Classification: UNCLASSIFIED

Classification: UNCLASSIFIED

How Analysts Attain Insight: 

The Benefits and Opportunities

Adrian Wolfberg, Ph.D.

Policymakers call upon intelligence analysts to deliver insightful 

assessments, yet consistent success has faltered due to a lack of 

understanding of the insight process and insufficient institutional 

emphasis on insight. This Research Short reports the results of a 

scientific study that explains the IC analysts’ insight process and its 

benefits, and provides opportunities for overcoming these dilemmas.

RESEARCH SHORT

CATALYST Designed to spark positive conversations

on the future of IC intelligence

March 28, 2022

What this is:

This report is the product 

of academic research. As the 

IC’s university, NIU is uniquely 

positioned to use academic 

approaches to research—and 

report on—subjects of interest 

to the community.

What this is not:

This is not finished intelligence. 

The opinions expressed in this 

report are solely the author’s 

and not those of the National 

Intelligence University or any 

other U.S. Government agency.

IMAGE FROM SHUTTERSTOCK
2

Why Do We Need Analysts To Be Insightful?

The practice of intelligence analysis—meant to protect against external threats and to leverage 

opportunities—frequently brings analysts face-to-face with novel problems, i.e., high-stakes 

challenges that pose the highest risks. In the national security arena, intelligence analysts have 

an especially demanding task because foreign adversaries—who pose threats but may also offer 

mitigating opportunities—neither transparently nor willingly provide all the information needed 

for risk and opportunity analysis. This is especially important when faced with novel situations 

that require a new understanding of what and how things relate and, therefore, require insightful 

analysis.1 In our complex and ambiguous world, insight is no longer a nice-to-have option; it is 

a critical necessity, and the Intelligence Community (IC) must do better than hope for insight.

Colloquially, the word insight, which comes from the Old Dutch, means seeing inside.

2 Ideas 

that are considered insightful are those that shed light on the inner nature of a person, thing, 

behavior, or situation.3 Such insights occur through an individual’s cognitive and emotional 

processing and include an unrecognized fundamental truth, a new view about the world that 

challenges the old view, an observation that is considered a deep understanding, or a revelation 

of hidden motivations that influence an individual’s feelings, behaviors, and actions.4 This is 

why policymakers value insightful knowledge products so highly.5

This Research Short asks the reader to enter unfamiliar terrain as it opens the “black box” of 

the insight process and four types of insight benefits. Although the need for analytic insight 

has been explored in literature tied to public policy6 and national security policy7 by academics 

with8 and without an intelligence background,

9 intelligence professionals,10 and think tanks,11

the process of how insight emerges in analysts and the knowledge of when insight has occurred 

have not been systematically investigated or understood. The field within the intelligence 

analysis domain is uncharted.

The Insight Process

Individuals who solve novel problems provide a unique real-world opportunity to inquire into 

the emergence of insight. 12 To better understand the insight process within the IC, 36 

intelligence analysts—recognized by their supervisors for having experienced insight—were 

interviewed about their experiences solving novel problems (details about the research method 

are provided in the Appendix). This study has 

identified three key phases: trigger and 

emergence, which lead to the insight benefits 

(see Figure 1). A more in-depth exploration of 

the insight process and the implications of 

this study for the IC appears in the Research 

Monograph, In Pursuit of Insight: The Everyday 

Work of Intelligence Analysts Who Solve Real 

World Novel Problems.

Figure 1. Phases Leading to Insight
3

Trigger Phase

The trigger phase begins with an initiating event that, seemingly by chance, brings the analyst’s 

attention to a particular problem to address; alternatively, after an analyst has been working on 

a given problem, a random event contributes to focusing their attention more intently on the 

problem. Entering into and navigating through the trigger phase takes cognitive and emotional 

courage on the analyst’s part. This phase consists of four elements: unpredictability, problem 

finding, novel problem type, and conflicting representations. 

Unpredictability: Personal events unexpectedly lead to an encounter with a novel problem or, 

to a lesser degree, to the way the analyst’s insight path unfolds. For example, an analyst who 

works at headquarters visits a field site, sees an analytical tool used for a different purpose than 

the analyst’s visit, and then is able to conceptualize how such a tool could help address the 

novel problem.

Novel Problem Finding: Because a novel problem is, by definition, one that an analyst has not 

previously experienced, solved, or made significant progress toward solving, the nature of the 

problem is uncertain, and its framing does not fit with the views of others. This uncertainty can 

raise questions about assumptions that analysts previously have made about the topic; possibly 

relevant factors not earlier considered; overcoming externally or internally imposed constraints;

and figuring out a detected activity when the situation is not clear. For example, an analyst has 

initially framed an approach to an issue based on a particular assumption, but exposure to an 

alternative framework leads the analyst to wonder if a different set of assumptions could better 

frame the issue.

Novel Problem Type: Two types of novel problems exist: prediction and mystery. Prediction 

problems attempt to understand something that is going to happen or might happen in the future, 

and typically seek to answer “how” or “under what conditions” questions. For example, how will 

an adversary fight? Mystery problems occur in the present, but not enough information is likely 

ever to be known by analysts to answer them definitively. These problems typically seek to answer 

“why,” “how,” or “where” questions. For example, where is the adversary hiding its weapons? 

Conflicting Representations: How an analyst understands a novel problem and what approach 

should be used to solve it (i.e., problem representation) typically do not fit within the views of 

others who have not yet been exposed to or worked on the novel problem. For example, with a 

prediction problem such as “where will the mobile missiles be located after they leave garrison,” 

an analyst represents the problem as a conceptual one that needs to be addressed with a new 

strategic paradigm. Others persist in applying existing strategies used to find missiles, which 

results in a conflicted representation of the problem.

Emergence Phase

After the trigger phase sets the starting conditions for insight, the emergence phase is the 

creative part of the insight journey—requiring an analyst’s persistence, openness, and selfawareness. This phase draws on two interrelated elements: internalized tensions and priming. 
4

Internalized Tensions: As analysts start working on a novel problem, they become aware of 

inconsistencies that can be cognition-based (i.e., inconsistencies between pairs of thoughts or 

ideas) or emotion-based (i.e., inconsistencies between an analyst’s action and interpretation of 

others’ reactions). Tensions induced by these inconsistencies can originate within the individual 

(i.e., self-initiated) or in the individual’s social environment (i.e., related to organizational 

structure and the behavior of others). An analyst who concludes that exploring a diversity of 

ways to represent a problem would lead to the most accurate assessment, while others judge that 

a standardized process would be best, is an example of cognition-based tension at the individual 

level. An analyst who presents a unique methodology in a detailed, transparent way to address 

skeptical concerns, while worried this could lead to being discredited in a production system that 

values standard product lines, is an example of emotion-based tension at the social level.

Priming: Analysts draw upon memories of past experiences unrelated to their present novel 

problem in order to make progress toward overcoming tensions and reaching insight. Priming 

sources also occur across the intersection of the emotion-cognition and individual-social 

dimensions. In an example of cognition-based priming at the individual level, an analyst who 

studied in graduate school how physical factors in the environment could trigger social or 

political outcomes applies that cause-and-effect knowledge to a national security novel 

problem. In an example of emotion-based priming at the social level, an analyst who had lived 

in a foreign country appreciates that even in countries where the same language is spoken, 

cultures can be very different.

The Obvious Insight Benefits

The insight phase flows from the trigger and emergence phases when the analyst reaches a unique 

understanding for the first time. As seen in Figure 2, this phase can produce four distinct insight 

benefits: understanding of novel problems, effective communication of complexity with others, 

self-reflection and greater awareness, and 

navigation of organizational politics and 

agendas. These benefits are arrayed across 

the intersections of the emotion-cognition 

and individual-social dimensions. 

Understanding of Novel Problems

This benefit (Figure 2, cell 1) represents a 

cognition-individual connection, in which 

the analyst gains a deeper understanding 

of the novel problem at hand. One of the 

36 intelligence analysts in the study 

described an insight reached when, by 

paying attention to new information about 

an adversary’s logistics trail, it became 

Figure 2. Four Types of Insight Benefits
5

clear that earlier patterns were shifting. Thinking about General Patton’s efforts to turn around 

his forces during World War II, the analyst began to view the logistics trail as a pyramid, with 

the lead force at the top and all the elements needed to support it below. Seeing the logistics 

trail as a work breakdown structure enabled the analyst to “get inside” the adversary’s mind, 

figuring out how and where units would deploy.

Effective Communication of Complexity with Others

This benefit (Figure 2, cell 2) represents a cognition-social connection, in which the analyst 

effectively communicates complex ideas with others in the analyst’s organization or external 

to the organization. For example, a junior analyst attended a meeting with more senior and 

experienced intelligence analysts to review plans for a U.S. military exercise and prospective 

reactions by a nearby adversary. As the group graphically outlined the history of perceived 

threats, this visualization led the analyst to realize that a more strategic consideration—a 

treaty—outweighed the planned military activity. As long as the signatories adhered to the 

treaty requirements, which the United States intended to do, the situation should remain calm. 

By clearly articulating the reasoning behind this insight, the junior analyst persuaded the 

experts in the meeting.

Self-Reflection and Greater Awareness

This benefit (Figure 2, cell 3) represents an emotion-individual connection, in which the 

analyst’s self-reflection results in greater self-awareness. One analyst, who understood the 

common need to have enough food to eat despite not having experienced deprivation, saw 

while deployed overseas that good people sometimes do bad things to provide food for their 

families. This experience changed the analyst’s assumption that only bad people do bad things, 

yielding the insight that good people may do bad things to achieve a greater good. Furthermore, 

the juxtaposition of seeing behaviors that are universal (e.g., how tribal elders love their 

grandchildren) with behaviors that to the analyst are not universal opened his mind to 

contextual factors that may foster contradiction. His improved understanding of complex 

behaviors—in effect, taking a more holistic view of a situation—subsequently deepened his 

analysis and increased his value to operational decisionmakers. 

Navigation of Organizational Politics and Agendas

This benefit (Figure 2, cell 4) represents an emotion-social connection in which the analyst has 

to navigate politics and agendas across cultures, whether the culture is that of the analyst’s 

employing organization and related organizations, or the culture of people in the world whom 

the analyst’s organization studies from a mission perspective. An analyst studying multiple 

related adversarial groups, which engage in the same type of threat behavior in a foreign 

country, conjectured that a key group was active—despite the absence of direct evidence—

because intelligence data showed the related groups were active. His assessment was dismissed 

by leadership within his organization and by policymakers interested in the activity. Observing 

that a clear separation between producer and consumer did not exist, even though the analyst’s 
6

belief system was based on such a separation, led to his insight about the potential effects of 

organizational and political agendas, including fuzzy boundaries due to overlapping interests 

between intelligence producers and consumers.13

Growing Insightful Analysts: The Not-So-Obvious 

Insight Opportunities

The examples of insight shared by the analysts interviewed for the study show that intelligence 

analysts with cognitive and emotional courage, as well as persistence, possess the building 

blocks—alone and within their social environment—to navigate the insight process. 

Broadening the pool of analysts meeting novel problems with insight across the IC, however, 

will require a deeper institutional commitment to supporting analytic insight. The dynamic 

between analysts and their institutional environment is critical to the emergence and sharing of 

insight, and the following recommendations are offered to heads of agencies and managers of 

both first-line managers and analysts. 

Recognizing Transformation Is Needed: Senior leaders of analyst managers should be 

guardians of the insight process. Developing an institutional leadership cadre who values a 

creativity climate and leads by example to foster insight is critical to building insightful 

analysts. As Robert E. Quinn, co-founder of the University of Michigan’s Center for Positive 

Organizations, has suggested, if the IC wants deep change (i.e., transformation) with regard to 

insight, then becoming familiar with and experiencing this unfamiliar territory is essential for 

managers and leaders.14

Understanding the Complexity of Insight: An organizational view of problem-solving as a 

routine, reproducible act is inadequate for interpreting the emergent behavior observed in novel 

problems. Often, analytic frameworks are built upon established and recognized known 

behavior, which is the antithesis for detecting and understanding the phenomenon of 

emergence.15, 16 As noted earlier, managers need to embrace the realization that novel situations 

challenging the IC require a new understanding of how things relate.17

Improving the Selection Process: Many public and private universities have intelligence analysis 

programs whose graduates join the IC. Working with the faculty at these institutions to identify 

foundational insight capabilities (e.g., courage, openness, and persistence) and the achievement 

of insight benefits in prospective candidates could strengthen IC recruitment and selection.

Tuning In to Self-Reflection: Because we cannot predict what specific past experiences may 

help solve a novel problem in an analyst’s future, analysts need a stockpile of diverse 

experiences and knowledge upon which to draw. Managers can foster the emergence phase by 

encouraging analysts to reflect on their past for any supportive memories that may help them 

tackle their internalized tensions. Developing a competency of self-reflection is necessary for 

analysts to understand both their own experiences and how theirs differ from the experiences 

of those they are analyzing. 
7

Leveraging Unpredictability: The unpredictability and uncontrollable nature of insight requires 

a mindset shift for managers of analytic production. Leaders must create time and space for 

insight to flourish in analysts, which can be a significant challenge in large organizations with 

hierarchical cultures that tend to emphasize order and control, as well as time sensitivity in 

responding to policy taskings. 

Exploiting Diversity of Benefits: Solving novel complex problems requires a diversity of 

insight benefits—not just the individual cognitive type that is usually associated with insight, 

which is depicted in “Understanding of Novel Problems” (Figure 2, cell 1). Each benefit type 

can have contributory value in solving novel problems. Managers should not dismiss the other 

three insight benefits; teams of analysts, through their interaction, can produce different types 

of benefits that collectively can contribute to solving novel problems.

Valuing Developmental Benefits: Analysts who have experienced insight not only contribute 

to the intelligence mission by solving novel problems, they also gain lifelong, personal benefits 

from the experience, which influence their intelligence career development. Insight should be 

viewed as both an organizational and individual developmental competency. Early tenure 

experiences with the diversity of insight types should be encouraged and fostered by managers 

so analysts grow comfortable with exploring the unknown. 

Integrating Human Insight with Artificial Intelligence/Machine Learning: Analysts take a 

relatively long time dwelling upon novel problems. They have to assess the new problem in 

the context of comparing what they and others think, and they have to assess the meaning of 

new behaviors. These are slow, iterative, self-reflective processes, in the words of Israeli 

psychologist Daniel Kahneman. 18 Artificial intelligence and machine learning, while 

producing fast quantitative capabilities that support foundational analysis, have a difficult time 

with abstract, deliberative thinking.19 How insight and AI/machine learning can be integrated 

remains an area of future research.

Adrian Wolfberg, Ph.D., is a senior research fellow in NIU’s Caracristi Institute for Intelligence Research. 

His research focuses on knowledge transfer, decisionmaking, decision conflict, organizational learning, 

creativity, organizational and temporal boundaries, and boundary crossing.

If you have comments, questions, or a suggestion for a Research Short topic or article, please contact 

the NIU Office of Research at NIU_OOR@dodiis.mil.
8

Appendix: Research Method

A review of three approaches that have typically been used to study insight—experimental, 

observational, and historical—made it clear that a different approach was needed to study 

insight emergence in intelligence analysts. For example, experimental techniques, which use 

controlled conditions on one or two variables while removing confounding variables,20 give 

participants tasks that are simple and of short duration (e.g., solving a puzzle),21 which do not 

meet the bar of the complex novel problems that IC analysts face. Observational approaches 

attempt to study insight in real-world conditions, which is challenging because it is difficult to 

predict when insight will occur22 and many factors are at play.

23 Historical efforts draw on 

interviews with individuals in full-time creative professions who have been publicly 

recognized for their insight such as Nobel Prize winners,24 research on notables such as Charles 

Darwin,25 or research on how experts such as firefighters, aircrew cockpit personnel, surgical 

teams, etc. have performed during critical incidents.26

What Is Known in Academic Research?

Four seminal information processing-based theories, which represent the current body of 

knowledge on how insight emerges, provided a starting framework for exploring analytic 

insight—even as they did not explain how insight emerges in intelligence analysts or the types 

of insight that emerge. These theories include emergence as a phenomenon at the differential 

interaction of two dimensions: the emotion-cognition dimension and the individual-social 

dimension. In cognitive scientist Stellan Ohlsson’s theory, insight emerges in an individual 

through the cognitive restructuring of the problem.27 In U.S. psychologist Gary Klein’s theory, 

insight emerges in an individual through the cognitive changing of the narrative that takes place 

in one’s mind.28 For Hungarian-American psychologist Mihaly Csikszentmihalyi and R. Keith 

Sawyer, insight emerges in the individual and in the individual’s social environment through 

the cognitive activity of incubation.29 In British organizational behaviorist Eugene SadlerSmith’s theory, insight emerges in an individual through the emotional and cognitive activity 

of intimation.30

Theoretical Lenses to This Study

Drawing on the academic literature, two foundational approaches were used in the study of the 

emergence of insight in intelligence analysts. First, an information processing approach was 

applied, which includes how individuals alone or in social situations process information, how 

they take it in, consider and synthesize it, and use it. The second approach involved the 

differential roles that emotion and cognition play in insight. Emotion and cognition are 

connected, influenced by our past experience and by our anticipation of the future. 31

Phenomena can have both emotional and cognitive components, such as intuition and trust.32

Emotion includes motivation, passion, intentionality, feeling, courage, risk-taking, altruism, 

openness, surprise, etc. 33 Cognition includes attention, decisionmaking, categorization, 

patterns, comprehension, reasoning, inferences, etc.34
9

Interviews with Intelligence Analysts

Because there are no formal means for recognizing insight in intelligence analysts, a threephase approach was used to identify intelligence analysts who have been informally recognized 

for being insightful. Because research has shown that crises are not conducive to insight 

because of the negative and interacting effects that information overload and ambiguity have 

on attention,35 executives in intelligence organizations not involved in a crisis and who value 

insight in analysts were contacted. These executives recommended 44 analysts recognized as 

having experienced insight, of whom 36 were interviewed.

The analysts came from three kinds of organizations: intelligence agencies, including the CIA, 

DIA, NGA, and ODNI; executive departments with offices of intelligence, including Energy 

and Treasury; and intelligence directorates within military organizations, including 

CYBERCOM, EUCOM, SOUTHCOM, STRATCOM, and the Joint Staff/J2. Their experience 

ranged from less than 1 year to almost 40 years, with most evenly distributed between 1 and 24 

years, and their service spanned various settings: military, civilian, commercial, and 

combinations of these three. The analysts specialized in a variety of disciplines: military forces, 

international relations, science and technology, finance, data analytics, analytic tradecraft, 

infrastructure, public health, and strategic warning. Of the 36 analysts, 34 had an undergraduate 

degree, most in the social sciences followed by the physical sciences, and of these 34, 28 also 

had 1 or more graduate degrees. Gender distribution was about one-third female and two-thirds 

male, which is fairly representative of the gender distribution of intelligence analysts in the IC.36 

Data Analysis

To analyze the interview data, a qualitative coding technique called grounded theory was 

applied, using both inductive and deductive approaches. The technique involved four levels of 

coding: codes indicating the interpretation of words, phrases, and sentences based on the 

research question; categories that grouped similar codes; themes, which were abstractions 

derived from the literature based on the relevance of the categories to the research question; 

and assertions, which synthesized the findings. The number of elements in each step was 1,421 

codes, 66 categories, 11 themes, and 4 assertions.

Analysts described the duration of their insight experience from the time they first paid 

attention to a problem until the solution was reached. The timescale for insight stories ranged 

typically between 1 and 3 years, with a mean duration of 16 months and a standard deviation 

of 10 months. Analysts selected the most meaningful insight experience to share and a large 

portion took place at the beginning of their careers. Nearly 50 percent of the analysts selected 

an insight experience that took place during the first three years of their careers, yet only about 

15 percent of the analysts interviewed had three years or less experience, suggesting managers 

should foster early tenure experiences with insight—encouraging analysts to explore the 

unknown before they adjust to organizational norms.
10

Endnotes

1 James G. March, The Ambiguities of Experience (Ithaca, NY: Cornell University Press, 2010), 75; Dean K. 

Simonton, Origins of Genius: Darwinian Perspectives on Creativity (New York, NY: Oxford University Press, 

1999), 27-40.

2 Mihaly Csikszentmihalyi and Keith Sawyer, “Creative Insight: The Social Dimension of a Solitary Moment,” in 

The Nature of Insight, ed. Robert J. Sternberg and Janet E. Davidson (Cambridge, MA: MIT Press, 1995), 329-63.

3 Csikszentmihalyi and Sawyer, “Creative Insight.”

4 Jonathan Dalton, “What is Insight? The Five Principles of Insight Definition,” Thrive, March 28, 2016, 

https://thrivethinking.com/2016/03/28/what-is-insight-definition/.

5 Loch K. Johnson, “Glimpses into the Gems of American Intelligence: The President’s Daily Brief and the 

National Intelligence Estimate,” Intelligence and National Intelligence 23, no. 3 (2008): 330-70, https://doi.org/

https://doi.org/10.1080/02684520802121257. 

6 Thomas H. Kean and Lee Hamilton, The 9/11 Commission Report: Final Report of the National Commission on 

Terrorist Attacks upon the United States (Washington, DC: U.S. Government Printing Office, 2004), 339, 

https://www.9-11commission.gov/report/; Laurence H. Silberman and Charles S. Robb, The Commission on the 

Intelligence Capabilities of the United States Regarding Weapons of Mass Destruction (Washington, DC: U.S. 

Government Printing Office, 2005), 560, https://www.govinfo.gov/app/details/GPO-WMD. 

7 Executive Order 12333: United States Intelligence Activities, as amended by Executive Order 13470, July 30, 

2008, https://www.archives.gov/federal-register/codification/executive-order/12333.html; Office of the Director of 

National Intelligence, National Intelligence Strategy of the United States of America 2019, January 2019, 

https://www.dni.gov/files/ODNI/documents/National_Intelligence_Strategy_2019.pdf.

8 Stephen Marrin, “Is Intelligence Analysis an Art or a Science?,” International Journal of Intelligence and 

Counterintelligence 25, no. 3 (2012): 529-45, https://doi.org/10.1080/08850607.2012.678690; Itai Shapira, 

“Strategic Intelligence as an Art and a Science: Creating and Using Conceptual Frameworks,” Intelligence and 

National Security 35, no. 2 (2020): 283-99, https://doi.org/10.1080/02684527.2019.1681135. 

9 Gary Klein and Andrea Jarosz, “A Naturalistic Study of Insight,” Journal of Cognitive Engineering and Decision 

Making 5, no. 4 (2011): 335-51, https://doi.org/10.1177%2F1555343411427013; Daniel J. Zelik, Emily S. 

Patterson, and Janet E. Miller, “Measuring Attributes of Rigor in Information Analysis,” in Macrocognition 

Metrics and Scenarios: Design and Evaluation for Real-World Teams, ed. Daniel J. Zelik, Emily S. Patterson, and 

David D. Woods (Aldershot, UK: CRC Press, 2018), 65-84. 

10 David T. Moore and Lisa Krizan, “Core Competencies for Intelligence Analysis at the National Security Agency,” 

in Bringing Intelligence About: Practitioners Reflect on Best Practices, ed. Russell G. Swenson (Washington, DC: 

Joint Military Intelligence College Press, 2003), 95-132.

11 Kenneth Lieberthal, The U.S. Intelligence Community and Foreign Policy: Getting Analysis Right (Washington, 

DC: Brookings Institution, 2009), https://www.brookings.edu/wp-content/uploads/2016/06/09_intelligence

_community_lieberthal.pdf.

12 Robert J. Sternberg, “A Three-Facet Model of Creativity,” in The Nature of Creativity, ed. Robert J. Sternberg

(Cambridge, UK: Cambridge University Press, 1988), 125-47.

13 Nancy Katz et al., “Network Theory and Small Groups,” Small Group Research 35, no. 3 (2004): 307-32, 

https://doi.org/10.1177%2F1046496404264941. 

14 Robert E. Quinn, Deep Change: Discovering the Leader Within (San Francisco, CA: Jossey-Bass Publishers, 

1996), 134-43.

15 Peter A. Corning, “The Re-emergence of ‘Emergence’: A Venerable Concept in Search of a Theory,” Complexity

7, no. 6 (2002): 23, https://doi.org/10.1002/cplx.10043.

16 Daniel Javorsek II and John G. Schwitz, “Probing Uncertainty, Complexity, and Human Agency in Intelligence,” 

Intelligence and National Security 29, no. 5 (2014): 639-54, https://doi.org/10.1080/02684527.2013.834218. 

17 March, The Ambiguities of Experience, 75.

18 Daniel Kahneman, Thinking, Fast and Slow (New York, NY: Farrar, Straus and Giroux, 2011).

19 Zigfried Hampel-Arias and John Speed Meyers, “What AI Can and Cannot Do for the Intelligence Community,” 

Defense One, January 5, 2021, https://www.defenseone.com/ideas/2021/01/what-ai-can-and-cannot-dointelligence-community/171195/.
11

20 Stellan Ohlsson, “The Dialectic between Routine and Creative Cognition,” in Insight: On the Origins of New Ideas, 

ed. Frederic Vellee-Tourangeau (New York, NY: Routledge, 2018), 8-29.

21 Eva V. Hoff, “Imagination,” in Encyclopedia of Creativity, vol. 1, ed. Mark A. Runco and Steven R. Pritzker 

(Cambridge, MA: Academic Press, 2020), 617-23.

22 Eugene Sadler-Smith, “Wallas’ Four-Stage Model of the Creative Process: More than Meets the Eye,” Creativity 

Research Journal 27, no. 4 (2015): 342-52, https://www.tandfonline.com/doi/abs/10.1080/10400419.2015.1087277.

23 Antonio Damasio, Descartes’ Error: Emotion, Reason, and the Human Brain (New York, NY: Penguin Books, 

1994), 128-30.

24 Csikszentmihalyi and Sawyer, “Creative Insight;” Albert Rothenberg, Flight from Wonder: An Investigation of 

Scientific Creativity (Oxford, UK: Oxford University Press, 2015), 74.

25 Simonton, Origins of Genius, 27-40.

26 Klein and Jarosz, “A Naturalistic Study of Insight.”

27 Stellan Ohlsson, “Information-Processing Explanations of Insight and Related Phenomena,” in Advances in the 

Psychology of Thinking, ed. Mark T. Keane and Kenneth J. Gilhooly (Hempstead, UK: Harvester Wheatsheaf, 

1992), 1-44; Ohlsson, “The Dialectic between Routine and Creative Cognition.”

28 Gary Klein, Seeing What Others Don’t: The Remarkable Ways We Gain Insights (New York, NY: Public Affairs, 

2013), 104.

29 Csikszentmihalyi and Sawyer, “Creative Insight.”

30 Sadler-Smith, “Wallas’ Four-Stage Model of the Creative Process.”

31 Antoine Bechara, Hanna Damasio, and Antonio Damasio, “Emotion, Decision Making and the Orbiotfrontal Cortex,” 

Cerebral Cortex 10, no. 3 (2000): 295-307, https://doi.org/10.1093/cercor/10.3.295; Damasio, Descartes’ Error.

32 Rothenberg, Flight from Wonder; Daniel J. McAllister, “Affect- and Cognition-Based Trust as Foundations for 

Interpersonal Cooperation in Organizations,” Academy of Management Journal 38, no. 1 (1995): 24-59, 

https://doi.org/10.5465/256727.

33 Rothenberg, Flight from Wonder.

34 Ohlsson, “The Dialectic between Routine and Creative Cognition.”

35 Adrian Wolfberg, “How Information Overload and Equivocality Affect Law Enforcement Intelligence Analysts: 

Implications for Learning and Knowledge Production,” Journal of Intelligence & Analysis 23, no. 1 (2017): 17-35.

36 Government Accountability Office, Intelligence Community: Additional Actions Needed to Strengthen 

Workforce Diversity Planning and Oversight (Washington, DC: Government Accountability Office, 2020). 

https://www.gao.gov/assets/gao-21-83.pdf.