Ten years from now the job of the intelligence analyst will have been transformed. Technological changes—both new technologies that can be used to conduct analysis and risks related to technologically based activities and communications around the world—are virtually inevitable. What is not inevitable is that the Intelligence Community (IC) will adapt to these changes in the most productive ways. The central argument of this report is that integrating the understanding of human beings and social processes that comes from social and behavioral sciences (SBS) research into the analyst’s work as it evolves in the coming decade will be critical. It is this knowledge base that will enable the IC to develop technological supports that are both proactive and interactive and can effectively augment the capacities of human analysts and, more broadly, to respond effectively to the security threats of the coming decades. Capitalizing on the power of research that integrates the insights from SBS research with what technology makes possible will require a fundamental commitment by the IC.
Consider the daily activities of an individual analyst. An analyst’s workday begins with an inventory of key questions for which she is responsible (see Chapter 4), and that is not likely to change. Today, an analyst may have a running list of such questions, supplemented each day through a review of news feeds, emails, conversations, or written messages. Ten years from now, an individual analyst will likely work with an artificial intelligence (AI) agent that will continuously monitor sources of information relevant to the
analyst’s inventory of questions and identify anomalies that may indicate new areas about which inquiry is warranted. This technological support will enable the analyst to spend much less time getting updated on current events, and more time looking for emergent trends in data and identifying optimal intervention points and policy opportunities for decision makers.
The key questions of the day for an analyst frequently include specific queries from policy makers about developing events. In the future, White House officials and other national security experts are also likely to have AI agents that highlight key developments based on priorities set by algorithms that reflect the concerns for which those individuals, in turn, are responsible. These AI agents will uncover connections and circumstances that sharpen the questions they relay to analysts.
The analyst of the future who participates in the scenario presented in Chapter 4 receives questions from the White House about the activities of terrorist group Z in country Y, located in the region for which she is responsible. The questions from the White House suggest a direction that needs exploration, so the analyst and colleagues identify particular aspects of current social media traffic about which further analysis is needed.
Through AI real-time processing of large amounts of data, the analyst has access to a continuously updated compilation of emergent narrative themes in the flow of social media information with potential relevance to her account, but it is up to her and her human colleagues to identify the most intriguing themes, those worthy of further exploration and analysis. This analysis comes in the form of an interactive graphic display; the analysis team has requested highlights from new narrative threads, the emotional intensity of the dialogue about threads that have been flagged, and the source of those threads. The interactive graphical display shows connections between the relatively closed network of chat rooms associated with terrorist group X and other networks. The analyst can click on links to learn more about the nature of the other networks, the geographic range of their members, how the connections were forged, and the key narratives being promulgated by each network.
The analyst’s personal AI agent, which has already stored a significant amount of information about her responsibilities and mode of working, notifies her that another analytic team has requested a similar analysis, and suggests contact with that group. It also offers her data maintained by a third team, whose account has to do with monitoring of weapons shipments around the globe, because that group has recently logged a change in transit points, bringing a particular supply chain closer to the region she monitors. The system also prompts her on whether it would be helpful to have an analysis of recent news coverage of elections in country X, which borders country Y. The system notes that the amount of Internet chatter from one of the terrorist networks in her region of responsibility has escalated and may
signal an impending threat. Her AI agent reminds her of her most persistent cognitive biases and blind spots, and recommends involving colleagues who complement her cognitive profile.
When the analyst brainstorms with her team of colleagues, they determine that the political developments are not likely relevant to the question about terrorist group Z’s current activities, applying deep knowledge and instincts that only human beings could have. One colleague who was recently stationed in the region knows that the elections are tightly controlled by the ruling regime, which is separate from the terrorist group. Because a serious and years-long drought in the area may be contributing to instability, the analytic team begins to investigate whether terrorist group Z may have become involved in black market activities associated with the water supply. The AI agent identifies recent published anthropological field research about the region that might guide the development of new lines of research and analysis. Social media analytics reveals that some of the narratives being promoted by the terrorist group are aimed at undermining the current regime; the terrorist group is using sophisticated bots to spread images and stories suggesting that the regime is denying water to particular groups.
The analyst realizes that the new line of analysis that has emerged is important enough that others in the national security community should be alerted. After a first-draft assessment of the situation has been generated by the AI agent, she refines the text and adds software-generated visualizations that are easier for her colleagues and clients to digest. The creation of the assessment triggers automated processes that elevate the warnings associated with terrorist group Z and provides clients with a visual cue that new analytic assessments are forthcoming.
Reliance on SBS research is embedded is almost every line of this portrait of the future, which is based on the premise that the IC has taken advantage of research discussed in this report. There is little doubt that the IC can expect new tools and types of data—and new security challenges—to alter the way intelligence analysis is carried out. SBS research offers the IC important opportunities to shape the way it responds to these changes. The opportunities described in this report offer the potential for
- stronger intelligence assessments;
- tools and technologies optimally designed for human use and human–machine interaction; and
- strengthened readiness to confront evolving security threats.
The research described in this report can support the development of intelligence assessments that will be richer 10 years from now because of the capacity to make use of new types of information and analyze existing types of information in new ways. For example, the analyst may be able to draw on new types of information—such as digital trace data that simultaneously reveal patterns in social media discourse and live interactions, models of interactions between social networks and political ideology, and analysis using natural language processing—which will improve his capacity to conceptualize and quantify cultural phenomena. Technology is making it possible to identify patterns in large datasets and integrate different sorts of data, including video and audio data and other visual representations; SBS research is providing the essential theoretical and empirical basis for designing and using these sophisticated methodologies to make the data meaningful and enrich the analyst’s understanding of the social and political worlds.
Assessments may be more nuanced. Technology that is grounded in foundational SBS research may enable analysts to identify intersections and see connections that humans alone could not have detected. Analysts may be able to assess complex phenomena and developments more systematically, for example, and to discern more easily the way an incident or piece of information fits—or may influence—a larger context. This technological augmentation of a human’s capacity to synthesize multiple types of data and to visualize and communicate complex findings may facilitate more nuanced understanding of the developments analysts track, and also support forecasting from a sociocultural perspective to facilitate more robust assessments of future possibilities.
Assessments may be more accurate and efficient. The methodologies and tools described in this report may allow for faster processing of large volumes of data, integration of multiple kinds of data, and other forms of analysis and tracking that would be beyond the capacity of human analysts. These capabilities can make it possible to efficiently track regions, populations, groups, and sources of information, from news coverage and social media discourse to satellite imagery of troop movements. The analyst may have improved capacity to address probabilistic events and to anticipate a range of possible outcomes. Indicators useful for gauging changes in a political leader’s behavior, the developing strength of minority group’s influence, or the cohesiveness of networks within which toxic narratives are spreading may aid the analyst in avoiding surprises and lead him more swiftly to developments requiring attention. Advances in cognitive science and neuroscience may provide more reliable indications of whether someone is being persuaded than could be gleaned from that person’s self-report.
Advances in social cybersecurity may decrease the time needed to assess the veracity of narratives, making earlier identification of threats possible and allowing for more reliable assessments of how populations respond to events of interest.
Technologies that become operational in the coming decade and beyond will augment the capacities of the human in vital ways, which will necessarily change how human analysts use and interact with them. Insights from SBS fields are essential to the design and development of tools and technologies that
- take advantage of the strengths of both humans and machines;
- allow humans to collaborate productively with machine partners;
- support more rapid assessment and forecasting of human activity; and
- avoid serious unintended practical and ethical consequences.
SBS research offers insights on human capacities and limitations, how humans can interact effectively with machines, how humans and machines can collaborate as teams, and how machines can mimic and manipulate humans. These insights will be needed in the design of tools that use AI and machine learning in conjunction with social network analysis, which will likely be an important component of analysis. This work could also support the development of an ecosystem for intelligence analysis composed of human analysts and semiautonomous AI agents, operating on and through diverse social media and supported by other technologies. Such a team could, proactively and securely, reach across controlled-access networks and develop enhanced intelligence analyses by identifying patterns and associations in data more rapidly than humans alone could, doing so in real time and uncovering connections that previously would not have been detectable.
Whatever directions the IC takes in developing and procuring technologies to support intelligence analysis in the coming decade, it will surely rely on researchers and other experts, both those working within the IC and outside contractors; commercially available software programs; and other resources. The extent to which both basic and emerging SBS research is being incorporated into the planning, design, and use of the tools and methods used and purchased by the IC is not publicly known. Emphasis on this aspect of design is critical, however, because the technology used for analysis is only as strong as the understanding of the human behavior
it is being used to model or explain; insights from SBS fields will provide essential support for the procurement of valid and effective products from the private sector to support the analyst’s work.
In the coming decade, the United States will face security challenges that include complex shifts in political dynamics; threats to international structures that have been a force for stability; and new types of weapons, including weaponized uses of information—all in the context of the effects of global climate change (see Chapter 3). Insights from SBS research discussed in this report—including improved understanding of the nature of social networks and complex systems, emerging sociotechnical responses to social cybersecurity threats, evolving ways of influencing hearts and minds, and the development of radicalization and extremism—represent but a few of the SBS contributions that will be vital to the U.S. capacity to react effectively to these evolving threats.
The emergence of new threats in cyberspace—cyber-mediated changes in individual, group, societal, and political behaviors and outcomes—is already a profound challenge for the IC, one that can be expected to grow in scale and urgency in the coming decade. The developing field of social cybersecurity, which integrates methods from the social sciences, most notably social network analysis, with machine learning, natural language processing, and other technologies, is offering tools, tactics, procedures, and policies with which to assess, predict, and mitigate the impact of adversarial social cyberattacks. Further research in this area can augment the significant approaches to cybersecurity already in place within the IC by integrating SBS-based understanding of individual and social processes and supporting the development of a new set of techniques for open-source assessment and forecasting that are grounded in understanding of social processes and phenomena.
Finally, the IC can use research from the fields of industrial-organizational psychology and human resource development in strengthening the readiness of its workforce to meet the challenges of the coming decade. The IC’s procedures with respect to the selection and retention of its analytic workforce, analysts’ skill development, and other aspects of workforce management are classified. However, translational research is needed to identify the applications of a well-developed body of research and practice to strengthening the analyst workforce. Such work could, for example, yield detailed descriptions of those attributes most useful for the selection of individuals likely to be effective analysts; strengthen agencies’ capacity to retain the most effective analysts; foster an organizational climate conducive to trust, collaboration, and learning; and provide support
for a workforce exposed to significant stresses in both offline and cyber-mediated environments.
The ideas discussed in this report highlight the reality that technological and other developments in intelligence analysis that proceed without the benefit of SBS research are likely to be limited in their effectiveness or worse, to result in misleading or distorted analysis. We close the report with our broad conclusion about the research opportunities that show promise for the coming decade and a recommendation for strengthening ties between the IC and the research community.
We have described both specific ideas and broad areas of opportunity for the IC to consider as it sets priorities for research in the coming decade that can support growth and development in how the analyst workforce performs its functions and in how that workforce itself is nurtured. There are many important areas—such as linguistics, cultural anthropology, behavioral economics, and learning science—that we were unable to address in this decadal survey, which by its nature could highlight only a few among many promising ideas. It is only through sustained attention to the integration of SBS research into its work that the IC can begin to more systematically take advantage of the full range of what SBS research has to offer. The following conclusion expresses our key message to IC leadership as they set specific priorities for research in the coming decade.
CONCLUSION 10-1: Social and behavioral sciences (SBS) research offers a fundamental—indeed essential—contribution to the mission of the Intelligence Community (IC), a mission that requires understanding of what human beings do, how, and why. The research described in this report amply demonstrates the critical importance of
- interdisciplinary research—both foundational and applied and domestic and international—designed to take advantage of and integrate theory, methodology, and data from across SBS fields to yield new insights into human behavioral and social processes with relevance to national security;
- the integration of basic science and developing research on human behavior and social processes, as well as advances in computational methods for large-scale data analysis, with the expertise of the IC on analytic methods and challenges;
- the incorporation of a deep understanding of the IC’s challenges into the identification of research questions and hypotheses to be tested, as well as the design and execution of research;
- the integration of SBS insights into the design and engineering of technologically based analytic tools; and
- translational and applied work to establish the direct utility of SBS research findings for the IC.
This chapter’s overview of the research examined in this report demonstrates both the power of the opportunities SBS research offers for the IC and the extent of the challenge of fully taking advantage of these opportunities. These ideas come from an extremely diverse set of academic disciplines: there is no “field” of SBS. This long report addresses only a sampling of potentially relevant SBS research; the contributions to intelligence analysis represented by these opportunities—and the landscape of opportunities we could not discuss here—cannot be realized simply by adding features to existing programs. If SBS perspectives are not fully integrated into the IC’s thinking, they will bring limited benefit.
This report has described clear evidence of the IC’s attention to SBS research, and valuable mechanisms, such as the Defense Advanced Research Projects Agency (DARPA) and the Intelligence Advanced Research Projects Activity (IARPA) are in place that can sponsor, facilitate, and help the IC utilize this research. However, these efforts remain ad hoc in important ways. While many of the mechanisms in place are stable, others come and go; many valuable efforts are “one-offs.” The IC as a whole has not yet developed a means of systematically identifying opportunities in SBS research and ensuring that the potential applications of these opportunities to intelligence analysis are pursued.
Scholars have taken note of the gap between the information, ideas, and theories produced by academic researchers and the exigencies of applying that knowledge in the context of government service.1 This gap is evident across domains, but some work has addressed its significance for the production and use of intelligence analysis. Literature produced under the umbrella of intelligence studies has produced conclusions about the practice of analysis (see Chapter 4) but has had only limited influence because
1 An influential book that addresses these issues documents problems with the U.S. strategy in Iraq between 1988 and 1991 and suggests ways in which scholars might develop information that is easier to apply, and policy makers might make better use of available research (George, 1993; see also Desch, 2019).
Strengthening the relationship between the SBS community and the IC is a broad-based challenge that has no single solution, and we recognize that we are by no means the first group to focus on this important challenge. Chapter 9 reviews lessons to be drawn from past collaborations between academic researchers and the IC. Capitalizing on the research opportunities discussed in this report will require the IC to abandon procedures and ways of doing business that have been in place for a long time; we close the report with our suggestions regarding ways the IC can proactively build collaboration with SBS researchers into its work.
RECOMMENDATION 10-1: The leadership of the Intelligence Community should make sustained collaboration with researchers in the social and behavioral sciences a key priority as it develops research objectives for the coming decade. A multipronged effort to integrate the knowledge and perspectives of researchers from these fields into the planning and design of efforts to support intelligence analysis is most likely to reap the potential benefits described in this report.
As the key coordinator of the IC, the Office of the Director of National Intelligence (ODNI) can continue to play an important leadership role in fostering the critical ties. The committee had no empirical foundation on which to base specific recommendations about institutional structures within the IC, and future efforts will need to be considered in light of particular efforts currently under way. Whatever structures are chosen, effective interchange is likely to involve four key ingredients:
- Identifying and building on successful examples
- Strengthening bridges between the two communities
- Providing opportunities for analytic staff to build their knowledge of SBS research
- Drawing on the principles of human–systems integration
Identify and Build on Successful Examples
As early as 1968, the National Academies noted that bringing SBS research to bear on national problems required bridging the divide between the specialized expertise of researchers and the broad problems faced by government (National Research Council Advisory Committee on Government Programs in the Behavioral Sciences, 1968, p. 46). The Intelligence Community Associates program brings academic specialists together and provides a natural bridge to the SBS community. Other valuable efforts to
bridge the gap between the IC and academia have included the Future of Intelligence Analysis Project, a cooperative effort involving the University of Maryland’s Center for International and Security Studies and ODNI, which yielded a two-volume report (Lahneman, 2006). Scholars have made broad recommendations for improving understanding and cooperation, such as encouraging scholars to spend time working in agencies and also encouraging analysts to spend time in academia; boosting the contributions of think tanks, which play a useful role in linking research to practice; and redesigning academic programs focused on intelligence (Marrin, 2012).
There is, however, no one office within the IC whose primary function is to survey the SBS landscape for promising research. The Intelligence Community Associates program and other efforts to support collaboration are a valuable resource for the IC and provide the platform on which to build stronger collaboration. One promising approach is the development of communities of practice by “finding junctures where the interests of the communities overlap sufficiently to create significant benefits for both,” an objective recommended in a recent Institute for Defense Analyses report (Koonin et al., 2013). A few examples are highlighted in Boxes 10-1, 10-2, 10-3, and 10-4.
Strengthen Bridges Between the Two Communities
As discussed in Chapter 2, profound differences between the cultures of the IC and the SBS community reflect their differing missions. One prominent difference is in openness: academic researchers are accustomed to making their data and methods available to other researchers, having their hypotheses and work tested and reviewed, and so on. By contrast, intelligence analysts must work around the need for varying levels of classification.
Some SBS researchers have been reluctant to work on classified projects, which they perceive as placing restrictions on academic freedom, because of their scholarly commitment to open dissemination of research results, and universities have varying policies regarding the acceptance of contracts involving classified research (Goolsby, 2005). The IC worries about classified projects for other reasons, most notably because any expansion of access to classified materials creates the “potential for unintentional disclosure of sensitive intelligence or information about sources and methods” (National Research Council, 2011, p. 23, note 42). Some members of the IC have argued that making the most of open-source intelligence (OSINT) sources and SBS knowledge requires a culture shift, including addressing the problem of classification (Fingar, 2007). One specific illustration of the problem is the requirement that many agencies have for prepublication review and approval of publications derived from research funded by
these agencies, which can inhibit collaboration with SBS academics and may even cause grant proposals to be rejected by university institutional review boards.
Several approaches may be of use in addressing this challenge. For some research purposes, it may be as effective to use a parallel but unclassified source of data. For example, data that once were classified but were later declassified could be made available to the entire SBS research community for comparison of methods and results. It may also be that a review of classification policies by the IC, in consultation with scholars, regarding research needs and objectives could identify policies that could be modified in particular cases.
Apart from issues of classification, means of facilitating productive interactions can play a key role. Possibilities include regular meetings at which members of the two communities share thinking about connections between research issues of concern to the IC, increased funding for unclassified research relating to such issues, and means of continuously soliciting input from researchers and providing incentives for them to pursue topics of interest to the IC. Testbeds, such as the one described in Chapter 7, offer another possibility for forging connections. One advantage to this model, in which researchers and members of the IC collaborate to design, test, and evaluate new projects, is that it can allow researchers access to analysts and their data and tools. Such collaborations can be a venue for research that targets important aspects of the work of the analyst without requiring outside access to classified material.
Provide Opportunities for Analytic Staff to Build SBS Knowledge
Members of the analytic workforce bring a wide range of educational and other experiences when they join the IC. While many have studied or earned degrees in SBS fields, others have not. The nature of their job allows them little time for keeping up with developments in even a single academic field, and little of the classified training they receive is likely to focus on basic SBS research. The committee heard anecdotally of valuable opportunities for analysts to deepen their knowledge of SBS work, including opportunities to take college courses periodically, attend training seminars at conferences, take short courses offered by universities, and participate in training offered by the agencies.
Nevertheless, there is a need for mechanisms through which analysts can keep current on SBS research relevant to their work in focused ways. The volume of relevant SBS research increases continuously, and keeping up even with a single subspecialty relevant to IC concerns could be a full-time job. While individual analysts and institutional units pursue the objective of staying current, we are not aware of any process for ensuring that analysts
working in a particular area can remain abreast of research developments. Possibilities for the IC to consider include working groups developed for the purpose of addressing a particular problem set or theme with SBS dimensions that could allow analysts the opportunity to develop expertise in that area over time. By focusing on such a problem set or theme, the working group could both identify relevant work and pursue individual interests while collaborating with others to build the expertise of the group, establishing themselves as a resource for others. The use of challenge problems, datasets, and artificial social media environments could, for example, support the development and testing of new theories and technologies for cybersecurity.
Other options include the use of such arrangements as the Intergovernmental Personnel Act (IPA) Mobility Program2 and internship opportunities for Ph.D. candidates that would allow SBS researchers to spend time in the IC and analysts to spend time in academic settings. Such options would require that onerous clearance and classification review constraints be relaxed.
The development of expertise in relevant SBS research could be treated as a core responsibility, and rewarded accordingly. All of these efforts would have the additional benefit of helping researchers build their understanding of the IC.
Draw on the Principles of Human–Systems Integration
Finally, the SBS research identified in this report as relevant to national security is in different stages of operational readiness. Some is still in the basic science stage; some (e.g., many of the ideas for the analyst workforce) is close to translation; and early versions of other research (e.g., social network methods) are in use by the IC. In some cases, new research conducted in the IC context will be needed to assess interventions found to improve teamwork in other settings. Evidence from other contexts for the effectiveness of various interventions can be used as a starting point for the development of interventions for the security community that will need to be tested in the security context.
Once basic research has been evaluated for its applicability in the IC context, it can be translated into operational procedures, methods, or pol-
2 The IPA program allows for the temporary assignment of personnel between the federal government and outside organizations (e.g., state/local governments, universities, federally funded research and development centers). The Office of Personnel Management notes that although federal agencies do not take full advantage of the IPA program, it is particularly useful in filling positions that require special expertise (e.g., research scientists). The personnel are on detail to the federal agencies and remain employees of their home institutions. See https://www.opm.gov/policy-data-oversight/hiring-information/intergovernment-personnel-act/#url= Assignment for more information on the IPA program.
icies. This translation requires collaboration among scientists, engineers, analysts, and applied scientists who are adept at the process. The nature of some SBS research (e.g., that in social networks and social cybersecurity) is such that the basic research involves the codevelopment of operational procedures, methods, and theories. In such cases, translational research takes a very different form from that in other areas, such as team science and psychology. Moreover, much of the research that will need to be translated for the IC context in the coming decade will involve interactions among humans and machines, often through social media.
Human–systems integration, an approach developed in the early 20th century, draws on research from numerous SBS domains, including psychology, human factors, management, occupational health and safety, and human–computer interaction, to improve the development of sociotechnical systems (dynamic systems in which people, tasks, technology, and the environment interact throughout the stages of the work the system is to carry out). The goal of this approach is to develop a resilient and adaptive system and avoid unintended consequences (National Research Council, 2007). A human–systems integration approach helps ensure that operational solutions address the needs as well as the capabilities and limitations of the analyst, including limitations that derive from policy decisions.
Addressing the barriers that interfere with productive collaboration between the IC and the SBS community will require that both communities have realistic expectations; a shared understanding of what SBS research can offer; and an understanding of “the inherent limitations in providing simple, universally applicable answers to complex social science questions,” in the words of another National Academies committee, charged with examining the integration of SBS research into the weather enterprise (National Academies of Sciences, Engineering, and Medicine, 2017, p. 6). In 1968, the National Academies argued that bridging the gap between the behavioral sciences and the federal government “requires identifying positions of responsibility in the government where an understanding of the behavioral sciences is essential” (National Research Council Advisory Committee on Government Programs in the Behavioral Sciences, 1968, p. 47).
The IC has unmistakably recognized the importance of SBS research, as its request for the present study demonstrates. Such efforts as the inventory of in-house SBS expertise conducted by ODNI in the wake of the 9/11 Commission Report are further evidence of that commitment (Fingar, 2011). Most recently, the director of national intelligence released a formal strategy for taking advantage of AI and other technologies to augment intelligence, which addresses the importance of “basic research focused
on sense-making” and strengthening collaboration between the IC and research institutions (Office of the Director of National Intelligence, 2019, pp. v and 12). Academic institutions could contribute to the IC–SBS collaboration by devoting greater attention to translational research, supporting the operationalization of tools from the SBS community, and applying SBS research findings to national security needs. The continued strengthening of the IC workforce and the technological systems it needs will depend on interdisciplinary approaches in which the insights and ideas of SBS researchers are fully integrated with the needs and objectives of the IC.
Adler, R. (2001). The crystal ball of chaos. Nature, 414(6863), 480–481.
Desch, M.C. (2019). Cult of the Irrelevant: The Waning Influence of Social Science on National Security. Princeton, NJ: Princeton University Press.
Fingar, T. (2007). Remarks and Q&A by the Deputy Director of National Intelligence for Analysis & Chairman, National Intelligence Council. Available: https://www.dni.gov/files/documents/Newsroom/Speeches%20and%20Interviews/20070717_speech_3.pdf [December 2018].
Fingar, T. (2011). Analysis in the U.S. Intelligence Community: Missions, masters, and methods. In B. Fischhoff and C. Chauvin (Eds.), Intelligence Analysis: Behavioral and Social Scientific Foundations (pp. 21–22). Washington, DC: The National Academies Press.
George, A.L. (1993). Bridging the Gap: Theory and Practice in Foreign Policy. Washington, DC: United States Institute of Peace Press.
Goldstone, J.A. (2001). Toward a fourth generation of revolutionary theory. Annual Review of Political Science, 4, 139–187. doi:10.1146/annurev.polisci.4.1.139.
Goldstone, J.A., Bates, R.H., Epstein, D.L., Gurr, T.R., Lustik, M.B., Marshall, M.G., Ulfelder, J., and Woodward, M. (2010). A global model for forecasting political instability. American Journal of Political Science, 54(1), 190–208.
Goolsby, R. (2005). Ethics and defense agency funding: Some considerations. Social Networks, 27(2), 95–106.
Hare, N., and Coghill, P. (2016). The future of the intelligence analysis task. Intelligence and National Security, 31(6), 858–870. doi:10.1080/02684527.2015.1115238.
Johnson, L.K. (2000). Bombs, Bugs, Drugs, and Thugs: Intelligence and America’s Quest for Security. New York: New York University Press.
Koonin, S.E., Keller, S.A., Shipp, S.S., Allen, T.W., and Walejko, G.K. (2013). Pathways to Cooperation Between the Intelligence Community and the Social and Behavioral Science Communities. IDA Paper P-5000. Arlington, VA: Institute for Defense Analyses.
Lahneman, W.J. (2006). The Future of Intelligence Analysis, Volume I. Final Report. College Park: The Center for International and Security Studies at Maryland.
Marrin, S. (2012). Is intelligence analysis an art or a science? International Journal of Intelligence and Counterintelligence, 25(3), 529–545. doi: 10.1080/08850607.2012.678690.
McMurtrie, B. (2014). Scoping out the future. Chronicle of Higher Education, October 13. Available: https://www.chronicle.com/article/Scoping-Out-the-Future/149271 [December 2018].
National Academies of Sciences, Engineering, and Medicine. (2017). Integrating Social and Behavioral Sciences within the Weather Enterprise. Washington, DC: The National Academies Press. doi:10.17226/24865.
National Research Council Advisory Committee on Government Programs in the Behavioral Sciences. (1968). The Behavioral Sciences and the Federal Government. Washington, DC: National Academy of Sciences.
National Research Council. (2007). Human–System Integration in the System Development Process: A New Look. Washington, DC: The National Academies Press. doi:10.17226/11893.
National Research Council. (2011). Intelligence Analysis: Behavioral and Social Scientific Foundations. Washington, DC: The National Academies Press.
Office of the Director of National Intelligence. (2019). The AIM Initiative—A Strategy for Augmenting Intelligence Using Machines. Available: https://www.dni.gov/files/ODNI/documents/AIM-Strategy.pdf [February 2019].
Wyler, L.S. (2008). Weak and Failing States: Evolving Security Threats and U.S. Policy (Order Code RL34253). Washington, DC: Congressional Research Service. Available: https://fas.org/sgp/crs/row/RL34253.pdf [December 2018].
This page intentionally left blank.