1. The document discusses the debate around whether intelligence analysis should be considered an art or a science. It argues that intelligence analysis is best viewed as a balance of both artistic intuition and scientific processes. 2. Technological advances can both help and hinder intelligence analysis. While new technologies allow for more precise analysis, they also risk discouraging creative thinking and questioning if relied on too heavily. 3. To maximize the benefits of technology, intelligence analysis needs to maintain an artistic approach that encourages questioning, looking at scenarios from different perspectives, and understanding the human factors involved. A balanced, intuitive approach combined with new data sources has the potential to improve intelligence analysis.

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Intelligence Analysis Encounters a Technological Aspect that can both Deter and
Encourage Best Practices
Aaron Csik
The vast world interest in technological advances creates extreme attention to a
resource that can improve practice if the origination of the question remains more so
intuitive rather than calculated. Intelligence analysis will constantly fight criticism as a
science because it lacks the systematic background of the study of medicine1. While
intelligence analysis seems to work best when it combines a delicate balance of artful
intuition with the scientific process, the criticisms are mainly against the scientific
imperfections2. The opportunity of intelligence analysis is great, especially as best
practices continue to be refined. The similarities between intelligence analysis and
medical diagnosis are well documented; however, intelligence analysis continually has
to prove its worth scientifically when its success is almost equally based on the artistic
interpretation of scientific tools and information3. This notion may hamper the ability of
intelligence analysis to be generally accepted as a clear-cut scientific practice; and will
simultaneously help reinforce certain intelligence viewpoints on the value of art in
intelligence.
To clarify the scope of intelligence analysis, it is best to describe the particular
angle of intelligence referred to in this paper, as well as the role consumers of
intelligence play in the use of intelligence. This paper is not solely looking at the
procedure of intelligence analysis: Collecting, analyzing, deducing, and testing. Rather,
it refers to the entire process of intelligence; the one that receives certain diplomatic
approval almost every step of the way4. It also involves the intuitive process that is

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necessary for good intelligence. Intelligence analysis is indeed the process of collecting,
analyzing, and physically acting on intelligence. However, its job is to aid in facilitating
the demands of the consumer5,6.
One cannot completely rule out intelligence analysis as a science because of its
academic and practical use of scientific processes. Intelligence requires free thought;
however, one cannot adequately reason unless he or she has a relatable framework to
work the process through7. Analysts use the analytic process to narrow down and rule
out alternate hypotheses. Therefore, a practitioner can rule out certain observations that
lead to an appropriate and “best” hypothesis8. It is vaguely accepted that intelligence
analysis needs both judgment and some structure; however, constant disagreement on
what to emphasize more holds the conversation from revolutionizing the idea9.
As stated, the art versus science debate about intelligence analysis does not
result in a winner. Logically, intelligence analysis cannot be considered a perfect
science, as it’s not ritualistic, and not always quantitative. The environments are rarely
controllable, and there is rarely such thing as a true experiment10. The spearheads of
intelligence as an art make sure to claim that analysts are held to unfair standard
regarding accuracy, as no artistic interpreation in intelligence is able to be “perfect”11.
Another common denominator in the debate of art versus science is the age and
experience of the analyst. Whereas a young analyst might think of intelligence analysis
as a scientific process to be done with pinpoint accuracy, an experienced analyst
alludes to pattern recognition and a constantly adapting intuition to completing the task
at hand12. The seemingly appropriate answer is that intelligence analysis is both an art

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and a science. It is a delicate balance of the two that must be originally reasoned for
each situation.
Intelligence analysis is a practice that works entirely within the diplomatic scope
of authority granted to it. As policymakers rarely have minutes to spare when receiving
information from an analyst, the burden of confidence in the relationship lies almost
solely on the intelligence analyst13. Analysts must also present information that the
consumer easily comprehends and shares interests with. A policymaker’s job is almost
always dealing with people; therefore, an analyst needs to describe information
highlighting the importance of interactions – stressing the importance of how the
physical person to person relationships will benefit the situation14. Former CIA senior
officer James McCullough remarks on information sharing between the intelligence
community saying that changes in political dynamics do not actually influence more
information sharing. This is because analysts still think in terms of intelligence,
policymakers think in terms of relations, and the intersection of these two are the only
ones who change their policies, resulting in little change15.
National security and medical diagnoses both require an artistic and scientific
sense. While one must have the expertise in the specific area of knowledge, one must
also use prior experiences and intuition to most accurately assess a scenario16. The
negative connotation attached to thinking outside-the-box, resulting from technological
accuracy, is the major dilemma of intelligence analysis. Hard questions require an
incredible amount of work, time, and thought; however, the right information is always
better than the most information. Working in analytic frameworks increases the chances
of constricting abstract thought17. This makes technology an enemy of artistic

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intelligence analysis. As programs make things “easier” and efficient, they
systematically shut down the creative thoughts that make sense of the framework. This
causes analysts, students, and consumers to only see the results of an incomplete
reasoning, creating intelligence’s most inconspicuous dilemma18.
The similarities between intelligence analysis and medical diagnosis and their
similar origins make new technology and artistic approaches, when used together, the
most promising opportunity to better improve professional practice. As modern U.S.
intelligence is a relatively young practice, many opportunities exist to improve
intelligence analysis using some of the same technology that can hold it back. Whether
it is collected data or medical symptoms, new technology allows more precision to the
analysis step of the scientific method19. Using new technology helps with dispelling
alternate hypotheses and allows for a broader fact-check with the main hypothesis.
Combined with artistic collection processes and a focus on language, this helps
practitioners guide their intuitive thought using information that previously lacked
specificity. With more accuracy in analysis and an increased acceptance and
encouragement of intuitive questioning, good intelligence gathering has the ability to
broaden the intelligence-consumer information sharing practice.
A major obstacle to this utopian thought of perfectly efficient intelligence is
teaching; more specifically, the benefits of using an artistic and scientific approach to
teaching practical knowledge. Explained in the beginning of the book, How Doctors
Think, by Jerome Groopman, as professionals know more and more about a practice
throughout time, education of those practices have shifted from a “why” perspective to a
“how” perspective20. When the algorithms and specific processes are constantly

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perfected, it fails to allow the questioning of reason. The thirst for reasons helps a
student and practitioner more accurately understand the hypothesis. This hurts
intelligence analysis more than medical diagnoses because, as stated previously,
intelligence analysis is too imperfect a science. When the factors are constantly
changing, unlike a diagnosis of a particular situation, failing to constantly ask why
lowers the understanding of the uniqueness of a scenario. The immense focus on facts,
accurate calculations, and algorithmic memorization throughout education provides an
early obstacle to practitioners that will slow down the intuitive reasoning skills required
for the most efficient analysis down the road.
Intelligence analysis, even when using technology intuitively as well as
scientifically, creates its biggest limitation by backtracking to the failure to solidify a
“perfect” process. As opposed to medical diagnosis, intelligence analysis uses many
more factors, which could be changing in real-time21. The more factors involved in a
situation, the more uncertainty seems to be involved in the process. Causing
practitioners to question more is useful; however, as technology is able to identify more
variables, it will increasingly discourage the necessity in properly taking hypothetical
leaps. Framing technological advancement as a future double-edged sword in
intelligence emphasizes the importance of practitioner adaptation. Future practice will
thus only take measurable strides if the artistic approach is not only accepted, but
encouraged. Unlike medical diagnosis, an intelligence analyst may need to take into
account motive, religion, and culture, on top of factual information, to comprehend.
Collection and analysis of these non-physical variables, combined with skepticism about
intuitive approaches, may create a possible reason for the slow progress made in

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determining best processes. Like variables seem to foster biases from analysts,
affecting their artistic approach using new technology. This will limit their ability to
combine artistry and science into a unison approach to an intelligence question.
A great supporter of artistry in a field dominated by rigid inferences, Dr. Myron
Falchuk gives artistic approach advocates a sense of relief through his experience
treating Anne Dodge. He speaks about the importance of listening, questioning, and the
use of language, and how starting fresh on a problem filled with background information
can lead to discoveries where only certain pieces of information matter22. He goes on to
describe how framing a scenario in a certain direction too early can lead to consistent
failure. Instead of every symptom representing a symptom, he alludes that some
symptoms are causes, while some symptoms are effects. Thinking holistically about
why the initial symptoms exist can help frame a scientific question to a “why does
symptom X cause or interact with symptom Y? And why do these symptoms interact to
cause physical observation Z?23” Dr. Falchuk’s experiences and ideologies dramatically
increase understanding of how an analytical process should be completed combining
the right amount of intuitive questioning and scientific observations.
The release and interest in using new technologies, along with the utilization of
artistic approaches to analysis presents the most profound spectrum of intelligence in
the coming years. The need for quick and accurate hypotheses by consumers is a
constant reminder that intelligence is imperfect in nature. The stress of accurately
collecting, analyzing, testing, and presenting an intelligence question is made easiest by
asking “why” to the right pieces of information. Coupled with newer and more precise
technology, the intelligence analyst is in a more advantageous position to be as correct

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as possible. With this comes the ease of analytical tunnel-vision. Technological
excellence influences an analyst to inaccurately frame a situation based on
observations if they neglect to question the right information, abandon thinking
abstractly, and/or fail to look at the big picture through observational biases. Similarly,
technology proves beneficial to an analyst with the “accurately respective” artistic
interpretation of the particular question. Technological advances also affect the
effectiveness of teaching practices due to a more understandable interface,
discouraging the student’s instinctive notion to ask “why”. Whether in data collection,
analysis, or hypothesis formulation and testing, the prevalence of technology can
provide an unneeded crutch to an analyst’s perception of a question; however,
maintaining a well-balanced using an appropriately artistic methodology will aid in good
intelligence analysis.
References
1. Stephen Marrin, Jonathan Clemente, Improving Intelligence Analysis by Looking to
the Medical Profession, International Journal of Intelligence and
CounterIntelligence, 18:4, 2005, pg. 707-708
2. Marrin, Clemente
3. Stephen Marrin, Jonathan Clemente, Modeling an Intelligence Analysis Profession on
Medicine, International Journal of Intelligence and CounterIntelligence, 19:4,
(2006-2007)
4. Stephane Lefebvre, A Look at Intelligence, International Journal of Intelligence and
CounterIntelligence, 17: pg. 233, (2004)
5. Martin T. Bimfort, A Definition of Intelligence, 6-7
6. R.A. Random, Intelligence as a Science, 76
7. Random, 77-78

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8. Robert S. Michael, Inquiry and Scientific Method, Strategies for Educational Inquiry,
Fall 2002, Y520:5982, pgs. 3,4
9. Stephen Marrin, Is Intelligence Analysis an Art or a Science?, International Journal of
Intelligence and CounterIntelligence, 25:3 (2012). 529-545
10. Stephen Marrin
11. Stephen Marrin
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13. Jack Davis, A Policymaker’s Perspective on Intelligence Analysis, Insightful
Interviews, pg. 7, 9
14. Martin Peterson, The Challenge for the Political Analyst, Advice from a DI Careerist,
52
15. James McCullough, Commentary on “Congress as a User of Intelligence”, 71
16, Roger George, Fixing the Problem of Analytic Mindsets, International Journal of
Intelligence and CounterIntelligence, 17:3, (2004), 385-404
17. Richards Heuer, Tim Van Gelder, Email exchange,
https://blackboard.jmu.edu/webapps/portal/frameset.jsp?tabGroup=courses&url=
%2Fwebapps%2Fblackboard%2Fcontent%2FcontentWrapper.jsp%3Fcontent_id
%3D_3286920_1%26displayName%3DLinked%2BFile%26course_id%3D_1494
40_1%26navItem%3Dcontent%26attachment%3Dtrue%26href%3Dhttps%253A
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20. Jerome Groopman, How Doctors Think, Houghton Mifflin, (2007), 6
21. Marrin, Clemente, Modeling..
22. Groopman, 12-14
23. Groopman, 20-22

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