Improving Intelligence Analysis by Looking to the Medical Profession – By STEPHEN MARRIN and JONATHAN D. CLEMENTE

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Improving Intelligence Analysis by

Looking to the Medical Profession

Intelligence agencies might benefit from assessing existing medical practices

for possible use in improving the accuracy of intelligence analysis and its

incorporation into policymaking. The processes used by the medical

profession to ensure diagnostic accuracy may provide specific models for

Intelligence Community use that could improve the accuracy of analytic

procedures. The medical profession’s way of accumulation, organization,

and use of information for purposes of decisionmaking could also provide

a model for the national security field to adopt in its quest for more

effective means of information transfer. Some limitations to the analogy

areinevitableduetointrinsicdifferences between the fields, but the study

of medicine could provide intelligence practitioners with a valuable source

of insight into various reforms with the potential to improve the craft of



The analogy between medical diagnosis and intelligence analysis has been a

thin thread running through the intelligence literature. In 1983, historian

Walter Laqueur, in ‘‘The Question of Judgment: Intelligence and



examined the analogy at a general level. He argued that

Stephen Marrin is a doctoral candidate in the Woodrow Wilson Department of

Politics at the University of Virginia, specializing in the study of intelligence. He

previously served as an analyst with the Central Intelligence Agency and

subsequently with the Congressional Government Accountability Office (GAO).

Jonathan D. Clemente, M.D., is a physician in private practice in Charlotte, North

Carolina. He is currently writing a scholarly history of the United States medical

intelligence program and medical support for clandestine operations from World


International Journal of Intelligence and CounterIntelligence, 18: 707–729, 2005

Copyright #Taylor & Francis Inc.

ISSN: 0885-0607 print=1521-0561 online

DOI: 10.1080/08850600590945434


medicine is more an art than a science because the process of diagnosis entails

the use of judgment as a means to address ambiguous signs and symptoms.


Laqueur also highlighted similarities between medicine and intelligence. For

example, in citing advances in medical technology he said it was ‘‘precisely

because of such progress [that] the similarity in concept between medicine

and intelligence has become more obvious.’’


He noted that ‘‘the

similarities extend to both collection and analysis, or in the case of

medicine, diagnosis.’’


In addition, Laqueur emphasized similarities in

analytic processes, pointing out that ‘‘the student of intelligence will profit

more from contemplating the principles of medical diagnosis than

immersing himself in any other field. The doctor and the analyst have to

collect and evaluate the evidence about phenomena frequently not

amenable to direct observation. This is done on the basis of indications,

signs, and symptoms… . The same approach applies to intelligence.’’


Many aspects of intelligence practice can be found in medicine, including a

parallel to the steps in the intelligence cycle. Just as in intelligence, medical

practice includes tasking, collection, analysis, and dissemination. Consider

the case where a patient presents a ‘‘chief complaint’’ and asks the

physician to come up with a diagnosis and appropriate course of

treatment. The physician assembles bits of raw information about the

‘‘history of present illness,’’ analyzes the data to come up with both a

reasonable differential diagnosis and a presumptive diagnosis, and provides

a course of treatment and prognosis to the patient. The cycle repeats itself

as better information becomes available, new questions arise, and the

diagnosis and definitive treatment are refined.

Unfortunately, Laqueur’s observations have not been explored at length in

over two decades. No other articles have been published on the analogy

between intelligence and medicine, and no books have addressed it at

length. This failure by both practitioners and students of intelligence to

explore the ramifications of an analogous profession is indicative of the

conceptual insularity of the intelligence discipline writ large. Security

concerns constrain the intelligence community’s ability to reach out to

external sources for ideas and insight, and, as a result, the internal

discussions that occur in intelligence circles regarding ways to improve

existing practices—the same kinds of discussions that occur in every field—

are stultified because of the limited number of ideas that can proceed

through the narrow chokepoints to the outside world.


The similarities between intelligence analysis and medical diagnosis are

obvious at first glance, with intelligence producing analysis and estimates

regarding events in foreign countries and medicine producing diagnoses



and prognoses regarding the health of individuals.


In both intelligence and

medicine, the practitioner uses similar approaches and technology to gather

data, integrates this data into an assessment of what is going on today

patterned on existing understandings of causal relationships, and then

interprets the importance of the situation and forecasts what might happen

in the future in terms useful for decisionmaking. In addition, both

intelligence analysis and medical diagnosis are vulnerable to similar causes

of inaccuracy in their respective assessments.

Parallels in Collection

Both medical and intelligence practitioners apply the same general

approaches and similar technologies to acquire information. Medical

diagnosis and patient health assessment follow a fairly standard algorithm

taught to every second-year medical student and in use since the days of

the great diagnostician Sir William Osler. Each step within this algorithm

has a specific parallel to the processes used to collect intelligence.

The diagnostic process begins with the elicitation of the ‘‘history of present

illness,’’ where the patient relates the characteristics of the specific complaint

and other subjective qualitative and quantitative features to a physician. The

physician then ascertains any relevant past medical or surgical history,

medication use, and known allergies. In the intelligence profession, this

might be roughly equivalent to the acquisition of ‘‘basic intelligence’’—i.e.,

knowledge regarding foreign countries or groups for operational planning

at any level


—in order to determine the potential significance of any recent

changes. While the patient interview is a good information source for

diagnosing a patient, as in the human intelligence process, self-reporting by

patients can be notoriously unreliable, for any of a number of reasons. As

a result, medical schools train physicians to acquire information from the

patient via what intelligence practitioners might consider an approximation

of human intelligence (HUMINT) elicitation techniques including use of

body language to ‘‘enhance rapport and reinforce continuity of

conversation,’’ appropriate uses of closed and open questioning,

minimization of jargon, and the use of positive reinforcement and silence

as ways to control the interview.


The intelligence community’s equivalent

to the ‘‘patient interview’’ might be a State Department or military attache


report of a conversation with a foreign official, or perhaps, a defector or

refugee debriefing.

The second step in the medical diagnostic process is the ‘‘review of

systems.’’ At this stage, the physician literally performs an objective

head-to-toe assessment of specific organ systems, such as the cardiovascular

and gastrointestinal systems, in order to determine whether any specific signs

or symptoms of disease are present. The penultimate step is the ‘‘physical



examination’’ of the patient, beginning with a measurement of the

acknowledged vital signs: temperature, blood pressure, pulse, heart and

respiratory rate. This hands-on assessment of the patient—checking for

swollen lymph nodes, listening to the heart, feeling the belly, checking the

reflexes—is the true art of medicine. In the intelligence field, these hands-

on checks do not have a direct equivalent for analysts, other than perhaps

overseas familiarization tours made to gain first-hand knowledge of the

country they are responsible for. A second-hand version of the physical

exam might also be intelligence cables from State Department officers or

military attache

´s, reporting on what they saw during their travels in

foreign countries.

Finally, if additional information is required, physicians then order

laboratory tests. Some tests, such as X-rays or magnetic resonance imaging

(MRI), are equivalent to imagery intelligence (IMINT),


while other tests

such as those that measure blood products or other bodily functions could

be considered the rough equivalent of measurement and signatures

intelligence (MASINT).

In addition, just as the collection systems are similar in both medicine and

intelligence, so is the discussion over the relative utility of the information

provided by each system. An active debate exists within the intelligence

field over the relative value of various collection systems in divining the

capabilities or intentions of international actors. A similar debate occurs in

the medical field. According to a popular aphorism taught to generations

of medical students, ‘‘90 percent of all diagnoses are made by the clinical

history alone, 9 percent by the physical exam, and 1 percent by laboratory

tests and imaging studies such as CT and MRI scans.’’ While the medical

profession’s use of laboratory tests and medical diagnostic imaging

modalities, such as computed tomography (CT) scans and magnetic

resonance imaging (MRI), may be increasing, they are not infallible and

often do not reveal the definitive diagnosis. Ultimately, just as IMINT

cannot provide the same insight into intentions as HUMINT, no CT scan

or MRI can replace the physician–patient relationship, the hands-on

approach, or the experience of having examined patients before. In both

intelligence and medicine, all forms of collection must work in concert for

the all-source intelligence analyst or the physician to successfully complete

their tasks.

Yet, the collection of information in either the medical or intelligence field

does not ipso facto lead the practitioner to a conclusion, and an over-

emphasis on collection in either field may lead to excessive data collection.

According to Richards Heuer, the ‘‘rationale for large technical collection

systems’’ may be rooted in the misapplication of the so-called ‘‘mosaic

theory of intelligence.’’


This theory states that a ‘‘clear picture of reality’’

results from the assemblage of numerous bits of information into a



‘‘mosaic or jigsaw puzzle’’ and implies that accurate assessments can arise

only after accumulating a complete data set. However, as Heuer points

out, research into cognitive psychology suggests the opposite. Intelligence

analysts may first form a mental picture and then find individual pieces of

information—each of which may support independent hypotheses—to

support their initial estimate of the situation. The accuracy of these

estimates, therefore, may depend on the balance between data collection

and ‘‘the mental model used in forming the picture.’’ As a result, the analytic

and diagnostic processes used in both fields are very important because they

help the practitioners create the mental models that Heuer refers to.

Parallels Between Analysis and Diagnosis

Once the various streams of information are collected, the integration process

in medicine is very similar to that which occurs in intelligence because

practitioners in both fields use approximations of the scientific method—

observation, hypothesis, experimentation, and conclusion—as a means to

organize and interpret the collected information. Many empirical or data-

driven professionals, such as detectives in the law enforcement profession

and physicians in the medical profession, use the scientific method as a

way to derive causal relationships and test hypotheses. The ultimate goal is

to derive an accurate estimate of any given situation.

As has been addressed elsewhere,


the intelligence analysis process,

though an approximation of the scientific method, does not parallel it

exactly because no experiments are possible in the international arena. Yet,

most writers who focus on analytic tradecraft—whether they realize it or

not—portray the intelligence analysis process as a version of the scientific

method. In the end, intelligence analysis entails inductive and deductive

reasoning applied in turn to find patterns among data and derive

hypotheses that explain what the data mean. Most recommendations for

improving intelligence analysis are akin to the lessons taught in graduate-

level methodology courses: use good data, prevent bias, test hypotheses

through a competitive process, etc. Analysts tend to use intuitive ‘‘pattern

and trend analysis’’—consisting of the identification of repeated behavior

over time and increases or decreases in that behavior—to uncover changes

in some aspect of international behavior that could have national security



They then apply some aspect of disciplinary theory—

political science, economics, psychology, military science—informed by

their knowledge of the history and culture of the region to derive the

implications of the change. This analytic process is very similar to the one

physicians use to diagnose their patients.

For the most part, physicians must combine the signs and symptoms into a

hypothesis informed by theory—i.e., identified patterns associated with



diseases. The ability to arrive at a correct medical diagnosis goes far beyond

merely ordering the appropriate blood tests or X-rays. This clinical skill

requires years to master. At its core it requires a solid base of working

medical knowledge, involving the interpolation and synthesis of sometimes

incongruous facts into a logical diagnosis. Fundamentally, the most

effective physicians are good listeners, capable of at once noting the

pertinent elements of the patient’s complaint, adroit at recognizing nuances

in expression, body position, and vocal inflection, and able to use these to

discern the true nature of a patient’s complaint.

When the analytic processes in medical diagnosis and intelligence analysis

are assessed side-by-side, the parallels are striking. According to the Central

Intelligence Agency’s (CIA) Richards Heuer, medical diagnosis provides a

more accurate way of describing how intelligence analysis should work

than do other analogies,



The doctor observes indicators (symptoms) of what is happening, uses his

or her specialized knowledge of how the body works to develop

hypotheses that might explain these observations, conducts tests to

collect additional information to evaluate the hypotheses, then makes a

diagnosis. This medical analogy focuses attention on the ability to

identify and evaluate all plausible hypotheses. Collection is focused

narrowly on information that will help to discriminate the relative

probability of alternate hypothesis. To the extent that this medical

analogy is the more appropriate guide to understanding the analytical

process, there are implications for the allocation of limited intelligence

resources. While analysis and collection are both important, the

medical analogy attributes more value to analysis and less to collection

than the mosaic metaphor.


Even the process of distinguishing the relevant information from the

irrelevant—also known as differentiating the signals from the noise—is

similar in both professions. The process of arriving at a medical diagnosis

requires that the physician first establish a reasonable ‘‘differential

diagnosis,’’ which often includes two or more diseases that may have

similar signs and symptoms. The task of the physician is to systematically

compare and contrast the clinical findings to determine the most likely

etiology—or cause—of the patient’s malady. Similarly, Heuer argues that

without considering all alternative hypotheses, an intelligence analyst

cannot evaluate the ‘‘diagnosticity of evidence.’’ He considers this term to

mean ‘‘the extent to which any item of evidence helps the analysts

determine the relative likelihood of alternative hypothesis.’’ So, for

example, Heuer correctly points out that ‘‘a high-temperature reading may

have great value in telling a doctor that a patient is sick, but relatively

little value in determining which illness a person is suffering from.’’

Diagnostic evidence influences one’s ‘‘judgment on the relative likelihood



of the various hypotheses’’; whereas, evidence that ‘‘seems consistent with all

the hypotheses’’ at least in the case of medicine, does not narrow the

differential diagnosis, and ‘‘may have no diagnostic value.’’


Technology and Coordination

Technological tools developed to improve the rigor and accuracy of

intelligence analysis or medical diagnosis can help analysts and physicians

weed through data and discover patterns, but are less able to assist the

analysts in interpreting the intelligence and deriving meaning and

implications. Both medical diagnosis and intelligence analysis require

judgment in interpretation of the evidence that goes above and beyond

what can be quantified or automated. The scientific method helps

intelligence analysts and physicians form hypotheses regarding the cause of

the issue at hand, but in both cases ambiguous information and

circumstances require critical thinking and judgment in order to come to

conclusions regarding the accuracy of the hypothesis and its implications

for—respectively—a nation’s interests, or the patient’s well-being. An

implication stemming from this observation is that the accuracy of the

intelligence analysis or diagnosis may rest on the cognitive abilities of the

practitioners. ‘‘The key,’’ according to Richards Heuer, ‘‘is not a simple

ability to recall facts, but the ability to recall patterns that relate facts to

each other and to broader concepts—and to employ procedures that

facilitate this process.’’


Yet, just as in intelligence analysis, medical

diagnosis is occasionally arrived at serendipitously, as when a physician

reads about some obscure disease in a medical textbook or journal the

night before a case of this disease is coincidentally seen in his clinical practice.

Complicating matters, arriving at a judgment in both intelligence and

medical fields can require the interdisciplinary coordination of various

specialists. The development of expertise in the medical field was not only

the province of individual cognition, but required the creation of

specialties and sub-specialties focused on specific functional systems such

as neurology and orthopedics. But the broader implications of this

knowledge can be lost if the contribution of the specialty is not

reintegrated into a holistic assessment of the patient’s health. This entire

dynamic parallels the analytical specialization by the CIA’s Directorate of

Intelligence according to analysts’ political, military, economic, and

leadership disciplines. In intelligence, the integration of the various

specialist perspectives can at times be difficult, especially when events

overseas appear to have multiple explanations that cross the various

disciplines. The integration of perspectives can be easy if they all point

towards one explanation, but if different intelligence disciplines or medical

specialties have different explanations, doing so can be very difficult.



The parallels between the collection and analysis of information in the

medical and intelligence fields indicate that the underlying analytic

processes are similar, but these similarities also mean that the causes of

inaccuracy in their respective fields are also parallel.


Medical diagnosis and intelligence analysis have similar causes of inaccuracy

due to their similarities in collection and analysis. They share at least three

causes of inaccuracy; they undoubtedly have many additional sources of

error in common.

First, inaccuracy in both intelligence analysis and medical diagnosis can

arise from the unavoidable limitations in the collection and analysis of

information. Both medicine and intelligence collection are subject to some

amount of both random and systematic error resulting from built-in

limitations of the collection instruments themselves, and as a result the

information that feeds into the subsequent analysis is never an exact

representation of reality. For example, the ability of modern medical

imaging modalities such as the CT and the MRI to accurately depict

anatomic structures is limited by technical constraints of spatial-temporal

resolution and signal-to-noise ratio. An equivalent in the intelligence world

could be the subjective interpretations that case officers inevitably include

in their interpretations of an asset’s reliability and the information he or

she provides. In the aggregate, these errors can combine to cause

inaccuracy on the margins of both intelligence analysis and diagnosis.

Additional inaccuracy at the analytic level compounds whatever errors

may have been incorporated during the collection of information.


As has

been pointed out elsewhere,


the analytic process itself is subject to an

individual analyst’s cognitive limitations, and as a result ‘‘analysis is

subject to many pitfalls—biases, stereotypes, mirror-imaging, simplistic

thinking, confusion between cause and effect, bureaucratic politics, group-

think, and a host of other human failings,’’ according to administrators at

the Joint Military Intelligence College.


In the medical field, one of the

most often repeated pearls of wisdom for diagnosing patients is that

‘‘uncommon manifestations of common diseases are more common than

uncommon manifestations of uncommon diseases,’’ or ‘‘when you hear

hoofbeats, look for horses and not zebras.’’ The challenge faced by many

neophyte physicians is to adhere to this medical truism. The background

noise that arises from reading about and observing a multitude of new and

unusual diseases can obscure the signals of a more workaday illness. The

same can be said for intelligence analysts as well, and controlling for

possible causes of error in analysis has become the subject of many

intelligence articles.




In addition, errors may arise in both intelligence analysis and medical

diagnosis due to problems intrinsic to the implementation of the scientific

method. The deductive approach used by practitioners in both fields

requires some inductive ability to distinguish the relevant information

(signals) from the irrelevant (noise). Generally, conceptual frameworks

built out of hypotheses that tie together a number of cause=effect

relationships are used, but distinguishing the signals can still be a difficult

task. As Walter Laqueur observes, ‘‘like the intelligence analyst, the

clinician faces the problem of detecting signals. A weak signal may be

drowned in background noise. Perhaps the most frequent of such

situations facing him occurs when taking the case history of a loquacious

patient. … In each case, a post mortem shows that all the necessary

information was available but it did not register, sometimes because of an

abundance of clues, sometimes because of a temporary eclipse in

observation or critical acumen.’’


In medicine, an example of this kind of

error would be the mistaken attribution of a health problem to an

innocuous external factor that was correlated with the problem but not the

cause of it. Specifically, the long-term false attribution of peptic ulcers to

‘‘spicy food, acid, stress, and lifestyle’’ rather than the presence of a

bacteria (Helicobacter pylori or H. pylori) that ‘‘causes more than 90

percent of duodenal ulcers and up to 80 percent of gastric ulcers’’ is an

example of an error due to the complexities of distinguishing signals from

noise in a medical context.


In the intelligence arena, many possible

explanations exist for specific outcomes, such as a foreign government’s

negotiating position at an international conference, but in many cases

intelligence analysts may have difficulty determining whether the position

taken is due to underlying political forces, economic conditions, or the

agenda of a single individual or groups of individuals. Errors in the

interpretation of events are likely when the conceptual frameworks for

explaining the outcome are insufficiently specified.

Finally, errors may occur in both intelligence analysis and medical

diagnosis due to the misapplication of the scientific method. For example,

in mid-2003 the Washington Post reported that ‘‘recommended ‘best

practices’ were followed about two-thirds of the time in diagnostic

testing,’’ presumably leading to suboptimal outcomes.


The parallels to

intelligence analysis are obvious. If the practitioner does not follow

analytic tradecraft, inaccuracies could be incorporated into the analytic

process unless specific means are implemented to ensure that the

conclusions follow directly from the evidence.

Because the mechanisms used to collect and analyze information in both

fields are so similar, the causes of inaccuracy are also similar. But, deriving

lessons from analogies requires an understanding of the limits of the

analogy that are defined by the differences between the fields. In addition



to the substantial similarities between the intelligence and medical fields,

substantial differences exist as well.



Prominent differences between intelligence analysis and medical diagnosis

limit the analogy and the lessons that can be derived from it. Differences

exist in the kinds of problems that practitioners in both fields address, the

kinds of knowledge used to address them, the reliability of the information

acquired, and the use of the information in decisionmaking. Nonetheless,

their existence does not remove all utility from the analogy. In each case,

the analogy continues to hold between intelligence analysis and a subset of

the medical profession.

Differing Types of Problems

Intelligence analysts and physicians obviously address different kinds of

problems. In general, intelligence analysts assess the international

environment for changes that could affect U.S. security interests. While the

identification of threats is a part of an intelligence analyst’s responsibility,

the analyst usually has to first assess whether or not there is a threat, while

a physician’s diagnostic mission tends to be more constrained. Patients

generally seek medical attention when they have identified an existing

health problem, and look to the physician to identify its cause and

establish a course of treatment for its resolution. As a result, the

intelligence analyst’s mission is roughly equivalent to the subset of the

medical diagnostic range known as preventive medicine, where patients are

assessed for underlying health problems for which no symptoms may be

observable or identifiable. Alternatively, subsets of each medical diagnostic

and intelligence analysis specialty may deal with a comparable range of

issues. For example, intelligence analysts who track identifiable problems

over time, such as nuclear proliferation or terrorism, may be more

analogous to the physician who assesses the condition of a patient with a

chronic health problem.

Epistemological Foundations

Intelligence analysis and medical diagnosis are grounded in different

epistemological foundations, with implications for how practitioners in the

respective fields make decisions.


Specifically, the greater accumulation of

knowledge and theory in the physical sciences than in the social sciences

provides medical practitioners with a relatively larger empirical base and



more precise causal relationships, enabling them to make diagnoses and

prognoses with a greater level of certainty than their intelligence


Medical knowledge of relationships between cause and effect exists at a

high level of specificity because the development of medical science—built

on the physical sciences—has allowed practitioners to aggregate knowledge

and build a progressively larger base of information regarding the effects

of diseases and pathologies on human health. The key to this growth has

been the ability of medical science to research the causes and effects of

various diseases in laboratories where researchers can limit the influence of

extraneous factors. In addition, medical researchers use incidence rates

of disease throughout the population as a way to approximate many

‘‘experiments’’ simultaneously. Once medical researchers have identified the

pathologic or cellular basis for disease and the full range of effects on a

typical patient’s health, new physicians are taught the patterns of signs and

symptoms in medical school, and are kept updated on current research

through their continuing professional education programs. As greater

knowledge of cause and effects is accumulated, more detailed and specific

diagnoses and prognoses become possible.

By way of contrast, most causal relationships derived from the social

scientific theories of interest to intelligence analysts are still indeterminate

due to the infrequent occurrence of important events on the international

stage, and the analyst’s inability to test hypotheses through laboratory

experiments. Intelligence analysts rely primarily on social scientific theories

that explain nation-state behavior at various levels of analysis, but none of

these theories is as precise as those in the physical sciences. For example,

intelligence analysts use international relations theory to ground their

analyses at the systemic level; political science and economic theory to

ground their analyses at the state level; and psychology to ground their

analyses at the individual level. Yet, for the most part, these theories do

not provide specific identifiable patterns akin to those physicians use to

diagnose pathology, because social scientists have been unable to define

the circumstances under which the various theories can individually explain

state behavior. Economics may be the social scientific theory that most

closely resembles the physical sciences,butevenithasdifficultywith

precise explanations because of its assumptions of perfect information and

rational behavior that rarely seem to occur in the real world. As a result,

Yale University historian John Lewis Gaddis asserts that most social

science theories ‘‘tend to be parsimonious, attributing human behavior to

one or two basic ‘causes’ without recognizing that people often do things

for complicated combinations of reasons’’ and as a result are ‘‘static,

neglecting the possibility that human behavior, individually or collectively,

might change over time.’’


Gaddis concludes that as a result of these



tendencies, ‘‘the social sciences are operating … at roughly the level of

freshman physics experiments [and] that’s why the forecasts they make

only occasionally correspond with the reality we subsequently



If the theories that intelligence analysts use to forecast future

events produce accurate assessments only infrequently, it is no surprise

that intelligence analysis forecasts follow a similar path.

Over time, social scientists have been able to accumulate knowledge about

the causes of larger international events—such as war or international

cooperation—but for the most part these explanations are very general and

lack the precision necessary to explain or forecast the kinds of specific

events that intelligence analysts are interested in. In medical terms,

intelligence analysts have a similar understanding of the patterns that

underlie international relations that physicians had for disease some two

centuries ago. Some social scientists have attempted to model international

relations in a similar way to the physical sciences, but these models have

been—for the most part


—found wanting for intelligence purposes. As

Walter Laqueur explains, ‘‘For a long time, military and foreign political

intelligence have tried to become scientific, or at the very least more

scientific. … But, inasmuch as assessment is concerned, the outcome of a

search for a scientific theory improving the predictive capacity of

intelligence has been quite disappointing.’’


As a result, for the most part,

medical diagnoses can be made with greater precision and accuracy than

can intelligence analysis.

Nonetheless, parallels do exist between medical diagnosis and intelligence

analysis in certain areas where medical knowledge has not yet acquired

sufficient ability to understand the cause of health problems or their

impact on a patient’s health. Many diseases and genetic syndromes have

no known cause or effective treatment and are deemed ‘‘idiopathic.’’

Medical literature frequently attributes the causative agent in these

‘‘idiopathic’’ cases to either an ‘‘autoimmune disorder’’ or a virus. In other

cases, the ability to diagnose various diseases may be fraught with

uncertainty and ambiguity. In describing the unpredictable biological

behavior of a certain cancer, a major pathology reference text quips ‘‘these

tumors don’t read textbooks.’’


Pathologists are supposed to provide the

clinician with the definitive ‘‘ground truth’’ of any given disease entity, but

for one particular class of tumors a surprising degree of internal

disagreement occurs over ‘‘final pathologic diagnosis,’’ not only at the

hospital level, but on a national and international level as well. Finally, the

effect of disease on individuals is highly variable. For many years, clinical

medicine was taught based on a ‘‘hypothetical 70 kilogram white male.’’

Yet physicians recognized through anecdotal experience what is now

accepted as fact: few individuals react exactly the same way to the same

disease, or the same treatment. To diagnose the patient effectively the



physician must be aware of these differences in presentation, but the medical

profession has only recently incorporated this paradigm shift into its

therapeutic regimens. As a result, a substantial practical component to

medicine requires a combination of experience and judgment that is not

codified in any text, but is simply passed down to young physicians in the

oral tradition of the clinical wards.

In those cases where levels of uncertainty faced by practitioners in both

fields are the same, their methods for handling uncertainty are also similar.

Intelligence agencies teach analysts to use alternative forms of analysis to

handle unconventional analytic challenges. Similarly, when physicians are

not able to make a positive diagnosis immediately because of the inherent

ambiguity in medicine’s ‘‘gray areas’’—when insufficient empiric knowledge

exists or a common disease presents atypical or protean manifestations—

physicians sometimes resort to alternative diagnostic methods. For example,

physicians can treat the patient with the ‘‘tincture of time’’ or through

‘‘diagnosing by observing natural history’’ where careful, close observation

and the allowance of a short passage of time permit the true cause of the

disease to ‘‘declare’’ itself. Some medical disorders, such as ‘‘fibromyalgia,’’

are generally considered by the medical profession to be ‘‘diagnoses of

exclusion.’’ In other words, such a diagnosis should be made only after other

more common or potentially serious conditions are ruled out.

Thus, even though medicine may have a large knowledge base of

information regarding disease, enabling physicians to make accurate

diagnoses in a majority of cases, a large subset of issues persists, where the

incidence rates are low or issues are complex, and, as a result, medical

knowledge of pathological etiology and resulting signs and symptoms are

scant. In these cases, the levels of diagnostic uncertainty approximate those

faced by intelligence analysts because of the inexactness of the social

science theories they use to interpret the raw intelligence at their disposal.

Rates of Denial and Deception

Because intelligence analysis entails deciphering meaning through a more

extensive ambiguity, caused by greater denial and deception than exists in

the medical field, intelligence analysts generally labor under greater levels

of uncertainty than their medical counterparts. For example, in the

intelligence field, concern over whether foreign governments and entities

are providing disinformation through U.S. collection capabilities so as to

deceive analysts and policymakers leads to pervasive uncertainty over the

reliability of almost all information collected. These concerns complicate

the assessment and validation process since no piece of evidence can be

considered reliable without excessive scrutiny into both its substance and

the process by which it was collected.



The bulk of the medical profession does not labor under similar levels of

uncertainty resulting from denial and deception efforts on the part of

patients. As Walter Laqueur observed: ‘‘There is one important difference:

the patient usually cooperates with the medical expert; he has no incentive

to hide and to mislead.’’


As noted, in the medical field some uncertainty

is intrinsic in the assessment of information, and other concerns about

reliability can creep in, due to laboratory error or errors in patient self-

reporting, but, for the most part, the uncertainty is not due to a conscious

effort on the part of individuals to manipulate the process. For a sub-set

of cases in medicine, however, physicians may also labor under conditions

of uncertainty analogous to those in the intelligence world due to denial

and deception efforts.

In medicine, intentional deception by patients for purposes of misleading

the diagnosis are rare, but can be found in cases where the patient has an

underlying incentive to deceive. For example, physicians responsible for

making disability determinations, and for managing pain by dispensing

narcotics, can encounter patients who attempt to deceive them in order to

acquire money or narcotics. In the medical profession, this kind of

deception is known as ‘‘malingering,’’ and the underlying incentive to

deceive is known as ‘‘external or secondary gain.’’ In addition, physicians

encounter denial in circumstances where a patient is embarrassed or

unwilling to share the complete circumstances of an injury. Also, rarer still,

are cases of unintentional denial—or patient self-deception—arising from

psychological disorders, in which symptoms expressed by the patient are

not indicative of underlying health problems. These incidents could be

roughly analogous to cases where inaccurate information is possessed by

foreign governments and subsequently acquired by intelligence agencies.

Examples from medicine include Munchausen syndrome (i.e., a habitual

and intentional effort to produce convincing physical or psychological

symptoms in order to gain attention through the sick role), and

hypochondriasis (i.e., morbid anxiety about one’s health with symptoms

unattributable to organic disease).


Malingering, hysterical symptoms, and hypochondriasis can be especially

difficult to detect, in part, because of a physician’s natural reluctance to make

such a ‘‘diagnosis’’ before an actual organic illness is excluded. As a result, no

firm epidemiological data on the incidence of such ‘‘deceptive’’ conditions is

available Nevertheless, physicians are taught to recognize certain signs of

‘‘functional’’ illnesses where no anatomic or pathologic causes can be

found. For example, the diagnosis of ‘‘pseudoseizures’’ may be established

through clinical history alone, or by the absence of signs associated with

true seizure disorders. Malingering may be detected when there is an

incongruity between claimed injury and an inconsistent mechanism of

injury. Ultimately, some cases may require the performance of specialized



tests to exclude a structural problem. ‘‘Hysterical blindness’’ can be

established by performing a visual-evoked response, where a flash of light

in the eye ‘‘evokes’’ an electrical signal in the portion of the brain involved

in vision, indicating intact visual pathways. Similar tests are used by

intelligence practitioners to determine whether a government or individual

is being actively deceptive or attempting to prevent the U.S. government

from acquiring certain kinds of information.

The relatively higher levels of uncertainty in the intelligence world are due

to the greater incentive for foreign governments to deny the U.S. government

information on their activities or deceive them regarding the extent of those

activities. But the subset of cases in the medical world, where patients have

incentives to deceive, can provide analogies and perhaps even lessons that

intelligence analysts can adopt to improve their own processes.


But the analogy between intelligence analysis and medical diagnosis fails the

closer it gets to the decisionmaking process. As Walter Laqueur points out:

‘‘the comparison between medicine and intelligence … cannot be carried

beyond a certain point; the doctor engages not only in diagnosis but also

in curing the patient.’’


Because most physicians are also responsible for

treating patients, they are in essence roughly equivalent to national security

decisionmakers. Yet, an in-depth examination of the distinction between

diagnosis and treatment in medicine and intelligence and decisionmaking

in foreign policy helps define the extent to which the analogy can be used

as a means of exploring alternative ways of doing business.

Assessing the importance of information within a decisionmaking process

first requires understanding how information is used by decisionmakers.

Harvard University historian Ernest May uses a simple framework to

summarize that process:

[At] any time or place, executive judgment involves answering three sets of

questions: ‘‘What is going on?’’; ‘‘So what?’’ (or ‘‘What difference does it

make?’’); and ‘‘What is to be done?’’ The better the process of executive

judgment, the more it involves asking the questions again and again, not

in set order, and testing the results until one finds a satisfactory answer

to the third question—what to do (which may be, of course, to do



In national security policymaking, an individual decisionmaker requires

information regarding international events and issues that have the

potential to affect United States national interests (what’s going on?); the

analysis and evaluation of this information (so what?); and the ability to

create and implement effective policies (what is to be done?). In medicine,



the decisionmaking process works similarly. A treating physician must first

assess the patient and diagnose the cause of any problems, then evaluate

the significance of these problems by creating a prognosis, and finally

decide on a course of action to treat the patient. But national security

decisionmaking occurs on both individual and organizational levels,

thereby greatly complicating the analogy between medical diagnosis and

intelligence analysis.

National security policymakers generally follow the decisionmaking

process laid out by Professor May, but a policymaker does not derive

information as directly from first-person experience as does a physician

from an interview and subsequent examination of the patient. Rather, in

the national security world, information is collected, filtered, analyzed,

and disseminated in an organizational context, so that any assessment of

the role that intelligence plays in national security decisionmaking must

also be grounded in an institutional context. National security

policymakers have staffs that provide them with information-acquisition,

analysis, and decisionmaking assistance. Additional similar assistance is

provided by intelligence agencies. In fact, intelligence analysts at the

CIA are trained to answer two of Professor May’s three questions by

explicitly addressing the ‘‘what’’ and the ‘‘so what’’ in their finished

intelligence analysis. However, answering the question ‘‘what is to be

done?’’ in the national security realm is prohibited for intelligence

analysts while they monitor the international environment for foreign

policymakers, and alert them to any changes that might affect national

interests. Intelligence is thus subordinate to policymaking, and resembles

the product of the type of analysts, described by Geoffrey Vickers, as

the kind who monitor the decisionmaker’s environment for any changes

and acts as a ‘‘watchdog on a chain; he can bark and alert the

householder, but he cannot bite.’’


National security decisionmakers, however, do not make decisions only

after receiving finished intelligence analysis; in many cases they are their

own analysts, and have entirely separate sources of information. Many

policymakers have access to raw intelligence reporting as well as finished

intelligence analysis; they also have separate information streams outside

the intelligence community, such as contacts in academia, think tanks,

the domestic and international business world, and foreign government

officials. As a result, the medical analogy may be a better fit for

comparing the decisionmaking processes of physicians and national

security policymakers than intelligence analysts. The eminent

international relations scholar Alexander George came to a similar

conclusion when he looked at the uses of information in foreign policy




Correct diagnosis of a policy problem and of the context in which it

occurs should precede and—as in medical practice—is usually a

prerequisite for efforts to make the best choice from among treatment

options. The analogy with the medical profession is an apt one, since

the policymaker, like the physician, acts as a clinician in striving to

make a correct diagnosis of a problem before determining how best to

prescribe for it.


But even if this analogy between physicians and policymakers works

better, physicians rely on the advice of other diagnostic experts because of

economies of scale and limitations in both time and expertise. For

example, an oncologist may be the ‘‘analyst’’ and ‘‘policymaker’’ for a

given patient, but relies on other analysts, such as the radiologist, to

identify the initial manifestations of disease, the surgeon to provide a tissue

sample, and the pathologist to give the ‘‘final answer.’’ In this framework,

the medical equivalent of an all-source intelligence analysis would be a

delegated diagnostic sub-specialty with access to most of a physician’s data

sources, including written reports of patient interviews, but no role in the

treatment decision process. This describes the role of a ‘‘consulting

physician’’ who is presented with a clinical problem outside the primary

physician’s expertise. The consultant is usually asked to review data and

formulate a diagnosis or differential diagnosis, but not necessarily to

implement treatment. One type of consulting physician is a radiologist,

who—while closer to the intelligence equivalent to an imagery analyst—

helps diagnose but does not treat, and hence, does not implement ‘‘medical



This examination of the analogy between intelligence and medicine indicates

its possible use in acquiring greater insight into intelligence processes, as well

as serving as a source of models for improving analytic processes. The

obvious similarities between intelligence analysis and medical diagnosis

indicate possible avenues for intelligence practitioners to derive lessons that

could improve analytic accuracy. For example, the processes of medical

diagnosis are vulnerable to the same pathologies that cause intelligence

failure, and techniques developed to improve the accuracy of diagnoses or

prevent malpractice based on diagnostic error may also improve the

accuracy of intelligence analysis. In 2003, a New York Times article

highlighted a team of radiologists who established a feedback process that

improves the accuracy of their diagnosis. A similar mechanism could be

used to improve the accuracy of intelligence analysis.


Alternatively, the

medical subspecialties have long relied on the monthly ‘‘morbidity and

mortality conference’’ (the ‘‘M and M’’ conference) as a forum to discuss



complications in diagnosis and treatment, and methods of preventing adverse

events and outcomes. Both minor and major complications in patient care

are discussed. Though physician participants in these regular ‘‘M&M’’

conferences often provide brutally frank assessments of their colleagues’

patient care, they are meant to be a learning tool for doctors at all stages

of their career. Perhaps the intelligence community might adopt a similar

periodic peer review process, not only to discuss ‘‘intelligence failures’’ of

the sort that makes newspaper headlines, but as a spot check on other

forms of basic and current intelligence.

In addition, each difference between intelligence analysis and medical

diagnosis conversely points to a more specific way that aspects of

intelligence analysis and medical diagnosis are similar in a subset of cases.

Lessons for the practice of intelligence analysis can be derived from each.

The medical equivalent of an all-source intelligence analyst would be a

diagnostic assistant in a preventive medicine context—possessing access to

all information that the treating physician needs—required to use

indeterminate indicators to diagnose patients who may have a rare disease

but also an incentive to misrepresent the health problem. The difficulties

that medical professionals face during the early stages of identifying and

preventing a novel disease such as AIDS might approximate the level of

complexity encountered by intelligence analysts daily. Nonetheless, each

difference between the professions highlights a dynamic where the analogy

still holds, and further examination may provide greater benefit for each


For example, a lesson that intelligence could learn from medicine’s

experience with preventive medicine is that, in many cases, the attempt to

assess developing health problems diverts substantial resources away from

addressing existing health problems. The medical profession has learned

that ‘‘many diagnostic tests … are given routinely to apparently healthy

people in the name of prevention,’’


and that this focus on testing, even

where there may not be any health problems, leads to the collection of

excessive amounts of information. As a result, the medical profession must

divert substantial diagnostic resources to analyzing the additional

information, even though most of it will indicate that no problem exists.

The lesson for intelligence agencies is that the possibility of collecting

information does not mean that it should be, because the additional

information may have a diversionary affect on analytic expertise.

Intelligence agencies could also learn from medicine’s foundation in the

physical sciences that specific procedures may have to be implemented in

order to aggregate knowledge and establish causal relationships specific

enough to be useful for purposes of intelligence analysis. Social scientists

in academia do not have access to the kinds of specific data that

intelligence analysts do. As a result, their models are usually general and at



a high level of abstraction. Due to security and classification concerns,

however, no established process exists for creating the kinds of indicator

patterns that intelligence analysts would find useful. Where would

medicine be if it had remained empirical, and knowledge not aggregated

into theory? The establishment of an internal intelligence community unit

of social scientists devoted to the production of mid-level theory and

hypotheses useful for intelligence analysts would provide intelligence

agencies with an improved base of theory for finding meaning in the raw

intelligence. In addition, new attempts are being made to improve the way

medicine learns about disease and its impacts. In 2003, the National

Institutes of Health started a multidisciplinary collaborative effort ‘‘to

improve the diagnosis … of diseases,’’ including ‘‘identify[ing] scientists

who are exceptionally creative thinkers, and award[ing] them $500,000

grants’’ as a way to foster idea generation and cross-pollination.



efforts in the intelligence community could draw together disparate experts

with idiosyncratic knowledge residing in the corners of the intelligence

community, and provide them with the opportunity to assess intractable

intelligence issues from new multi-disciplinary perspectives. In the end, not

every collaborative project has to break new ground for such an approach

to be successful; as with scientific research and development, all that is

needed is a periodic breakthrough for the approach to be worthwhile.

Discerning the Deceivers

In the area of ‘‘denial and deception,’’ the intelligence community might also

learn from medicine’s experience in identifying how physicians distinguish

malingering from legitimate patient health concerns. The incidence of

malingering may be under-diagnosed when deception goes undetected.

Conversely, the incidence of malingering may be over-diagnosed in cases

where medical knowledge has not been able to fully capture the complexity

of the human physiological system. As noted earlier, gray areas exist in

medicine at the boundary between understanding and learning. Because

physicians may not fully understand the underlying causal mechanisms,

patients with rare diseases may be diagnosed as malingerers even though the

disease itself is real, but poorly understood by medicine. The challenge for

physicians, therefore, is to remain cognizant of the potential for deceptive

behavior on the part of patients, but not to the point that legitimate signs

and symptoms are dismissed out of hand. In the intelligence world, this

observation may have immediate relevance in the assessment of the status

of Iraq’s weapons of mass destruction (WMD). In that case, intelligence

analysts apparently assumed that Saddam Hussein’s failure to document

the destruction of all of his WMD indicated that he was deceiving Western

governments and diverting the weapons elsewhere, despite his protestations



to the contrary. In the end, a warning from the medical world applies just as

well to concerns of deception in the intelligence arena: ‘‘to recognize that

[because] the detection of malingering can be very difficult’’ any diagnosis

of it ‘‘must be sustained by evidence.’’


Lessons for intelligence could also come from acknowledgement of the role

that intelligence information plays in decisionmaking, and explicit efforts

to improve the kinds of information provided to policymakers. For

example, according to a David Brown in the Washington Post, ‘‘the body

of medical research on just about any important subject is vast—too big

for the average practitioner to grasp,’’


just as it is in national security

decisionmaking. To address this problem, a government agency—the

Agency for Healthcare Research and Quality (AHRQ)—has established

‘‘evidence-based practice centers’’ at thirteen universities, and is paying

researchers there to ‘‘examine all the studies on a given question, evaluate

their validity … and ultimately extract conclusions—the ‘‘best evidence’’—

from the mass of information.’’ While this medical research addresses both

diagnosis and treatment, an intelligence adaptation might be to similarly

organize and assess both raw intelligence sets and finished intelligence—to

identify the good and the bad—for the benefit of providing decisionmakers

with a better sense of the intelligence information that already exists on a

particular topic. On a broader scale, the AHRQ’s mission is to assess how

medical processes work, and how the government might help improve

those processes.


A similar unit inside the intelligence community with

free rein to assess management practices could be invaluable.

Crossing Professional Lines

Finally, the lessons that intelligence can draw from an examination of the

similarities and differences with the medical profession indicate the

importance of looking to analogous professions for ideas that can be

adapted to an intelligence context. Doing so might help improve finished

intelligence production processes and the incorporation of intelligence into

decisionmaking. Analogies serve a number of purposes, such as aiding

communication about difficult topics by finding illustrative examples in

other fields, or by more directly affecting existing ways of doing business

through the incorporation of tools that exist to achieve similar purposes in

other fields. Many of the challenges intelligence analysts face are not as

unique as its practitioners believe, but the insularity of the field prevents

them from being able to identify the lessons from other professions that

could be useful as models to follow.

As a result, the first task is to identify analogous professions, and examine

them for the lessons they might provide. Any profession that encounters



similar problems—such as medicine, journalism, law, or law enforcement—

may provide fertile ground for deriving ideas to improve existing practices.

Perhaps if intelligence analysts adopted methods from analogous

professions—or adapted them to the unique requirements of intelligence

analysis—some of the obstacles they currently face in accurately portraying

their understandings of the international environment could be overcome.



Walter Laqueur, ‘‘The Question of Judgment: Intelligence and Medicine,’’

The Journal of Contemporary History, Vol. 18. 1983, pp. 533–548. See also:

Walter Laqueur, A World of Secrets: The Uses and Limits of Intelligence

(New York: Basic Books, 1985), pp. 302–305.


According to Dorland’s Medical Dictionary, a ‘‘sign’’ is ‘‘any objective evidence of

disease’’ that can be independently observed by the physician, whereas, a

‘‘symptom’’ is ‘‘any subjective evidence of disease’’ reported by the patient.

Dorland’s Pocket Medical Dictionary, 26th ed. (Philadelphia: W.B. Saunders,



Walter Laqueur, ‘‘The Question of Judgment,’’ p. 535.




Ibid., pp. 534–535.


According to Dorland’s Medical Dictionary, ‘‘diagnosis’’ is the determination of a

cause of disease, and ‘‘prognosis’’ is ‘‘a forecast of the probable course and

outcome of a disorder.’’


See United States Department of Defense, Joint Publication 1-02, Department of

Defense Dictionary of Military and Associated Terms (Washington, DC: Joint

Chiefs of Staff, 2003), p. 55.


Janice Williams, Henry Schneiderman, and Paula Algranati, Physical Diagnosis:

Bedside Evaluation of Diagnosis and Function (Baltimore: Williams and Wilkins,

1994), pp. 1–5.


For parallels in the technologies used in medicine and intelligence, see: Sam Grant

and Peter C. Oleson, ‘‘Dual Use of Intelligence Technologies: Breast Cancer

Detection Research,’’ Studies in Intelligence, Vol. 1, No. 1, 1997, at

http:==<a href=”” rel=”nofollow”></a>=csi=studies=97unclass=cancer.html


Richards J., Heuer, J. Psychology of Intelligence Analysis (Washington, DC: CIA

Center for the Study of Intelligence, 1999), pp. 61–62.


Stephen Marrin, ‘‘Improving CIA Analysis by Overcoming Institutional

Obstacles,’’ in Russell G. Swenson, ed., Bringing Intelligence About:

Practitioners Reflect on Best Practices (Washington, DC: Joint Military

Intelligence College, 2003), pp. 40–59.


Mark V. Kauppi, ‘‘Counterterrorism Analysis 101,’’ Defense Intelligence Journal,

Vol. 11, No. 1, Winter 2002, p. 47.


Richards Heuer, Psychology of Intelligence Analysis, p. 62.




Ibid. While Heuer’s observations may be true in theory, the medical profession is

currently experiencing a debate over the possible over-collection of data that does

not conform to medical diagnostic theory. This problem with over-collection has

its parallels in the intelligence world as well. As a result, both fields struggle with

allocation and utilization of scarce resources.


Ibid., pp. 45, 101–102.


Ibid., p. 26. In this section Heuer cites Arthur S. Elstein, Lee S. Shulman, and

Sarah A. Sprafka, Medical Problem Solving: An Analysis of Clinical Reasoning

(Cambridge, MA: Harvard University Press, 1978), p. 276.


For a list of analytic errors that apply to both intelligence analysis and medicine,

see: Walter Laqueur, ‘‘The Question of Judgment,’’ p. 541.


Stephen Marrin, ‘‘Improving CIA Analysis by Overcoming Institutional

Obstacles,’’ pp. 40–59.


Ronald D. Garst and Max L. Gross, ‘‘On Becoming an Intelligence Analyst,’’

Defense Intelligence Journal, Vol. 6, No. 2, 1997, p. 48.


For more on the causes of analytic failure, see Richards Heuer, ‘‘Improving

Intelligence Analysis: Some Insights on Data, Concepts, and Management in

the Intelligence Community,’’ The Bureaucrat,Vol.8,No.1,Winter1979=80,

pp. 2–11. See also, Richard Betts, ‘‘Analysis, War and Decision: Why

Intelligence Failures Are Inevitable,’’ World Politics,Vol.31,No.1,October



Walter Laqueur, ‘‘The Question of Judgment,’’ p. 544.


For more on this dynamic, see: Center for Disease Control (CDC) Website; ‘‘Fact

Sheet: Helicobacter pylori and Peptic Ulcer Disease.’’ http:==<a href=”” rel=”nofollow”></a>=ulcer=



David Brown, ‘‘Medical Care Often Not Optimal, Study Finds,’’ The Washington

Post, 26 June 2003, p. A02.


For more on intelligence epistemology, see: Mark M. Lowenthal, ‘‘Intelligence

Epistemology: Dealing with the Unbelievable,’’ International Journal of

Intelligence and CounterIntelligence, Vol. 6, No. 3, Fall 1993, pp. 319–325.


John Lewis Gaddis, The Landscape of History: How Historians Map the Past

(New York: Oxford University Press, 2002), p. 57.


Ibid., p. 60.


An exception might be models developed internal to the intelligence community

that enable them to assess events of interest such as political stability. For

more, see: Stanley A. Feder, ‘‘FACTIONS and Policon: New Ways to Analyze

Politics,’’ in Inside CIA’s Private World: Declassified Articles from the Agency’s

Internal Journal, 1955–1992, H. Bradford Westerfield, ed. (New Haven: Yale

University Press, 1995), pp. 274–292. Also see: Stanley A. Feder, ‘‘Forecasting

for Policy Making in the Post Cold-War Period,’’ Annual Review of Political

Science, Vol. 5, June 2002, pp. 111–125.


Walter Laqueur, ‘‘The Question of Judgment,’’ p. 533.


Ramzi S. Cotran, Vinay Kumar, Stanley L. Robbins, Robbins Pathologic Basis of

Disease, 4th ed. (Philadelphia: W.B. Saunders Company, 1989).




Walter Laqueur, ‘‘The Question of Judgment,’’ p. 535.


See Dorland’s Pocket Medical Dictionary, 26th ed.


Walter Laqueur, ‘‘The Question of Judgment,’’ p. 545.


Ernest R. May, Strange Victory: Hitler’s Conquest of France (New York: Hill and

Wang, 2000), pp. 458–459.


Geoffrey Vickers, The Art of Judgment: A Study of Policy Making (Thousand

Oaks, CA: Sage Publications, 1995), pp. 225–226.


Alexander L. George, Bridging the Gap: Theory and Practice in Foreign Policy

(Washington, DC: United States Institute of Peace Press, 1993), p. xx.


Michael Moss, ‘‘Mammogram Team Learns from Its Errors,’’ The New York

Times, 28 June 2002, p. A1. Also cited in Steven Rieber, ‘‘Intelligence Analysis

and Judgmental Calibration,’’ International Journal of Intelligence and

CounterIntelligence, Vol. 17, No. 1, Spring 2004, pp. 97–112.


Shannon Brownlee, ‘‘The Perils of Prevention,’’ The New York Times, 16 March

2003, p. 52. For more on the diversion of resources to address aspects of

prevention, see Gina Kolata, ‘‘Annual Physical Checkup May Be an Empty

Ritual,’’ The New York Times, 12 August 2003, p. 71.


Rick Weiss, ‘‘Cross-Pollination in Pursuit of Cures: NIH Launches Drive to

Increase Collaboration Among Scientific Disciplines,’’ The Washington Post,

1 October 2003, p. A2.


‘‘Malingering: Can It Be Detected?,’’ Med League Support Service Inc.

http:== <a href=”” rel=”nofollow”></a>=Articles=Medical%20Topics=Detecting Malingering.



David Brown, ‘‘Director Seeks ‘Just the Facts’ to Improve Medical Care,’’

The Washington Post, 5 February 2003, p. A2.


Agency for Healthcare Research and Quality Website: http:==<a href=”http://www.ahrq.go” rel=”nofollow”>www.ahrq.go</a>v=

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Communicating Uncertainty in

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Communicating Uncertainty in

Intelligence and Other Professions

Recent events have focused new attention on the need for intelligence

professionals to present alternative hypotheses to pol icymakers in a way

that makes clear the uncertainties in the evaluation and interpretation of

the evidence on which they are based, and the fact that it is rarel y possible

to exclude alternative explanations.


This information improves the ability

of decisionmakers, if they so wish, to ta ke into account the risk that

intelligence estimates may not be correct.

This problem is not unique to the intelligence profession. Experts from

many other fields face the problem of conveying technical judgments

involving uncertainty to their nonspecialist clients. Doctors, for example,

must routinely advise th eir pa tients a bout the ris ks inv olved in various

alternative treatments. Unlike doctors, however, intelligence analysts

cannot often support their judgments with statistical analysis of empirical

data derived from a large number of similar past cases.



A number of recent introspective works responding to recent intelligence

failures h ave called attention to the need for intelligence analysts to give

proper attention to hypotheses and data collection efforts that are contrary

to what they regard as the most likely interpretation of available

information, and especially to hypotheses that run counter to prevailing

Dr. Charles Weiss is Distinguished Professor and, until recently, Chair of

Science, Technology, and International Affairs at the Edmund A. Walsh

School of Foreign Service, Georgetown University, Washington, D.C. A

Harvard-trained biochemical physicist, he was the first Science and


to 1986.


International Journal of Intelligence and CounterIntelligence, 21: 57–85, 2008

Copyright # Taylor & Francis Group, LLC

ISSN: 0885-0607 print=1521-0561 online

DOI: 10.1080/08850600701649312


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models and preconceptions.


This reluctance to confront uncertainty has

parallels in science and medicine, both of which discourage interpretations

contrary to prevailing paradigms.

Like intelligence analysts, scientific advisors to policymakers have long

prided themselves on ‘‘speaking truth to power.’’


In prac tice, matters are

more complicated. In science advising as in intelligence analysis, ‘‘truth’’

may be probabilistic, and may depend on an advisor’s best educa ted guess

as to the outcome of experiments that have not yet been performed or the

interpretation of data that are not quite in point. Like intelligence

professionals, scientific advisors must adjust to the needs of their advisees,

who bear ultimate responsibility for their decisions.


Moreover, like most intelligence analysis, most scientific research is

concerned with filling gaps in existing paradigms; revolutionary concepts

require years to become established. In principle, this derives from the

dictum that ‘‘extraordinary claims require extraordinary evidence.’’ In

practice, scientists’ judgment re garding the quality of evidence often

depends o n how closely it fits their preconceptions.


Abandonment of a

fundamental paradigm may owe as much to the death or retirement of an

older generation of scie ntists as to the success of the new model in winning

them over.


Similarly, young doctors are advis ed to look for the most common

diagnosis before considering rare or exotic diseases: ‘‘When you hear

hoofbeats, think horses, not zebras.’’


They also learn to b e hesitant to

point out mistakes or disagreements with senior authority figure s—a

phenomenon well-known in other professions, such as pilots, and in

bureaucracies of all kinds. Nevertheless, these fields have well–established

procedures for identifying and highlighting less likely possibilities that

might undermine these key assumptions and for carrying out the tests

needed to eliminate (or possibly confirm) them. Doctors, fo r ex ample,

conduct tests intended to rule out possible but less likely diagnoses.


Many a scientific reputation has been established by a dramatic experiment

that overturned long-held preconceptions.

Environmental sc ientists are particularly alert to possib le surprises, and

emphasize research on indicators that could be the first signs of more

serious environmental damage than would be predicted by the hypothesis

deemed most likely in a particular situation. Extensive research is

underway, for example, to test for phenomena that would indicate an

increased likelihood of catastrophic sea level rise due to the melting of the

Antarctic ice shelf, or of the weakening of the Gulf Stream (and

consequent chilling of Western Europe) due to possible melting of the

Greenland icecap and c onsequent weakening or disruption of the ‘‘oceanic

conveyer belt.’’


Even so, these scientists have been criticized for

‘‘anchoring’’ on past estimates of climate change, and in particular for the




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relatively small change i n the consensus projections of global warming

despite the many scientific advances of the past decade.


Even the problem of deliber ate deception i s not unique to int elligence

analysis. A medical patient may be too embarrassed to share the complete

circumstances of an illness or injury. Fakery in scientific research—s uch as

the recent ‘‘ dry-labbin g’’ of human cloni ng by a Korean sc ientist



dealt with by peer review, and by the requirement that impor tant findings

be confirmed by independent researchers—the latter being typically

unavailable to intelligence practitioners. Environmentalists, somewhat like

intelligence analysts, sometimes face disinformation put out to the public,

in this case by opponents of one or another regulation. Scientists detect

such disinformation rather easily, but often have difficulty refuting them

convincingly before a general audience.


The resulting frustration

resembles that felt by intelligence analysts—or their policymaker clients—

when they cannot refute misinformation in the press.

The Intelligence Community (IC) has de veloped many devices to attack

the problem of unexpected surprises, including t he use of ‘‘red teams’’ to

attack the assumptions underly ing conventional analysis.


One of the

most respected analysts of the intelligence profes sion, Richards Heuer, has

proposed a method of ‘‘Analysis of Competing Hypotheses’’ (ACH), which

‘‘requires the analyst to explicitly identify all reasonable alternatives and

have them compete against one another for the analyst’s favor, rather than

evaluating their plausibility one at a time.’’


Heuer’s method seeks to

distinguish ‘‘key drivers’’ that a re ‘‘ diagnostic’’ in the sense that they

‘‘influence your judgment on the relative likelihood of the various



In this way, the ACH method forces the analyst to ‘‘begin

with a full set of alternative hypotheses, to identify the few items of

evidence or assumptions that have the greatest diagnostic value in judging

[their] relati ve likelihood,seeking evidence to refute hypothese s [rat her

than] looking for evidence to confirm a favored hypothesis.’’



elaborate, but less user-friendly, versions of this technique employ

Bayesian statistics to assign probabilities to each alternative.


Now that

the National Intelligence Strategy has identified ‘‘exploring alternative

analytic views’’ as one of the ten major ‘‘enterprise objectives’’ of the

national intelligence effort, the use of these methods may become more

common in the future.


Read the whole story


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