Ten years from now, the job of the intelligence analyst will be transformed. Analysts responding to continuously evolving security risks will likely be tracking new combinations of nonstate and state-sponsored actors who threaten to disrupt governance and civil society. These potential adversaries will likely be motivated by both familiar and unforeseeable drivers, including the effects of global climate change, which will be manifest through such issues as scarcities of water, food, and other resources; extreme weather events; and dislocation of communities. Shifting strategic alliances, military conflicts, the presence of hostile terrorist factions and street gangs, and deteriorating local economies will further challenge stability. At the same time, adversaries and other actors of concern to the Intelligence Community (IC) will have access to new resources, including computing technologies and cyberspace operations, as well as chemical and biological weapons—perhaps even stolen nuclear weaponry—that will dramatically amplify their power to inflict harm and disrupt daily life and commerce.
Intelligence analysts themselves will have new resources based on advances in data processing and other technologies. Technologies including artificial intelligence (AI), large dataset analytics, dynamic search tools, and interactive technologies are already allowing analysts to process and integrate multiple sources of data and intelligence far more quickly and efficiently than ever before. They are also dramatically expanding opportunities for collaboration involving personnel and technology, and integration of new types of data. New knowledge, tools, and technologies with
applications for understanding, forecasting, and mitigating security risks are continually emerging.
The IC will need research from the social and behavioral sciences (SBS) if it is to take maximum advantage of these developing resources and be optimally prepared for the security challenges on the horizon. But what is needed is not simply more research. Intelligence analysts already rely on SBS research, just as they already synthesize large volumes of data and information about fast-breaking developments to produce reliable and accurate assessments that can support urgent and consequential decisions.
To date, however, the influence of SBS research on intelligence analysis has been ad hoc: despite the value of many ongoing efforts, the IC has not found ways to systematically integrate research and perspectives from the academic SBS community into its work. Recognizing this gap and the crucial role of SBS research in supporting intelligence analysis, the Office of the Director of National Intelligence (ODNI), which oversees and directs the work of the agencies and organizations responsible for foreign, military, and domestic intelligence for the United States, requested that the National Academies of Sciences, Engineering, and Medicine conduct a decadal survey of SBS research with applications to national security.
The charge to the Committee on a Decadal Survey of Social and Behavioral Sciences for Applications to National Security was to (1) develop understanding and direction regarding resources from SBS disciplines with the greatest potential to augment and support the intelligence analysis process and enhance national security, which the IC can use in determining its research priorities for the coming decade; and (2) identify lessons to be learned from the application of the decadal survey process in the national security context.
A decadal survey is a method for engaging members of a scholarly community to identify lines of research with the greatest potential to be of use over a 10-year period in pursuit of a particular goal. The National Academies developed this type of survey to support the planning of future research for other government entities, including the National Aeronautics and Space Administration, the National Science Foundation (NSF), the U.S. Department of Energy, the National Oceanic and Atmospheric Administration, and the U.S. Geological Survey. The process has not previously been used to survey SBS research or to support the IC’s research planning. In conducting the present survey, the committee adapted the methods used in previous decadal surveys; we developed a process to seek understanding of the needs of the IC and current challenges in the work of the IC analyst and to cull SBS research of potential relevance to those challenges.
We identified two broad categories of need for the IC: support in leveraging developing research and technology to improve the skills and tools used by analysts, and support in strengthening the IC workforce. Thus, our focus was on the insights provided by the SBS disciplines into human behavior, capacities, and limitations, and ways in which those insights could be integrated into both the content of intelligence analysis (understanding what people and adversaries do) and the technical means of analysis (improving and supplementing the human capacities of the analyst).
We used four criteria to identify the areas of research with the most promise for direct impact on these two categories of need:
- the potential for impact on urgent national security priorities;
- the strength of the supporting evidence base;
- technical readiness, or the state of development on the continuum from basic research, to field testing and evaluation, to applied research; and
- the potential to use or develop emerging data sources, methods, or other technical advances with potential to yield significant advances.
We also considered the ethical implications of the research itself and its applications throughout the study process.
OPPORTUNITIES TO SHAPE THE FUTURE OF INTELLIGENCE ANALYSIS: RESEARCH DIRECTIONS
Opportunities in the research we examined can contribute to the most fundamental aspects of the IC’s work. To adapt to anticipated changes in both the security landscape and the way intelligence analysis is conducted, the IC will need the insights that come from deep understanding of cultural and political history and context, the way humans and social and political entities behave, and current trends and forces shaping the actions and decisions of individuals and groups. Integrating the understanding of human beings and social processes that comes from 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 tools and methods 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. We have identified research directions, summarized in our conclusions, for pursuing the opportunities in the bodies of work we examined. While there are clear, critical potential benefits to the IC in each of these areas, they are by no means the only promising ones. Nevertheless, a 10-year research agenda based on these
areas would contribute significantly to the IC’s analytic responsibilities, and build a strong foundation for significantly strengthening interchange between the security community and the external SBS research community.
Targeted SBS research offers the potential for stronger intelligence assessments, tools and technologies optimally designed for human use and human–machine interaction, and optimal readiness to confront evolving security threats.
Stronger Intelligence Assessments
SBS research can support the development of intelligence assessments that are richer 10 years from now because analysts will have the capacity to use new types of information and analyze existing types of information in new ways. SBS research involves gathering reliable and interpretable data on human behavior that does not fall within the expertise of other disciplines. It provides the essential theoretical and empirical bases for designing and using sophisticated methodologies to make complex data meaningful and enrich the analyst’s understanding of the social and political worlds. Assessments may also be more nuanced because analysts will have tools that allow them to identify intersections and see connections in large-scale datasets that humans alone could not detect.
Assessments may be more accurate and efficient. 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 analyses, and tracking of developments—capabilities beyond those of human analysts—but only if conceptual frameworks derived from SBS work provide the basis for their design. The result will be improved forecasting and the possibility of efficiently tracking regions, populations, groups, and sources of information. New kinds of indicators based in research on, for example, manifestations of emotion or how extremist narratives exert influence, could help the analyst gauge changes in a political leader’s behavior, the developing strength of a minority group’s influence, or the cohesiveness of networks within which toxic narratives are spreading, and direct the analyst’s attention more swiftly to those developments requiring attention.
CONCLUSION 5-1:1 Developing research on narratives, social networks, complex systems, and affect and emotion can enhance understanding of primary targets of intelligence analysis, the potential impact of actions taken by the Intelligence Community, and individual and social processes relevant to security threats. This research offers possibilities for new tools, including but not limited to
1 Conclusions are numbered according to the chapters in which they are introduced.
- indicators for use in monitoring and detection of key security-related developments;
- algorithms for extracting meaning from large quantities of open-source information; and
- models for reasoning about the potential implications of various interventions or activities.
CONCLUSION 5-2: Interdisciplinary, multimethod approaches to integrating insights from social and behavioral sciences fields with sophisticated technological developments will be essential to support the development of new tools for the analysis and interpretation of data and intelligence. The Intelligence Community would benefit from pursuing a portfolio of such research focused on the development of operational methods and tools.
Tools and Technologies Optimally Designed for Human Use and Human–Machine Interaction
Tools and technologies that become operational in the coming decade and beyond—including advances in data processing and AI that support large dataset analytics, dynamic search tools, statistical modeling, and interactivity—will augment the capacities of the human analyst in vital ways, which will necessarily change the nature of human–machine interaction. 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 accurate assessment and forecasting of human activity; and
- avoid serious unintended practical and ethical consequences.
SBS research offers insights that will be needed to design tools that use AI and machine learning. It could also support the development of an ecosystem for intelligence analysis composed of human analysts and autonomous AI agents, supported by other technologies, with the capacity to derive meaning efficiently from multiple sources of information.
Existing and emerging SBS research can also provide essential support for the procurement of products from the private sector, such as commercially available software programs and other technologies. While these externally produced resources bring important efficiencies and other benefits, careful attention is needed to ensure that they reflect SBS-based insights so they provide the benefits for which they were sought. Technology used
for analysis is only as strong as the understanding of the human behavior it is being used to model or explain.
CONCLUSION 7-1: To develop a human–machine ecosystem that functions effectively for intelligence analysis, it will be necessary to integrate findings from social and behavioral sciences research into the design and development of artificial intelligence and other technologies involved. A research program for this purpose would extend theory and findings from current research on human–machine interactions to new types of interactions involving multiple agents in a complex teaming environment.
CONCLUSION 7-2: A social and behavioral sciences research agenda to support the development of technologies and systems for effective human–machine teams for intelligence analysis should include, but not be limited to, the following goals:
- Apply methodologies from the vision sciences, the behavioral sciences, and human factors to advances in data visualization to improve understanding of how people extract meaning from visualizations and the functionality of tools designed to present information from large datasets.
- Use techniques from social network analysis to better understand how information can be transmitted effectively, as well as filtered among distributed teams of humans and machines, and how the need to use artificial intelligence (AI) to search and filter information can be balanced with the need to restrict access to certain information.
- Develop new modes of forecasting that incorporate human judgment with automated analyses by AI agents.
- Apply neuroscience-inspired strategies and tools to research on workload effects in a complex environment of networked human and AI agents.
- Examine the implications of ongoing system monitoring of work behaviors in terms of privacy issues, as well as potential interruptions to the intrinsic work habits of human analysts.
- Extend insights from the science of human teamwork to determine how to assemble and divide tasks among teams of humans and AI agents and measure performance in such teams.
- Identify guidelines for communication protocols for use in coordinating the sharing of information among multiple human and AI agents in ways that accommodate the needs and capabilities of human analysts and minimize disadvantages associated with interruption and multitasking in humans.
CONCLUSION 7-3: The design, development, and implementation of a system of human–technology teams, which would include autonomous agents, for use in intelligence analysis raise important ethical questions regarding access to certain types of data; authority to modify, store, or transmit data; and accountability and protections when systems fail. The Intelligence Community (IC) could best ensure that such systems function in an ethical manner and prepare to address unforeseeable new ethical issues by
- from the start, incorporating into the design and development process collaborative research, involving both members of the IC and the social and behavioral sciences community, on the application of ethical principles developed in other human–technology contexts to the IC context;
- ensuring that all research supported by the IC adheres to the standards for ethical conduct of research; and
- establishing a structure for ongoing review of ethical issues that may arise as the technology develops and new circumstances arise.
Optimal Readiness to Confront Evolving Security Threats
The contributions of SBS research will be vital to the capacity of the United States to react effectively to future risks. Ongoing SBS work is illuminating, for example, the nature of social networks and complex systems, protections against social cybersecurity threats, evolving ways adversaries influence hearts and minds, and the ways individuals are drawn into radicalization and extremism. Developments in numerous SBS fields are building understanding of both familiar and emerging threats. The emergence of new threats in cyberspace 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 has the potential to offer tools, tactics, procedures, and policies for assessing, predicting, and mitigating the impact of adversarial social cyberattacks.
CONCLUSION 6-1: A comprehensive multidisciplinary research strategy for identifying, monitoring, and countering social cyberattacks, predicated on computational social science, would provide significant support for the Intelligence Community’s (IC’s) efforts to address the social cybersecurity threat in the coming decade. The emerging field of social cybersecurity research can yield insights that would supplement the IC’s training and technology acquisition in the area of social cybersecurity threats and foster an effective social cybersafety culture. These insights could support development of the capacity to, for example, detect bots and malicious online actors and track the impact of social cyberattacks.
CONCLUSION 6-2: The Intelligence Community could strengthen its capacity to safeguard the nation against social cyber-mediated threats by supporting research with the objectives of developing
- generally applicable scientific methods for assessing bias in online data, drawing conclusions based on missing data, and triangulating to interpolate missing or incorrect data using multiple data sources; and
- new computational social science methods that would simultaneously consider change in social networks and narratives within social media–based groups from a geotemporal social-cyber perspective; and operational computational social science theories of influence and manipulation in a cyber-mediated environment that simultaneously take into account the network structure of online communities, the types of actors in those communities, social cognition, emotion, cognitive biases, narratives and counternarratives, and exploitable features of the social media technology.
Finally, SBS research can aid in strengthening the overall effectiveness of the IC workforce, an important aspect of preparedness for the security challenges of the coming decade. To the extent that foundational and current insights from industrial-organizational psychology and related fields have not already been integrated into the IC’s personnel management approaches, translational research to identify the applications of a well-developed body of research and practice in this area is likely to be beneficial. Four salient areas for which robust research is available are the selection of applicants likely to be effective in analytic roles, skill development on the job through both formal training and informal learning, means of retaining and engaging effective analysts, and ways of providing support for a potentially stressed and fatigued workforce.
CONCLUSION 8-1: A range of personal attributes—including skills in critical evaluation, writing and presentation, and teamwork; openness to feedback; and a continuous learning orientation—contribute to successful job performance as an intelligence analyst. To strengthen its capacity to select individuals well suited to work as an intelligence analyst, the Intelligence Community (IC) would benefit from
- regularly updating its assessment of the facets of the analyst’s job performance that are of greatest value to the IC and the attributes most useful for selection of personnel for intelligence analysis roles;
- having the capacity to measure a broad range of attributes for use in selecting individuals who possess those attributes; and
- evaluating the predictive power and potential ethical implications of such assessment devices as digital games, gleaning information about candidates from social media, and using machine learning approaches to extract information from interviews and resumés and develop scoring algorithms.
CONCLUSION 8-2: A large body of social and behavioral sciences research identifies individual and organizational factors linked to employee retention, including employees’ attitudes and engagement, unit cohesiveness, and leader quality, but these factors have not been examined in the Intelligence Community (IC) context. Translational work examining the role of these potential influencing factors could aid in managing retention in the IC.
CONCLUSION 8-3: A systematic review of the degree to which the organizational culture within the agencies of the Intelligence Community supports both organizationally directed training and autonomous learning could provide valuable information that could be used to promote these means of enhancing the skills of the analytic workforce. This review could focus on practices that promote such a culture, including
- opportunities for workers to receive feedback,
- tolerance for error as employees attempt to use new skills,
- support and encouragement from supervisors and peers, and
- allocation of time for autonomous learning.
CONCLUSION 8-4: Emerging research indicates that developing tools and methods could be used to assess and mitigate issues related to the effects of work in the high-stress environment of intelligence analysis, including cognitive fatigue, reduced attention, impaired performance, and decreased efficiency. Possibilities include the application of neuroergonomics (e.g., cueing, visual or auditory warning signals, automation); neuroscience (e.g., noninvasive brain stimulation); and neuropharmacology. The development of effective and safe tools and methods ready for implementation would require (1) research on the utility and applicability of these methods in the Intelligence Community environment, and (2) careful consideration of safety and ethical issues related to their use.
CONCLUSION 8-5: To fully benefit from research findings relevant to the development of an optimal analytic workforce, the Intelligence Community (IC) would need to invest in research and evaluation to
guide their application in the context of intelligence analysis. Translating key insights about selection, training, retention of, and support for the IC analytic workforce will in itself require a team approach in which members of the IC, social and behavioral sciences researchers, applied scientists, and others collaborate to help translate the approaches discussed here for the IC context and assess their effectiveness.
CAPITALIZING ON THESE OPPORTUNITIES
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.
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.
The range of opportunities explored in this report demonstrates both the power of the benefits SBS research offers for the IC and the extent of the challenge of fully taking advantage of these opportunities. Strengthening the relationship between the SBS community and the IC will be critical if these opportunities are to bear fruit. This report offers insights for sustaining this effort in the long term that come both from the experience of
conducting this decadal survey and from a review of the history of collaboration between these two very different communities.
Overall, what initially appeared to be the greatest challenge in conducting this study—a broad charge that required looking across a very wide research landscape—turned out to be the most valuable aspect of the task. The challenge of casting such a wide net in searching for intersections between the needs of the IC and the available SBS research meant that the committee’s efforts were not driven by the perspectives of a single discipline and that we had no preconceptions about where to look for relevant work. Further, despite the obvious difficulty of looking across multiple, diverse disciplines, the study process did reveal certain basic elements that would likely have emerged regardless of the methods used in the process. Without a doubt, for example, any attempt to meet our charge would have highlighted the importance of learning more about human–machine interactions, ways to make use of emerging analytics for big data, and the integration of insights about human behavior and group functioning in the pursuit of cybersecurity.
The survey process also allowed us to see firsthand some of the obstacles to integration and collaboration between the IC and the SBS community, and to observe that coordination between the two is less prevalent than would be optimal. Moreover, awareness of the potential applications of SBS research to IC needs is highly uneven across relevant SBS fields, and there is a long way to go in building awareness of these potential applications of their work among the research community.
Most of the opportunities identified in this report will depend on the integration of research from SBS fields with work from technical fields including engineering, computer science, and neuroscience. Technological developments occur in a social and economic context: SBS research is therefore essential to understanding of the potential applications and benefits, risks, and long-term effects of sophisticated technology and to its sound application, despite significant differences in theory and method between these two cultures. Therefore, we make one recommendation to the IC:
RECOMMENDATION 10-1: The leadership of the Intelligence Community should make sustained collaboration with researchers in the social and behavioral sciences (SBS) community a key priority as it develops research objectives for the coming decade. A multipronged effort to integrate the knowledge and perspectives of researchers from the SBS fields into the planning and design of efforts to support intelligence analysis is most likely to reap the potential benefits described in this report.
Although the objectives and perspectives of the SBS research community and the IC are not always aligned, the two communities have always had much to learn from one another. Researchers and members of the IC have differing objectives, face differing challenges and constraints, and operate in contexts that have very different norms and expectations. Nevertheless, collaborations between the two have for decades yielded important scientific and analytic insights.
CONCLUSION 9-1: Explicit attention to the respective intellectual goals, values, and perspectives of members of the Intelligence Community and academic researchers is a prerequisite for productive collaboration. Collaborations between the two have yielded important scientific and analytic insights, and have functioned well when funding sources and agency goals have been transparent, when social and behavioral sciences research questions and agency missions and goals have been harmonized and clear, and when ethical and value-based concerns have been treated with sufficient care. Conversely, the relationship has fractured in the past when funding sources have been kept secret or misrepresented, researchers and government agencies have struggled to balance research and agency needs, and research has touched on broader ethical or value-based disagreements.
CONCLUSION 9-2: Ethical issues may arise at all steps of the research process, from planning, to dissemination of findings, to the operationalization of digital tools in analytic contexts. Because standards with respect to some ethical issues—particularly those concerning the use of large-scale digital datasets—are developing, and because these issues are context-sensitive, ethical assessments require careful attention throughout the research process.
CONCLUSION 9-3: Meticulous clarity and openness about the approaches taken to ensure the reproducibility and validity of the evidence generated in the course of research conducted by or with the support of the Intelligence Community (IC) are critical to the utility of the research results. The IC can promote this standard by requiring researchers to identify project components that incorporate assessments of reproducibility, replication, and validity.
The findings presented in this report provide the foundation for what the committee hopes will become a stable and continuing process by which SBS research can be culled for its relevance to national security challenges, and promising relevant work can be supported and integrated into IC plan-
ning and operations. Effective interchange in the future is likely to involve four key ingredients:
- building on effective examples of collaboration, such as communities of practice;
- strengthening cultural bridges between the two communities and addressing institutional obstacles to collaboration;
- providing opportunities for analytic staff to build their knowledge of SBS research and for researchers to improve their understanding of the IC; and
- relying on the principles of human–systems integration to facilitate the development of collaborative systems that function effectively.
This report comes at a critical time in the nation’s history: new forms of threats, as well as complex new methods and tools for understanding trends and developments, identifying immediate threats, and forecasting future problems, are making the IC analyst’s work both more challenging and more critical. Without understanding of the human component of these developments, the IC analyst would be perilously hampered. 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. The continued strengthening of the IC workforce 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.
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