feature
detection by higher-level object recognition. Current Biology, 17, 26–31.
- Keeping Examiners Prepared for Testimony - #32
Evaluation: Absolute or 100% Certain?
by Michele Triplett, King County
The intent of this is to provide thought provoking discussion.
No claims of accuracy exist.
Absolute or 100% Certain:
How certain are you that this latent print was left by
this known print?
I have no way of determining a numerical value for
my certainty level. The visual
evidence and the careful use of scientific protocols lead me to arrive at
only one conclusion. This
conclusion has been reviewed and no other possibility was found.
The ground truth can’t be determined but we can
reasonably establish it by using accepted principles, good quality assurance
measures, and leaving our conclusions open for review and scrutiny by
Any answer for this question is highly subjective.
There may be no right or wrong answers just different points of view.
These answers are given only to help people see different view
Answers a and b:
It’s important to understand the difference between measuring a
confidence level and measuring the accuracy of a conclusion.
100% confident isn’t the same as 100% accurate.
Juries or attorneys may misinterpret confidence levels for accuracy
rates. If this is done then it
may appear that you’re overstating the accuracy of fingerprint results.
In addition, some people discourage using numbers to describe a
confidence level or an accuracy rate because it’s impossible to determine
how you arrived at that number.
Answers c and d:
Some people recommend that you state results in the positive rather
than the negative. Instead of
saying that you have no way of determining a numerical number, you could say
that when scientific protocols are used carefully then the error rate is
extremely low, very close to zero.
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