SMA Publications

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Anticipating Rare Events: Can Acts of Terror, Use of Weapons of Mass Destruction or Other High Profile Acts Be Anticipated? A Scientific Perspective on Problems, Pitfalls and Prospective Solutions.

Author | Editor: Chesser, N. (DTI).

This white paper covers topics related to the field of anticipating/forecasting specific categories of “rare events” such as acts of terror, use of a weapon of mass destruction, or other high profile attacks. It is primarily meant for the operational community in DoD, DHS, and other USG agencies. It addresses three interrelated facets of the problem set:

1. How do various disciplines treat the forecasting of rare events?
2. Based on current research in various disciplines, what are fundamental limitations and common pitfalls in anticipating/forecasting rare events?
3. And lastly, which strategies are the best candidates to provide remedies (examples from various disciplines are presented)?

This is obviously an important topic and before outlining in some detail the overall flow of the various contributions, some top-level observations and common themes are in order:

1. We are NOT dealing here with physical phenomena. Rather these “rare events” that come about are due to human volition. That being the case, one should not expect “point predictions” but rather something more akin to “anticipating/forecasting” a range of possible futures. Furthermore, the difficulties are compounded because these forecasts, to be relevant, have to be done on a global scale and chronologically as far in advance of the rare event occurrence as possible. Therefore, caution is in order when dealing with these phenomena and the reader should approach this topic with a critical disposition and eyes wide open. Hubris is NOT a recommended frame of mind here!
2. The reader will be disappointed if she/he expects a linear menu-driven approach to tackle these problems. Brute force approaches are NOT feasible. Or stated differently, the problem set is NOT amenable to a “blueprint” driven reductionist approach! The approach taken here is heavily tilted towards a dynamic methodological pluralism commensurate with the magnitude and scale of the problem set. Emphasis is placed on judiciously incorporating uncertainties and human foibles and attacking the problem set with approaches from various disciplines. These involve analytical, quantitative, and computational models primarily from the social sciences.
3. On the other hand, the reader who is disposed to eclectic approaches to this very critical problem set will NOT be disappointed. Inductive, deductive, and abductive approaches will be discussed along side themes from gaming theories. Key to all this is a mix of creative intuition and the age-old scientific method. The concepts from the fields of complex adaptive systems, emergence, and co-evolution all contribute to a sustained strategy. The process of objective multi-disciplinary inquiry is at the heart of any success in this challenging domain.
4. The vast majority of the data for such assessments come from open sources. The reader will encounter approaches that take advantage of such data. Equally important is development of an appreciation of the “cultural other” within their own “context” and “discourse”. This is critically important. On the other hand, this massive amount of data (the good, the bad, and the ugly!) brings with it its own share of problems that will need to be dealt with. There is NO free lunch in this business! In all circumstances however, a prudent frame of mind is to let the data speak for itself!
5. The points made so far point to a multi-disciplinary strategy as the only viable game in town. On top of that, we don’t expect single agencies to be able, on their own, to field these multi-disciplinary teams. Agile, federated approaches are in order. The reader who approaches this topic with that frame of reference will resonate with the report.
6. Finally, and most importantly, rare events, by their very nature, are almost impossible to predict. At the core of this white paper is the assumption that we can do a better job of anticipating them, however, if we learn more about how our brain works and why it gets us into trouble. Although we may not be able to predict rare events, we can reduce the chances of being surprised if we employ measures to help guard against inevitable cognitive pitfalls.

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The reader should also be forewarned that the approaches discussed in this paper are by no means a “be all...end all”. All contributors would agree that the approaches presented here are to varying degrees “fragile” and will need further nurturing to reach their full potential.

The reader should not be put off by the size of the report. The articles are intentionally kept short and written to stand alone. You are encouraged to read the whole report. However even a selective reading would offer its own rewards. With that in mind, all the contributors have done their best to make their articles easily readable.

We open up the white paper with an article by Gary Ackerman (1.1). It serves as a scene setter. Gary makes the point about differences between strategic and point predictions; points out general forecasting complexities; and, as the reader will be reminded throughout the rest of report, the limitations of purely inductive approaches (i.e., the happy-go-lucky turkey all year until the unexpected on Turkey Day!). These inductive approaches work best when coupled with other complementary approaches. He makes the point that forecasting must rely on information sharing, extensive collaboration, and automated tools, a point that will be made by other contributors.

From this scene setter, we’re ready to assess how various disciplines have been treating this genre of problem set. We start with an anthropological perspective by Larry Kuznar (2.1). The realization that a broader understanding of culture is necessary to meet modern national security challenges is a “no-brainer” and has naturally refocused attention toward anthropology. Historically, the human ability to use past experience and creative imagination to model possible futures provides humans with a powerful and unique ability for prognostication. The article makes the point that when creative imagination departs from empirically verifiable social processes, and when beliefs in predictions become dogmatic and not adjustable in light of new data, the benefits of prediction are lost and whole societies can be destroyed due to a collectively held fantasy.

From an anthropological perspective, we move to philosophical and epistemological considerations (i.e., what we know and how we know it) by Ken Long (2.2). The paper summarizes recent results in the epistemology of the social sciences which indicate that the employment of case-by-case studies in combination with theories of limited scope involving a select intersection of variables can produce results that are far more useful than more traditional research.

In the following paper (2.3), Carl Hunt and Kathleen Kiernan provide a law enforcement (LE) perspective to the challenges criminal investigators and police officers on the street face in anticipating rare events. Similarities and differences with intelligence analyses are highlighted. The authors discuss the three “I’s” in LE (i.e., Information, Interrogation and Instrumentation) in the context of our problem set and highlight the role of fusion of intuition, probability and modeling as enhancements to the three “I’s”.

We next move to the all important evolutionary theory and the insights it can provide.c In his contribution (2.4), Lee Cronk makes the case that although it deals mainly with the common and everyday, evolutionary theory may also help us forecast rare events, including rare human behaviors. Understanding evolutionary theory’s contributions to this problem requires an understanding of the theory itself and of how it is applied to human behavior and psychology. He describes concepts such as costly signaling theory; i.e., terrorist organizations actively seeking recognition for their acts, giving them an additional reason to send hard-to-fake signals regarding their collective willingness to do harm to others on behalf of their causes. An appreciation of the signaling value of terrorist acts may increase our ability to forecast them. He also describes the concept of mismatch theory; i.e., the idea that much of the malaise in modern society may be due to the mismatch between it and the kinds of societies in which we grew up. And finally he describes “the smoke detector principle” (i.e., early warning system) from the perspective of evolutionary theory.

We conclude this segment of the white paper with a military perspective provided by Maj Joe Rupp (2.5). He approaches rare events from the perspective of “crisis” level events. As such, understanding the nature of crises facilitates a better understanding of how rare events may be anticipated. He goes on to dissect the anatomy of crises by tapping a body of literature on the topic. Rather than view a crisis as a "situation", the phrase "sequence of interactions" is used. This implies that there are events leading up to a "rare event" that would serve as indicators of that event. Identification and understanding of these precipitants would serve to help one anticipate rare events. From a military perspective, anticipation of a truly unforeseen event may lie solely in maintaining an adaptive system capable of relying on current plans and available resources as a point of departure from which the organization can adjust to meet the challenge of the unforeseen event. In contrast to the Cold War planning construct, he introduces the concept of Adaptive Planning and Execution (APEX) which through technology, uses automatic “flags” networked to near-real-time sources of information to alert leaders and planners to changes in critical conditions and planning assumptions that warrant a reevaluation of a plan. All this calls for “agile and adaptive leaders able to conduct simultaneous, distributed, and continuous operations”.

From here we move on to part 3 of this report to examine fundamental limitations and common pitfalls in anticipating/forecasting rare events. The opening article by Sarah Beebe and Randy Pherson (3.1) discusses the cognitive processes that make it so difficult to anticipate rare events; i.e., the things that help us efficiently recognize patterns and quickly perform routine tasks can also lead to inflexible mindsets, distorted perceptions, and flawed memory.

The next article (3.2) by Sue Numrich tackles the set of interrelated empirical challenges we face. The human domain is currently broken down and studied in a variety of disparate disciplines including psychology, political science, sociology, economics, anthropology, history and many others, all of which, taken as a whole, are needed to understand and explain the human terrain. These factors require an ability to share information in new ways. Moreover, the abundance of information sources in our internet-enabled world creates a problem of extracting and managing the information events and requires a balance between the amount of information acquired and the capability to process it into usable data.

No discussion of rare events is complete these days without due consideration to Black Swans! That challenge is taken on by Carl Hunt (3.3). Carl differentiates between true Black Swans (TBS, the truly unpredictable) from anticipatory black swans (ABS, which may be difficult but not impossible to anticipate), which is more in line with the topic of this white paper. He states that it’s the questions as much as the answers that will lead to success in anticipating what we call Black Swans, regardless of category. Often these questions are posed in the form of hypotheses or assumptions that bear on the conclusions decision-makers take. We must also be willing to let go of prejudice, bias and pre-conceived notions. Carl reinforces a strong theme in this white paper namely that “Intuition and the Scientific Method” should synergize to help in tackling anticipatory black swans.

Having set the cognitive limitations, we next move to discuss remedies. The reader who has stuck with us so far will find the subsequent papers offering some guarded hope. For methodological purposes, we divide the solution space into two categories: front-end and back- end. These are discussed in turn by Fenstermacher/Grauer and Popp/Canna.

Laurie Fenstermacher and Maj Nic Grauer (4.1) start off by depicting the daunting task ahead not just as a “needle in a haystack” but as a “particular piece of straw in a haystack” (the perennial discouragingly low signal-to-noise problem!). They define “Front end” as the group of capabilities to retrieve or INGEST, label or CHARACTERIZE, apply specific labels, extract information, parameterize or CODE and VISUALIZE data/information. Besides the low “signal-to-noise” ratio challenge, there are other challenges such as languages other than English. In addition, the information is more often than not “unstructured” and multi-dimensional. They state firmly that there are no “silver bullet” solutions...but (and dear reader please don’t despair!) there are genuinely a number of solutions. These can do one or more of the above functions and, in doing so, provide a force multiplier for scare human resources by enabling them to use their time for thinking/analysis and not data/information processing. They go on to describe promising capabilities in all front-end categories. Their parting claim is that properly employed as part of an “optimized mixed initiative” (computer/human) system, the solutions can provide a key force multiplier in providing early warning of rare events well to the “left of boom”.

The following article (4.2) by Bob Popp and Sarah Canna provides an overview of the back-end solution space. Stated simply, the challenge here is how to make sense of and connect the relatively few and sparse dots embedded within massive amounts of information. They state that the IT tools associated with the back-end are the analytic components that attempt to meet this challenge and provide analysts with the ability for collaboration, analysis and decision support, pattern analysis, and anticipatory modeling. They go on to make the case that IT tools can help invert a trend – sometimes referred to as the “Analyst Bathtub Curve” – thus allowing analysts to spend less time on research and production and more time on analysis. They illustrate how several such tools were integrated in a sample analytic cycle.

Having introduced the broad concepts of front-end and back-end, we go on to discuss various promising remedies. The first article in this category (4.3) by Bob Popp and Stacy Pfautz discusses the landscape of Quantitative/Computational Social Science (Q/CSS) technologies that provide promising new methods, models, and tools to help decision-makers anticipate rare events. They describes the three main Q/CSS modeling categories; namely quantitative, computational, and qualitative techniques.

Kuznar et al (4.4) follow-up with a discussion of statistical modeling approaches. The challenge here is data sparseness. They emphasize a common theme throughout this white paper; namely that there is no guarantee that conditions and causal relations of the past will extend into the future. Furthermore, in the case of rare events, there is often precious little information upon which to base predictions. They do discuss state-of the-art methods to extract and structure data, impute missing values, and produce statistically verifiable forecasting of rare WMD terrorism activities. A key product from this effort is the identification of key factors (i.e., fingerprints, indicators, antecedents, or precursors) that are statistically related to increases in the probability of rare events occurrence.

We shift gears next with an article by Tom Rieger (4.5) on models based on the Gallup World Poll data This provides the ability to spot areas that are currently or could be at risk of becoming unstable, including pockets of radicalism. These can provide very useful avenues for narrowing down search spaces for origin and destination of rare event activities.

Having presented empirically based approaches to forecasting and the evaluation of the environmental factors from which they arise, we turn our attention next to the use of applied behavior-based methodology to support anticipation/forecasting. The author of this article (4.6) is Gary Jackson. Key to his argument is the assumption that if antecedents and consequences associated with repeated occurrences of behavior can be identified, then the occurrence of that behavior in the future may be anticipated when the same or highly similar constellations of antecedents and likely consequences are present. In the absence of adequate history, Jackson has developed a hybrid approach of behavioral data combined with subject matter expert (SME) generated scenarios. A neural network pattern classification engine is trained and used to generate hypotheses given real world injects.

In the following article (4.7), Sandy Thompson, Paul Whitney, Katherine Wolf, and Alan Brothers discuss a data integration framework for quantitatively assessing relative likelihood, consequence and risk for rare event scenarios. Current methodologies are limited as they are qualitative in nature, based on expert assessments, and elicited opinions. The authors advance structural models to organize and clarify rare event scenario assessments, including qualitative as well as quantitative factors. Benefits to intelligence analysts would include increased transparency into the analysis process, facilitation of collaborative and other parallel work activities, and mitigation of analyst bias and anchoring tendencies. They discuss concepts based on Bayesian statistics and the three primary factors that drive the analysis: the motivation and intent of the group directing the event, the capabilities of the group behind the attack, and target characteristics. They conclude their article by pointing out that the methodologies are intended to address and mitigate bias, reduce anchoring, and incorporate uncertainty assessments.

In the following article (4.8), Allison Astorino-Courtois and David Vona make the case that subjective decision analysis – viewing an adversary’s choices, costs and benefits from his perspective – can provide invaluable assistance to the rare event analyst. Here “subjective” refers to a decision model designed according to how the decision maker views the world rather than the beliefs of the analyst. Such an analysis helps the analyst gain insight into three critical areas; namely motivation, intent, and indicators. The authors argue that such an approach is valuable because it forces the analyst to look at the issue of rare and dangerous events from the perspective of those deciding to engage in them.

In the next article (4.9), Elisa Bienenstock and Pam Toman provide an overview of Social Network Analysis (SNA) and propose a manner in which potential rare events may be recognized a priori through monitoring social networks of interest. In line with a common theme throughout this white paper, they emphatically state that SNA alone is not a sufficient perspective from which to anticipate the planning or imminence of a rare event. To be useful, SNA must be used as a component of a more comprehensive strategy requiring cultural and domain knowledge. They go on to state that SNA is both an approach to understanding social structure and a set of methods for analysis to define and discover those activities and associations that are indicators of these rare, high impact events. In particular, they focus their discussions on two insights from the field of social network analysis: 1) the innovation necessary to conceive of these rare events originating at the periphery of the terrorist network, and 2) the organization of an event and how it generates activity in new regions of the network.

Ritu Sharma, Donna Mayo, and CAPT Brett Pierson introduce in the next article (4.10) concepts from System Dynamics (SD) and systems thinking to explore some of the ways in which this technique can contribute to the understanding of “rare events”. Their focus is on identifying the key dynamics that drive behavior over time and the explicit consideration of feedback loops. Starting with the by now familiar premise that building a model that can accurately predict the future is impossible, they go on to enumerate the benefits attributed to a System Dynamics model to help prepare for, and hopefully mitigate the adverse effects of, rare events such as understanding which rare events generate the most harmful impacts, highlighting the factors and causal logic that would drive a rare event, and lastly identifying the highest leverage areas for focus and mitigation. They conclude by stating that System Dynamics can integrate valuable experience, research, and insight into a coherent framework to help refine and accelerate learning, facilitate discussion, and make the insight actionable by identifying key leverage points and creating a platform to test impacts of various strategies.

The next article (4.11) by Carl Hunt and David Schum advances approaches that harness the science of probabilistic reasoning augmented by complex system theory in support of testing hypotheses for unforeseen events. Key assumptions here go to the heart of the challenge of forecasting rare events: nonlinearity of input and output; the ambiguity of cause and effect; the whole is not quantitatively equal to its parts; and that results may not be assumed to be repeatable. Adaptation and co-evolution are important features in this approach. The article stresses the role of curiosity and discovery in the process of abduction as a formal method of reasoning. We often deal with evidence that is typically incomplete, often inconclusive, usually dissonant, ambiguous, and imperfectly credible. When this occurs, we must apply some sort of probabilistic inference method to assess the effect a particular piece of evidence will have on our decision-making, even when there are no historical event distributions to assess – the authors discuss how this might be accomplished.

Eric Bonabeau in his contribution (4.12) re-states a now-common theme; namely our inability to predict low-frequency, high-impact events in human and manmade systems is due to two fundamental cognitive biases that affect human decision making. These are availability and linearity. Availability heuristics guide us toward choices that are easily available from a cognitive perspective: if it’s easy to remember, it must make sense. Linearity heuristics make us seek simple cause-effect relationships in everything. He makes the case that to anticipate rare events we need augmented paranoia. His corrective strategies include tapping the collective intelligence of people in a group and tapping the creative power of evolution.

At this juncture in the white paper we change course again and discuss the key role of gaming and its role in anticipating rare events. Although games cannot “predict” the future, they can provide enhanced understanding of the key underlying factors and interdependencies that are likely to drive future outcomes. There are four contributions in this section.

The first contribution (4.13), by Fred Ambrose and Beth Ahern, makes the case for moving beyond traditional Red Teams. They state that the conventional use of Red Teams is not to serve as an anticipatory tool to assess unexpected TTPs. Rather they are configured to test concepts, hypothesis, or tactics and operational plans in a controlled manner. They recommend instead modifying traditional red teams by acknowledging the importance of the professional culture of individuals who make up these teams augmented by consideration given to the knowledge, experience, skills, access, links, and training (KESALT) of people who may be operating against the blue teams. This can help alleviate failures on the part of Blue Teams to fully understand the role of “professional cultural norms” of thought, language, and behavior. They introduce the concept of Social Prosthetic Systems (SPS) and the value of integrating it into Red Team formation. SPS can help analysts to understand the roles that culture, language, intellect, and problem solving play for our adversaries as they form planning or operational groups in a manner similar to “prosthetic extensions”. They point out that a red team based on the KESALT of known or suspected groups and their SPSs, can provide much greater insight into the most probable courses of action that such a group might devise, along with the greatest potential to carry out these actions successfully. In addition, such red teams can provide invaluable insights into and bases for new collection opportunities, as well as definable indications and warning. In this sense it can help create the basis for obtaining structured technical support for a blue team or joint task force and lead to unique training opportunities for joint task force officers. Such red team efforts can lead to unique training opportunities for joint task force officers; newly identified metrics and observables that can serve as unique indications and warnings, and even can anticipate both the state of planning and execution and the ultimate nature and target(s) of military or terrorist actions.

In the following article (4.14), Dan Flynn opens his contribution with a theme which is common by now: that standard analytic techniques relying on past observations to make linear projections about the future are often inadequate to fully anticipate emerging interdependencies and factors driving key actors toward certain outcomes. He posits that strategic analytic gaming is a methodology that can be employed to reveal new insights when complexity and uncertainty are the dominant features of an issue. Through strategic analytic games, events that are “rare” but imaginable, such as a WMD terrorist attack, can be explored and their implications assessed. In addition, strategic gaming can reveal emerging issues and relationships that were previously unanticipated but could result in future challenges and surprise if not addressed.

In his contribution to the role of gaming (4.15), Jeff Cares describes an innovative approach to planning for uncertain futures, called “Co-Evolutionary Gaming.” His focus is on complex environments in which trajectories to future states cannot all be known in advance because of strong dependencies among states. He discusses problematic characteristics of existing gaming methods. He then goes on to highlight characteristics of a method for proposed scenario-based planning that more creatively explores the potential decision space. He introduces the concept of Co-evolutionary Gaming as a method of planning for uncertain futures with which players can quickly and inexpensively explore an extremely vast landscape of possibilities from many perspectives.

We end this series on gaming with a contribution by Bud Hay (4.16) who approaches gaming from an operational perspective. Instead of focusing on the worst possible case, he advocates addressing more fundamental issues, such as: What is the adversary trying to achieve? What are his overall interests and objectives? What assets are needed to accomplish those objectives? What are the rules of engagement? What alternative paths are possible to achieve success? He advocates an “environment” first and “scenario” second approach to gaming. He goes on to make the case that operational level gaming can be a valuable technique for planners and operators alike to anticipate surprise, evaluate various courses of action, and sharpen understanding of critical factors regarding potential crisis situations. By examining the congruence of capabilities and intent, it helps decision makers better anticipate rare events. All these can provide a contextual framework from which to postulate likely, and not so likely, terrorist attacks and to evaluate readiness and preparedness against them.

We shift gears again with a series of four articles that will round out the discussion of analytic opportunities in our remedy section. In the first contribution (4.17), Sue Numrich tackles the all- important issue of knowledge extraction. Sue’s point of departure is that rare events of greatest concern arise in foreign populations among people whose customs and patterns of thoughts are not well understood, largely through lack of familiarity. The expert in such cases is someone who has spent considerable time living with and studying the population in question. The problem with relying on expert opinion is that it is only opinion and all observers, including subject matter experts have perspectives or biases. She tackles the issues of how to elicit expert opinion in a manner that adds understanding and not selecting the wrong experts or interpreting their statements incorrectly. She differentiates between SME elicitation and polling and the all important problem of finding the right experts. She goes on to tackle the issue of how best to structure the interviews and understanding the biases (ours and theirs!).

In the second in this series of articles (4.18), Frank Connors and Brad Clark discuss the important role of open source methods. They state the objective of open source analysis is to provide insights into local and regional events and situations. In this sense, open source analysis provides a tipping and cueing function to support all-source analysis. They go on to describe Project ARGUS, an open source capability to detect biological events on a global scale. A total of 50 ARGUS personnel are fluent in over 30 foreign languages. The scale of open source collection ranges from 250,000 to 1,000,000 articles each day with archiving of relevant articles. Machine and human translation is utilized in conjunction with Bayesian networks developed in each foreign language performing key word searches for event detection. They conclude by stressing that combining the open source data with other classified data sets is key to the overall evaluation.

The next contribution (4.19) by Randy Pherson, Alan Schwartz, and Elizabeth Manak focuses on the role of Analysis of Competing Hypotheses (ACH) and other structured analytical techniques. The authors begin with familiar themes for the reader who has stuck with us so far; namely, engrained mindsets are a major contributor to analytic failures and how difficult it is to overcome the tendency to reach premature closure. The authors go on to describe remedies such as Key Assumption Check, Analysis of Competing Hypotheses (ACH), Quadrant Crunching, and The Pre-Mortem Assessment amongst others. Key to their argument is that the answer is not to try to predict the future. Instead, the analyst’s task is to anticipate multiple futures (i.e., the future in plural) and identify observable indicators that can be used to track the future as it unfolds. Armed with such indicators, the analyst can warn policy makers and decision makers of possible futures and alert them in advance, based on the evidence.

We complete the series of articles on analytical techniques with a contribution by Renee Agress, Alan Christiansen, Brian Nichols, John Patterson, and David Porter (4.20). Their theme is that through the analyses of actors, resources, and processes, and the application of a multi-method approach, more opportunities are uncovered to anticipate a rare event and implement interventions that lead to more desirable outcomes. They stress the need for understanding the motivation of actors (Intent), their required resources (Capability), and the multitude of process steps that the actors have to implement (Access). While each of these items may or may not be alarming in isolation, the capability to identify a nexus of individuals and activities spanning the three areas can facilitate anticipating a rare event. However, anticipation becomes more difficult as time approaches the period of an execution. During and prior to the execution phase, the members of the group become OPSEC conscious and tend not leave a data signature. In line with their multi-method approach, they highlight the need for diverse fields such as econometrics, game theory, and social network analysis, amongst others.

At the beginning of this Executive Summary, it was stated that the challenges caused by rare events points to the need for a multi-disciplinary and multi- agency response built on the notions of transparency, bias mitigation and collaboration. The challenge of course is how to instantiate such concepts. This is taken up by Carl Hunt and Terry Pierce (4.21). They propose the integration of a collaboration concept built on a biologically inspired innovation known as the Flexible Distributed Control (FDC) Mission Fabric which can provide a potential substrate for organizational interaction. These interactions will occur through a setting known as the Nexus Federated Collaboration Environment (NFCE) that is described in detail in an SMA Report of the same name. The NFCE concept is adaptively structured, while empowering collaborative consensus-building. It is built on a multi-layer/multi-disciplinary decision-making platform such as the proposed FDC, while maintaining an orientation towards evolutionary design. The NFCE seeks to highlight and mitigate biases through visibility of objective processes, while accommodating incentives for resolving competing objectives. The authors point out that while these are lofty objectives, the means to integrate and synergize the attributes of the NFCE are coming together in bits and pieces throughout government and industry. The FDC is a proposed concept for creating an instantaneous means to distribute and modulate control of the pervasive flow of command and control information in the digital network. It offers the ability to focus and align social networks and organizations. The FDC weaves the virtues of social networking into a group-action mission fabric that is based on collaboration and self-organization rather than on layered hierarchy and centralized control. The article goes on to discuss the engine for executing FDC; i.e. the mission fabric – a new situational awareness architecture enabling collaboration and decision making in a distributed environment. The mission fabric is a network-linked platform, which leverages social networking and immersive decision making. From initial assessments, it appears that the NFCE and FDC may synergize effectively to empower interagency planning and operations.

Jennifer O’Connor brings this white paper to a close with an epilogue (4.22). She provides insightful comments on the whole enterprise of forecasting rare events and the role of identifiable pattern of precursors. She warns against confusing historical antecedents with generative causes. She provides a general framework and set of avenues by which one can think about rare-events-in-the-making in contemporary and futuristic terms. She stresses the need for an almost clinical detachment from our own basic information gathering and processing. She concludes by stating that the strategy of inoculating against “rare events” allows us to move off the well-worn path of generalizations based in the past and alarmist projections.

Two appendices to this white paper provide information relevant to the topic at hand. Appendix A describes a Table Top Exercise (TTX) planned and executed by DNI with support from SAIC and MITRE. It was designed to assess analytic methodologies by simulating a terrorist plot to carry out a biological attack. The Appendix goes on to summarize the main insights and implications produced by the exercise. In Appendix B, we reference an article by Harold Ford titled “The Primary Purpose of National Estimating” which addresses the Japanese attack on Pearl Harbor. It is very pertinent to the topic at hand and is alluded to by various contributors to this white paper.

Lastly, Appendix C provides definitions of acronyms used.

Contributing Authors

Gary Ackerman (U MD START), Renee Agress (Detica), Beth Ahern (MITRE), Fred Ambrose (USG), Victor Asal (SUNY, Albany), Elisa Bienenstock (NSI), Alan Brothers (PNNL), Hriar Cabayan (RRTO), Bradley Clark (TAS), Allison Astorino-Courtois (NSI), Sarah Beebe (PAL), Eric Bonabeau (Icosystem), Sarah Canna (NSI), Jeffrey Cares (Alidade), Alan Christianson (Detica), Frank Connors (DTRA), Lee Cronk (Rutgers), Laurie Fenstermacher (AFRL), Daniel Flynn (ODNI), Nic Grauer (AFRL), Bud Hay (ret), Carl Hunt (DTI), Gary Jackson (SAIC), Kathleen Kiernan (RRTO), Lawrence Kuznar (NSI), Kenneth Long (IPFW), Elizabeth Manak (PAL), Donna Mayo (PA Consulting), Brian Nichols (Detica), Sue Numrich (IDA), Jennifer O’Connor (DHS), John Patterson (Detica), Krishna Pattipati (U Conn), Stacy Lovell Pfautz (NSI), Randolph Pherson (PAL), Terry Pierce (DHS/USAFA), CAPT Brett Pierson (Joint Staff J8), Bob Popp (NSI), David C. Porter (Detica), Karl Rethemeyer (SUNY, Albany), Tom Rieger (Gallup Consulting), Maj Joseph Rupp (Joint Staff J3), David Schum (GMU), Alan Schwartz (PAL), Ritu Sharma (PA Consulting), Steven Shellman (William and Mary, SAE), Sandy Thompson (PNNL), Pam Toman (NSI), David Vona (NSI), Paul Whitney (PNNL), and Katherine Wolf (PNNL)</p>, &nbsp;, , <h5>Download Publication</h5>, <a href="http://nsiteam.com/social/wp-content/uploads/2016/01/Anticipating-Rare-Events.pdf" target="_blank" rel="noopener"><img class="wp-image-1895 alignleft" src="http://nsiteam.com/social/wp-content/uploads/2008/12/Anticipating-Rare-Events-150x150.png" alt="human-domain" width="100" height="100" style="border:2px solid black" class="alignnone size-thumbnail wp-image-6908" /></a>

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The Human Domain: The Unconventional Collection and Analysis Challenge Workshop.

Author | Editor: Canna, S. & Popp, R. (NSI, Inc).

One of the major challenges the US has faced during the opening decades of the 21st Century is the growth in the number and international reach of insurgents, terrorists, WMD proliferators and other sorts of nefarious groups. Among many others, the current situation in Iraq illustrates the difficulty of countering insurgencies once they have become violent and operationally well-established. The apparent transition of contemporary war away from the traditional physical battlefield towards the human element as the battlefield poses new challenges for both intelligence and operations – collections and analysis within the human domain requires new thinking and new methods.

The purpose of this workshop was to identify approaches to recognize and anticipate the conditions in which insurgents, terrorists, WMD proliferators and other sorts of nefarious groups tend to emerge, become operationally established, and choose to employ tactics counter to the interests of the US national security objectives. An underlying presumption of this workshop is that tackling these movements during their emergent phases is less costly in resources and lives, with more non-lethal options available for consideration, than after they have become fully established. Novel approaches to collections and analysis of the interactions within and between elements of the “human dimension” may lead us to greater potential for proactive rather than reactive capabilities, and certainly non-kinetic capabilities, not only within the military context, but within all components of national power.

Clearly, focusing on emergent violent groups and their activities will necessitate a shift in how the nation and its allies collects, analyzes, and acts upon information from and about these volatile environments. The workshop brought together a diverse group of physical and social scientists, academics, analysts, intelligence collection managers, operational planners, and decision makers to discuss novel techniques and methods for a more proactive approach to address the human dimension associated with insurgents, terrorists, WMD proliferators and other sorts of nefarious groups, and the impact of such an approach on training, planning, tasking, collection, analysis, and decision making in the coming decades.

EVOLUTION OF VIOLENT EXTREMISM

There is an important distinction between activism and radicalism. Activism is legal and nonviolent political action, while radicalism is illegal and violent political action. Activism is not necessarily a conveyor belt to radicalism. Individuals can be radicalized from any layer of society including neutral parties, sympathizers, and activists.

Government Sponsored Research on Violent Extremism

The Department of Homeland Security (DHS) is is laying the groundwork to conduct in-depth case studies of individuals engaged in terrorist violence in the US. At the group level, DHS is studying terrorist group rhetoric with a focus on both groups that have engaged in terrorism and groups that would be considered radical but that have not engaged in terrorism. The study will look at groups with similar ideologies and goals and try to understand why some groups choose violence and others do not. DHS will also work to identify characteristics of groups who participate in IED attacks. At the community level, DHS is involved in two primary activities. The first is evaluating whether survey data can shed light on radical activity in the US. Finally, DHS is working with START to study the effectiveness of counter radicalization programs conducted in five countries including Yemen, Indonesia, Columbia, Northern Ireland, and Saudi Arabia.

The Behavioral Analysis Unit is the newest organization within the Federal Bureau of Investigation. It is an operational unit that conducts research. Counterterrorism research within the unit is still in its infancy stages; however, some projects are currently underway dealing primarily with operational threat assessments. The most pertinent research efforts are in collaboration with DoD intelligence units. This work primarily focuses on radicalization by looking at the radicalization process in historic case studies. The FBI is also involved in another research effort in coordination with the WMD directorate, to look at 50 domestic cases in which offenders used WMD in the US.

The Defense Intelligence Socio-Cultural Dynamics Working Group (SCDWG) was created in 2002 to develop an enterprise solution to institutionalize Socio-Cultural Dynamics intelligence analysis. The group was asked to address the full scope of issues, from policy to tactical. The group was asked to define the role of intelligence in this area as well as to identify the “right tool for the right job.”

The Marine Corps Intelligence Activity (MCIA) is working on the next generation of cultural intelligence. They are working on visualizing cultural intelligence by “putting culture on the map.” Their second project is to support influence operations and irregular warfare by building partner capacities focused on the values and themes of sub-national groups. The third is cultural vignettes, which are short and focused products designed to create a specific cognitive map for each mission set. The fourth is building an analytic capacity by supporting uniquely trained cultural analysts, ensuring 24/7 reachback for deployed unites, and creating deployable analytic teams for contingency operations.

UNDERSTANDING SOCIO-CULTURAL DYNAMICS: TRADECRAFT AND OBSERVATIONS FROM A DISTANCE

Studies to understand a country and its people must be planned and carried out with nuance. Ethnic maps, a critical tool for US forces, have long been a political issue. It affects resource allocation, boundaries, and political formulae. In countries experiencing ethnic conflict, building a credible demographic baseline must be done before lasting geopolitical stability can be realized. Maps can help researchers and analysts understand the cultural geography of conflict. Chorological analysis, relating to the description or mapping of a region, can reveal causal linkages and patterns of political and social behavior that researchers were previously unaware of. Mapping the human terrain is needed to understand these complex problems.

Culture at a distance methodology from 1942 mostly comprised of several sources. Researchers studied travelers’ accounts, ethnographies, histories and other second hand sources including social science works. Content analysis finds its roots in these attempts. Post World War II, the DoD funded a great deal of social science research although only a small part of it was “culture at a distance”. They focused instead on models such as game theory. Their main interest was in political instability: its causes and indicators.

Today, the DoD has stated that socio-cultural data collection is everyone’s problem. However, the DoD does not currently have the knowledge and understanding of non-Western cultures and societies necessary to execute these missions. Because of this, there are several new culture at a distance methods. Computational modeling has become the sine qua non of culture at a distance method, but it suffers from considerable handicaps. Its emphasis on computational engineering leads to “everything looks like a nail” thinking. The problem with models is that many do not scale gracefully from explaining small scale issues to larger scale ones. Models are culturally and socially ignorant, which is frequently the case when engineers develop “new cultural theory” with little or no training in the fields of social science.

Socio-Cultural Tradecraft and Open Source Collection Requirements Management

Emerging violent non-state actors use or share a common story about their involvement to motivate and empower their groups, and attract and mobilize their audiences. The degree by which infringements are interpreted, personified, and perceived is the variable to which violence emerges. It is typically a conflict between the haves and the have not’s over a particular issue. Modeling these relationships requires a four prong approach: anthropological research; open source collection; human intelligence collection; and environmental research. The model will synthesize that information to assess behavior.

Cultural geography is the study of spatial variations among cultural groups and the spatial functioning of society. Urban geography is the study of how cities function, their internal systems and structure, and the external influences on them and the study of the variation among cities and their internal and external relationships. The human geography areas of interest include economics, demographics, politics, culture, combined social implications, and technology/infrastructure. Cultural geographers face several challenges. First, experiences in Afghanistan and Iraq have shown that neighborhood level data is necessary for operational and tactical planning (Intelligence Preparation of Battlefield). Second, there is a lack of reliable data sets. For example, there has been no census in Lebanon since 1932. Third, closed countries, such as North Korea, pose a problem. Fourth, no city level data exists or it is difficult to obtain in grey literature. Fifth, there is a lack of current academic studies. Therefore, researchers must take a multidiscipline approach and use sources from a variety of fields to complete their research.

Remote Observing Using Large Data Sets

The nexus for computer forensics is addressing large data sets. Researchers and developers are working with open source information and applying analytic tools to it. They have discovered that it is considered novel in the US to use the same tool to address open source and classified datasets and merge them. One large data set, INSPIRE, was developed to allow an analyst to look at a large number of text documents and look for words and phrases. The program graphically portrays the output. A subsequent project is porting INSPIRE over to high power computing environment.</p>, <p>Content analyzers are another tool for working with very large datasets. The tool makes coding schemes in the process of creating large data sets from large text sources. It has an automatic generation process that is transparent. From this data, the analyst produces dashboard like metrics to describe the data. This has created an impetus to create measures of effectiveness and validation. The team discovered that people and computer coders make different types of errors. Humans make boredom errors. Their accuracy always goes down over time. However, if a computer sees a new word, it will not code it. The operation code measures how you present self and others in text on cooperative or conflictive dimensions. The tool can also extract and compare entities for distrustfulness. They use a combination of tools to look for themes and people. It is a pragmatic way to build structure while reducing the analysts’ reading load.

UNDERSTANDING THE HUMAN TERRAIN: TRADECRAFT AND STREETCRAFT METHODS

Applying Law Enforcement Methods to Gathering Human Terrain

An appropriate balance of skills, knowledge, and abilities need to be incorporated into an analysis team. It needs to be half Army Ranger company and half artist colony. Good analysts are adaptable, intellectually flexible, and have a high degree of comfort with ambiguity. An analyst’s job is simple: they read, write, and present. In the development of a good analyst, no preparation matches analyst’s comfort level with ambiguity. Furthermore, the depth and breadth of an analyst’s rolodex is more important than personal understanding of a region or topic. Analysts must also exhibit finesse - the practice of combining knowledge, thought, and intellectual stamina. Personal conviction of paying attention to a few small details that have enormous impact on outcomes or intelligence is critical. Good analysts are those who care as much about operational environment as producing a final product.

Approximately 90 percent of the food we eat, clothes we wear, and products we use are imported daily via commercial maritime transport. Threats to ships and ports include drug smuggling, stowaways, and terrorists. Drugs are often creatively hidden in cargo, such as cocaine stashed inside individual bananas. Drug couriers can also be hidden away in cargo shipments. These could easily be terrorists or terrorist materials. According to a US Coast Guard report, 25 Islamic extremists entered the US onboard commercial cargo vessels. Narco traffickers are more frequently taking consignments of extremists to the US. There is an increasing level of cooperation between MS-13, narco traffickers, and Islamists. The human collection component is critical to stopping these illegal activities because Customs cannot provide the level of analysis needed.

The Department of Commerce’s task is to prevent the export of US dual-use goods and technology that may be used by rogue states or terrorists to make chemical, biological or nuclear weapons. The Office of Export Enforcement’s priorities are WMD proliferation, terrorism/terrorist support, and unauthorized military/government use. Commerce is unique in that it has civil penalties, in addition to criminal penalties, in which one only needs the preponderance of the evidence to convict. The challenge of identifying and stopping illegal dual use exports is making sure at every step of the process that all of the people involved can validate the end use. It gets murky because end users lie and some components are working with the end users. Globalization is also a national security challenge and many transactions are moving over the internet. The US government does not move at the speed of business.

The Criminal Investigation Task Force (CITF) was created in early 2002 by the DoD to conduct investigations of detainees captured in the Global War on Terrorism. CIFT became the investigative arm of the DoD after OSD was given the mission to prosecute the detainees. OSD transferred the responsibility to the Army, where the CITF now falls under Army Criminal Investigation Command (CID). The need for analysts and intelligence professionals was huge, especially for law enforcement officials not used to working with classified materials. Likewise, law enforcement people need to communicate with the combatant commanders. Terrorists groups often act like organized crime groups. The intelligence community may not have much experience in this, but law enforcement does. It also has experience in conducting interrogations. To conduct interviews effectively the interrogator must put all biases aside and just accept the culture for what it is. The interrogator must get down to the bedrock of cultural foundation.

Applying Social Science Methods to Understanding the Human Terrain

Social science is the application of consistent, rigorous methods of research and analysis to describe or explain social life. Its purpose is inference: using facts we do know (data, observations) to learn about facts we do not know (theories, hypotheses). It is used to make descriptive inferences (semantic program); to place or make observations within a conceptual framework to allow people to understand a phenomenon; and to make causal inferences (syntactic / pragmatic program). Because of the large number of potential causal factors for any social phenomenon, establishing causation is difficult. If we can establish the cause of a social phenomenon, then we can make policy to affect that phenomenon.

Data collection involves various methodologies such as ethnography: participant observation; surveys: interview processes (formal, informal, group, individual, structured, unstructured); record or document review; and history: conducting interviews or reviewing documents about the past. Data analysis involves direct interpretation: analysis by an individual’s reflection and synthesis; quantitative analysis: using standard methods of statistics to ascertain relationships; and formal modeling: analysis by creating a formal system that mimics the world. In evaluating which method is most appropriate, it is important to keep in mind that multidisciplinary methods reinforce one another.

Field research in Iraq is particularly complicated. Researchers must use semantic programs and descriptive inference as well as create a pragmatic program with causal inference. Some of the challenges include sampling, reactive bias, and interpretive bias. Coping with these problems is done by working through local researchers, geographic sampling and purposive sampling, redundancy of methods, and redundancy of research networks. On the ground analysis is informed by area studies, topic specialization, and occasional forays into population.

There is a great need to improve intelligence support to stability operations. To do this, analysts must embrace the importance of understanding the human terrain. There are three key elements to the human terrain. The first is developing a socio-cultural dynamics data network and repository. The second is developing data gathering, visualization, and analytic tools. The third is recruiting, training, and deploying experts to support decision-making.

To understand counterinsurgency, you must first understand and define the elements involved. Collecting information for COIN operations involves identifying key groups in a society and representing where they are located on a map. For each group, researchers seek to identify security (level, sources, threats); income and services (level, sources, gaps); beliefs and communications systems (narratives, symbols, norms and sanctions); and authority structures & figures (identity, structures, levels of authority).

Soldiers as Human Terrain Sensors

The Civil Affairs (CA) information objectives were to provide multi-dimensional situational understanding, provide situational analysis, and to work on the development of possible solution sets. The foci of CA operations are human terrain identification and prioritization (sphere of influence management) and civil reconnaissance. Within the human terrain network, there are sphere of influence engagements. These works identified political/tribal leaders throughout the district and their areas of influence to facilitate reconciliation efforts. They also identified facility managers/public works workers to facilitate transition to Iraqis fixing Iraqi problems. They also prioritized efforts to optimize limited resources for engagement.

There are three critical nodes in the CA analysis process. The first is collection. The information is the critical base element to the process. Without this, there is no system. The second is consolidation. Analysis and understanding the information makes the process function. It is an art and a science. The third is dissemination. Sharing the situational understanding is the key to success. Dissemination must flow up and down in order to coordinate and integrate with partners.

Provincial Reconstruction Teams (PRTs) have become a key tool for the international community to assist Afghanistan in becoming a secure and self-sustaining Republic. They represent, at the local level, the combined will of the international community to help the government and the civil society of Afghanistan become more stable and prosperous. PRTs, due to their provincial focus and civil-military resources, have wide latitude to accomplish their mission of extending the authority of the Government by improving security, supporting good governance and enabling economic development. This engagement of diplomatic, military and economic power by Nations at the provincial level allied with the wide latitude to accomplish their mission has been a strength, as it provides flexibility of approach and resources to support the provincial government structures and improve security.</p>, <p>The Humanitarian Information Unit (HIU) serves as a United States Government (USG) interagency center to identify, collect, analyze and disseminate unclassified information critical to USG decision makers and partners in preparation for and response to humanitarian emergencies worldwide, and to promote best practices for humanitarian information management.

Civilians as Human Terrain Sensors

In order to operate effectively in Afghanistan, warfighters need to understand the cultural context and history of the nation. An anthropology background by itself is not always useful. Human Terrain Teams (HTTs) and others need culture specific knowledge to achieve their mission in foreign countries. An open source portal exists to provide a civilian based source of socio-cultural information on Afghanistan. The portal facilitates a subject matter expert network to encourage interaction among the key players including the Department of State (DoS), non-governmental organizations (NGOs), the US Agency for International Development (USAID), Brigade Combat Teams (BCTs), and soldiers. The site drills down to the provincial level where 21 of 34 provinces have been completed. The site provides information on detailed maps, refugees, education, health, topographic information, etc.

SUPPORTING ANALYTIC DISCIPLINES

Modeling and Visualization Workshop Summary

The objective of the Social Science Modeling and Visualization Workshop, held in January 2008, was to provide a “mixing bowl” for social scientists, modelers, researchers and government stakeholders to discuss the state-of-the-art in methods/models/visualization and their potential application in SMA efforts. Models can clarify complex situations, test assumptions, aid decision making, explore co-evolutionary motivations and bound the expected and outlier behaviors. Modeling can capture dynamical, non-linear processes. They can be multi-level, multi-scale behavior representations. Other benefits include that models can assist in training decision makers on the consequences of their policies/decisions. Visualization is a critical component of modeling. Therefore, it needs to be considered from the beginning of a project. Visualization serves a variety of functions include support of knowledge management, contextual visualization, relational visualization, identification of key features/nodes/information, understanding of decisions/complex processes, and evaluation/inspection of the data. Models must be verified, valid, and credible. The theoretic framework of social science modeling and visualization still needs work. Opportunities and challenges include the need for better, scientifically grounded theories. The federal government is interested in social science, but struggling to determine how to support it. It will take 4-5 years to reach robust funding levels.

Evolutionary Agent-based Modeling and Game Theoretic Simulations

Agent Based Modeling (ABM) is successful in the social science arena because as in the traditional approach to formal modeling, the goal is reducing the social landscape to a set of meaningful variables and specific mathematical equations. ABM brings to social science the ability to begin with a social landscape of entities in the world. It can identify basic relationships between actors. All models are developed or designed to answer a class of questions. ABMs are typically designed to answer questions that are intractable through earlier and more traditional mathematical or statistical methods, such as complex emergent patterns in large systems of agents. The beauty of ABM is that it can conduct experiments about shifting policies. All this can be done in silicon because you cannot manipulate players in the real world. ABM is a specific kind of simulation. It provides an experimental setting for finding patterns that are not very obvious.

Game theory is a branch of applied mathematics that formally models strategic behavior. Game theory is an approach to aid in articulating and understanding important factors of conflicts / disputes / coalitions. Game theory is neither prescriptive nor descriptive; nor is it normative. It is a theoretical tool. Game theory does not provide an answer; it provides a helpful way to frame the question to better understand the situation. If the assumptions are correct, game theory will provide an answer. Some assumptions of the theory include (bounded) rationality, complete information, and preference hierarchy for players (utility). In conclusion, it is important to remember that people are not agents. Game theory requires assumptions about behavior. It provides insight and understanding, but people are more complex than mathematical models. Finally, as in any model, if you put garbage in, you get garbage out.

Data Fusion / Integration and Detecting Patterns in Heterogeneous Data Sets

The defense and intelligence communities are making great progress in the social sciences. Many agencies now realize the importance of social science approaches, in combination with more traditional approaches. Often, people want to know why if we can go to the moon we cannot accurately model social science. It is because people are complex intelligent agents with feedback. They have multiple incentives, multiple allegiances, and multiple groups. Humans also exhibit adversarial behavior. They provide inaccurate and misleading information. Behavior is not invariant. There is a hierarchy of challenges in data fusion. The first is registration and entity resolution. The second is group and network detection. The third is feature construction and recognition. The fourth is complex event detection. The fifth is that concepts in models are inherently fuzzy. There is a prediction versus risk relation. And risk brings additional scrutiny and preparation challenges.

Data fusion technologies encompass a variety of characteristics. It is historically a deductively-based inferencing / estimation process. The resulting observations and estimates produce random variables optimized for minimum uncertainty. The process is adaptive in various ways. It enables observation management, process adaptation, and beneficial actions. Data fusion models can be used to analyze a broad set of areas. The physical domain is the easiest to accomplish fusion. This includes weapon systems and weather reports. The information domain is harder. This includes symbolic representation and interpretations of data and models. The cognitive domain includes beliefs, values, and emotions and is the most difficult to fuse.

Efforts are underway to create an automated multi-source, multi-sensor, multi-data fusion tool. One way they are doing this is by looking at textual information. They take documents of different types, use ABA tools and extract antecedents. The tools can grab information, bring it together, and end up with predictive models. Working toward multi-focused analysis, the tool must overcome the problem of sorting through tons of information.

Large Data Sets and Knowledge Extraction Techniques

Large data and visualization efforts are becoming an ever growing avalanche within the social science community. Loading all the data is hopeless. Therefore, efforts have focused on trying to load the structure of the data. This results in maximum expressiveness with minimum size. The structure of the data for documents includes terms, entities, and concepts. The structure for transaction, travel, and communication records include people, places, organizations, and relationships. However, smart loading still requires human guidance. A sandbox is an environment for “what if” questions and for constructing arguments. It should have quick access to exploratory tools and answer the question, “How are these actors connected?” The system’s job is to track workflow and allow for annotations and assumptions. The analyst can backtrack and replay, branch, and recombine. He may also retract or change assumptions. The output should embody a complete chain of reasoning.

Work is being undertaken to determine whether researchers could construct a scaffold for the data that can say something about the dataset. The geometry in the data set might help pull out information. By comparison if you look at physics, the math needed to model it is very tame math. In biology, the math needed is fundamentally different. Even though researchers have not discovered the laws of social science, there are some regularities, although they have not been captured in math to a sufficient depth.

The scale and speed of the data means that the classic, craftsman approach to machine learning is no longer possible. The answer is a commodity, hands-on model. This is a challenging task. Not only does commodity mean that researchers have to develop algorithms that are robust in the face of noise, skew, and the host of other ills; it also means that they have to work out how to set all algorithm parameters from the data or the context, so that the human analyst need not concern themselves with them. There is no single algorithmic magic bullet. There are lots of pattern recognition algorithms; some are well known, including decision trees, support vector machines, neural nets, nearest neighbors, naive Bayes. Ensembles are the first and the most powerful of the techniques to know about, as they permit you to squeeze all possible accuracy out of your data.

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Overcoming Information Challenge in Federated Analysis: From Concepts to Practice.

Author | Editor: Canna, S. (NSI, Inc).

The Overcoming Information Challenge in Federated Analysis: from Concepts to Practice workshop, held on 27-28 August 2008, was convened in response to requests from US Special Operations Command and US Strategic Command, Lieutenant General Carter F. Ham, Director of Operations, J-3, Joint Staff. The workshop is part of an effort to develop national-level capability to identify and anticipate the action of Violent Non-State Actors (VNSA) with regard to their intent and capability to acquire, build, store, employ, deploy, or supply weapons of mass destruction (WMD). In support of this effort, the workshop was sponsored by a multiagency team and hosted at the Directed Technologies Incorporated (DTI) facility in Arlington, Virginia.

The purpose of the workshop was to identify analytical methods and tools that could (1) aid in the sorting of large volumes of unstructured, multilingual data and to (2) help make sense of the output. Concerted novel approaches to data trolling, ingest, characterization, processing, extraction, coding, and visualization may lead to great potential for proactive rather than reactive capabilities, not only within the military context, but within all components of national power.

Focusing on the front-end issues of the data analysis process will significantly improve our nation’s and its allies’ capabilities to proactively uncover global WMD proliferation. The workshop brought together a diverse group of physical and social scientists, academics, analysts, intelligence collection managers, operational planners, and decision makers to demonstrate and discuss usable techniques and methods for a more effective nexus of the federated informational and analytical processes.

This workshop examined technologies that could play a role in addressing the problems faced by the Strategic Multi-layer Analysis (SMA) team in marshalling data and putting it in a form that could be readily analyzed to perform quantitative analysis. The purpose of the workshop was to expose problems and offer potential solutions to the problem of ingesting large quantities of data, particularly data from multilingual text and coding it for use in analytical models. The discussion of the Weapons of Mass Destruction – Terrorism (WMD-T) Joint Intelligence Preparation of the Operational Environment (JIPOE) problem space and technical approach are included to give the reader an understanding of why the technologies being explored will be needed in the long term by any group seeking to look globally at non-state actors who may choose to use weapons of mass destruction.

JIPOE is a proven doctrinal process typically applied to a bounded geographic space.1 While it has rarely been applied to the government as a whole, the process can be used to assess the information challenge problem and the federated analysis solution. While the JIPOE process typically focuses on the commander, the process applies to any federal decision maker. The combined forces of the nature of globalization and increasing interdependency generated by the informational revolution have ushered in a new imperative for a more holistic understanding of the operation environment. This workshop addressed these issues and looked for solutions to automated multi-data lingual processing in a federated environment.

The objective of the WMD-T JIPOE effort is to develop a sustained, national-level means for combating WMD-Terrorism with a forecasting, anticipating, or inferential strategic environmental level assessment capability covering the full threat spectrum from intent to act, to acquisition and attack preparation, and all the way downstream to deployment by non-state actors (i.e., from far left to just left of “boom”). The ability of the government to process data, identify indicators of terrorism, and share those findings in a truly federate manner needs to be enhanced. As a consequence, the only way to fight a dynamic and adaptive threat network is a similarly dynamic and adaptive USG federated forecasting and anticipating assessment network.

The notion of a sustained and repeatable capability requires that the adopted methods and processes be founded on robust scientific methods and theory. The nature of global reach forces the intelligence and defense communities to continue to enhance their efforts to exploit open source information and fuse it, as appropriate, with all the source information currently collected. The volume of that information demands that the effort use reliable automation technology to the fullest extent, recognizing that multilingual data mining is not mature for all languages. Even with the best data mining techniques, new methods for sorting the data and targeting the factors that will most reliably detect intent to acquire and use WMD must be established to avoid increasing the workload of already over-burdened analysts. Thus from the front end extraction processes to the back end analysis methods, existing tools must be augmented by emerging capabilities that keep analytical decisions properly centered on the human analysts while enhancing their performance.

Pieces of the WMD-T JIPOE capability already exist in various places among a number of groups within and outside the government. Thus the WMD-T JIPOE will work to take full advantage of these unique and disparate efforts in such a way that each participating group is capable of sustaining its own efforts while collaborating with and benefiting from the work of the other participants. The Information Challenge workshop highlighted pieces of the puzzle to join the research and the operation communities together to work toward a unified effort. The ultimate vision of the WMD-T JIPOE enterprise is a federation in which the WMD-T JIPOE cell is the core and integrator of data and where methods and tradecraft are shared among collaborating groups.

The workshop was designed to showcase tools and technologies that could be brought to bear on the information challenge problem. The problems and potential solutions explored in this workshop are common to challenges that rely on the ability to ingest large amounts of multilingual text information and extract from it data that can be used in analytical models.

Deterrence in the 21st Century: An Effects-Based Approach in an Interconnected World Volume III.

Author | Editor: Chesser, N. (DTI).

Supporting material for Volume II -- Deterrence Typology, which was created to assist in the development of deterrence options and plans for State and Non-State Actors.

Deterrence in the 21st Century: An Effects-Based Approach in an Interconnected World Volume II - Typologies.

Author | Editor: Chesser, N. (DTI).

This Deterrence Typology was created to assist in the development of deterrence options and plans for State and Non-State Actors. It can be used as a stand alone document for identifying important information to characterize and understand State or Non-State Actors. It can also assist in the development of initial questions that should be answered about either type of actor to be deterred.

This typology represents the merged product of three separate efforts to identify and categorize (a) the most relevant factors influencing the behavior and decisions of State and Non-State Actors and (b) the underlying elements of Decision Making by individuals and groups. Because it is the product of negotiation and consensus, some of the detail and richness of the descriptions developed specifically for State and Non-State Actors has been lost. However, the resulting merged product should be more valuable as a single resource for either type of Actors.

The section on Decision Making and the Decision Maker should help the user better understand which elements of the previous sections may be most influential in a specific scenario or situation and how they may impact the Decision Maker’s behavior. While the section on Decision Making Approaches may be one of the most important for understanding and affecting an Actor’s decision calculus, the information needed to make a determination about an approach may be difficult to ascertain without sufficient information about previous decisions made in a variety of situations and about the current context. Although a set of implications for each decision making style has been included to aid analysis and development of potential deterrence options, it is recommended that the user vet decision making approach determinations with appropriate subject matter experts.

This typology is organized into five (5) sub-typologies deemed relevant to describing the factors likely to impact an actor’s decision making process about a particular issue or action. The five sub-typologies are: Objectives, Motivation, Capabilities, Functional and Structural Environment (including the physical and human terrain), and Decision Making (see Table of Contents – next page). The overall format of the Deterrence Typology provides a brief definition of each sub- typology followed by a list of indicators of the sub-typology and observables. Suggested collection and analysis sources are enumerated under the observables.

The Deterrence Typology should be referred to for additional detail, definitions, and examples before and during completion of the Guiding Questions.

Collection & Analysis Caveats:

1. Collection sources are representative versus exhaustive.
2. “Analysis” implies the use of content analysis, pattern analysis (including nodal), trend analysis, change detection, and anomaly detection. Any additional factors are directly noted in the relevant section.

See the Annex for Information Sources and Methods

Deterrence in the 21st Century: An Effects-Based Approach in an Interconnected World Volume I

Author | Editor: Chesser, N. (DTI).

This report summarizes the results from a 120-day effort that was undertaken to meet these challenges. A scope of the effort is provided by Lt Col Shannahan in section 1; namely, decision makers, policy makers and commanders at all levels need to better understand deterrence theory applicable to the 21st century security environment. The USG requires a typology to understand the ways and means to deter a non-nation-state actor while simultaneously retaining the means to deter and compel nation-states.

The effort focused on the scientific underpinnings of deterrence. A broad viewpoint was adopted; namely actions that prevent an adversary from engaging in behaviors that threaten or oppose US national interests. For further elaborations please refer to the Glossary (Appendix B).

The effort, instead of focusing on an adversary’s capability as the basis for planning, refocuses analysis and planning on the actor’s motivations for action, his intent, and the structure of his decision problem as he sees it. Capability is not ignored, but actor’s perspective, motive and intent is at the core of this effort and the role of social science is paramount. The results are actualized in the Deterrence Analysis and Planning Support Environment (DAPSE) which is a web application that captures the depth of current academic thought along with established military doctrine to advise planners and associated staff with the means to deter the adversary. A DAPSE overview and description are provided in sections 2 and 3 by Dr Chesser and Stu Schwark & Altaf Bahora respectively.

A primary task of the Deterrence Strategic Multi-layer Analysis (SMA) project was developing a typology that could characterize the information needed for understanding adversaries and other actors of interest. A typology was developed that is consistent with various social science disciplines, and that incorporates a thorough consideration of human and cultural factors necessary for understanding what people value and how to influence them; i.e., a systems hierarchical paradigm for analyzing any society. The systems hierarchical approach is based on several anthropological ontologies that relate the various aspects of society, and is also based on inputs from the numerous social scientists involved in this project. Key aspects of a society captured in the systems hierarchical approach include ideology and religion, culturally based values, social organization, culturally prescribed roles, demography, and the actor’s decision making process, as well as capabilities.

These are described by Dr Larry Kuznar in section 4. While the DAPSE typology is one of the more complete and useful typologies for guiding analysis and planning, there are gaps. Two of the most obvious are a lack of consideration of language and history.

Drs Laurie Fenstermacher and Bob Popp discuss the role of modeling in section 5. Models, first and foremost, augment the ability of an analyst or planner, but do not in any way replace them. Models aren’t turnkey... they provide input to decisions, they don’t make them! They are good at producing a swath of forecasts (e.g., the range of probable locations for landfall of a hurricane), not good at producing point predictions (due to inherent uncertainty in the data or in the model itself). In addition, models can compensate for limits in subject matter expert (SME) knowledge. Due to the inherent complexity and dynamic nature of the systems and problems of interest, it is extremely difficult for an expert, or group of experts, to account for the effects of all possible interactions, particularly those with a low probability of occurrence. A complete reliance on SMEs will result in a very subjective assessment devoid of empirical evidence!

Section 6 by Dr Allison Astorino-Courtois outlines the use of the DAPSE Typology to guide the user’s information search and organization; “reconstruction” of the interest-based decision calculus from the deteree’s perspective; and techniques for analyzing that decision calculus to discover the most effective “influence levers” for deterring an opponent’s unacceptable activities. This is at the core of this deterrence effort and the reader is well advised to dwell on it.</p>, <p>Having identified the strategic context, deterrence objectives and decision calculus of actor(s) to be deterred, the analysis now turns to analyzing the truthfulness of the hypotheses (influence levers) emerging from the decision deterrent matrix, and also evaluating possible courses of action and their consequences under different conditions. These approaches are described in section 7 by Drs Bob Popp and Laurie Fenstermacher.

The final stage in the DAPSE process is a last check of the refined US deterrence option(s) identified and evaluated and tested. To do this the refined US deterrence option, now including actual US DIME (Diplomatic, Informational, Military, and Economic) actions, is “run” back through the Deterrence Decision Calculus (DDC) matrix. This is described in section 8 by Dr Allison Astorino-Courtois.

By now the reader should be aware that the approach taken focuses on the actor’s intent instead of focusing primarily on adversary capability...a necessary change after a near monopoly on capability fixation in the Cold War. This shift is the holy grail of the intel community and an essential maxim of our new world order – the shift from physical space to cognitive space. This necessitates the need to expand use of non-traditional sources of information and application of non-traditional analyses (e.g., cognitive and behavioral modeling). These are described in section 9 by Drs Bert Davis and Brian Meadows.

In section 10, LCDR Wes Latchford discusses perspectives on deterrence provided by the private sector. In support of the SMA, the GISC Partnership Group was asked to leverage its unique network of non-traditional domestic and international civilian business and academia experts to explore how particular elements of private sector enterprises approach the concept of "deterrence," the indicators utilized to determine when deterrence is necessary, and the "ways and means" by which deterrence is accomplished. The private sector provides a “Second Set of Eyes” perspective outside of DoD.

In section 11, Dr Carl Hunt and CAPT(S) Todd Veazie address the very important topic of networks and connections in developing a deterrence strategy. Their theme is that deterrence in the Cyber Age will not work as it did in the Cold War, simply because we will find it far more difficult to apply it and to understand feedback from its use – we may not be able to understand what the adversary values and thus never understand how to place that value at risk. This will absolutely require more consistent use of multi-disciplinary thinking and decision-making. We must create a Cyber Power-based DIME incorporating interconnectivity and economic interdependencies already emerging: we must change thinking about the DIME to include interconnectivity and shore up the economic, diplomatic and information components, while strengthening the potential of the military component.

Each of the sections in this report identifies, as appropriate, areas that need further work. In section 12, Dr Larry Kuznar identifies several key areas that clearly require more development. They include social neuroscience, global challenges, information age deterrence and strategic communication, and dynamism and complexity. Related to these is the potential for the development of a dynamic approach to deterrence that would incorporate feedback from on- going US COAs (courses of action) and re-evaluation of deterrence strategies, operations and tactics.

Having developed the methodology and a set of procedures, the effort turned next to several potential notional scenarios to assess whether or not they worked together to produce a viable result. In section 13, Dr Sue Numrich, explores one of the test scenarios in some depth. The scenario selected is based on a current problem – the influx of foreign fighters into Iraq. Although the DAPSE process is intended to be exercised over a longer time period, the analysts who developed this scenario worked over a period of only four days relying on their accumulated experience. The section summarizes a set of possible deterrence options based on this analysis.

Products resulting from efforts like this with heavy reliance on social science can atrophy rather fast. Col Tim Fay in section 14 discusses transition options being contemplated.

As the effort neared completion, the team applied the DAPSE to several NOTIONAL scenarios primarily to identify and rectify gaps/deficiencies. These are being published separately. The first three are classified and will be forwarded in appropriate channels:

• Scenario 1: Non-state
• Scenario 2: State – PACOM
• Scenario 3: State – CENTCOM
• Scenario 4: Sudan (multiple actors)

Many thanks are due to all who worked on this effort (see Appendix F), to the contributors to this report and finally to Dr. Nancy Chesser who patiently edited the report.

Authors: Dr. Sabrina Polansky (Pagano) (NSI, Inc.) and Tom Rieger . (NSI, Inc.)

Quick Look Preview

This report supported SMA’s Integrating Information in Joint Operations (IIJO) project. For additional speaker sessions and project publications, please visit the IIJO project page.

In the current environment of contested norms, increasing great power competition, and rapid technological change, protecting and furthering US interests requires the ability to compete effectively in the information environment (IE). In recent years, the IE has seen the proliferation of actors, channels of communication, and messages. To compete in this crowded and contested environment, we must be able to communicate effectively. Yet, the IE is complicated, available information is often vast and imperfect, time is constrained, and additionally, we are limited by our own cognitive capacity.

Humans have developed several adaptations to address these cognitive limitations, including heuristics and other mental shortcuts that facilitate survival by enabling more efficient processing of information from the environment. Unfortunately, these same shortcuts hardwire biases into our thinking and communication, which render messaging efforts ineffective and open to manipulation by adversaries seeking to mislead or confuse. These cognitive biases can lead to inaccurate judgments and poor decision- making that could trigger either unintended escalation or failures to identify threats in a timely manner. Understanding sources and types of cognitive bias can help minimize miscommunication and inform development of better strategies for responding to adversary attempts to leverage these biases to their advantage.

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Author: Farwell, J. (King’s College, U. of London and Middle East Institute.)

Executive Summary

This report addresses the elements of narrative that lend coherence to US military activities that could help shape Chinese and Russian behaviors. From there, the paper looks at kinetic and non- kinetic tactics that are and will be used by competing powers domestically and abroad to undercut US interests over the coming decade. These responses do not factor in the potential impact of emerging technologies, including G5, Artificial Intelligence, and Quantum Computing. These seem likely to have a significant impact and the Pentagon would seem well advised to conduct new research that anticipates the scope and capacity of each technology and how each or all of them confluently affects tactics, strategies, and operations.

This essay focuses on tactics, not the broader questions of operations or strategy as the United States wrestles with the implications of New Generation Warfare (NGW). Russia’s term is “hybrid warfare.” China’s approach is expressed in its Three Warfares concept. The West talks about “Gray Zone” warfare.

NGW is usually discussed in military circles. But it is more distinctly a political notion, not a military one, although its strategies incorporate military aspects and, especially for Russia, kinetic activity. All three nations’ notions think of NGW as action short of warfare.

The Russian notion of hybrid warfare emanates from the “active measures” employed by Russian intelligence during the Cold War and preceding it. Its approach seeks to create disruption, chaos, fear, uncertainty, and loss of confidence in the media as well as in public and private institutions. The approach includes weaponized social media, coercion, bribery, disinformation, intimidation, and unattributed kinetic action.

The Chinese notion is more sophisticated and builds upon a late 1990s concept of combination warfare that was adapted from its perception of US approaches, based on observations about how the United States operated during Desert Storm in Iraq. China has evolved its approach into a “Three Warfares” concept that confluently employs lawfare, psychological warfare, and media warfare. China leverages the state’s authoritarian power to integrate its concept with diplomatic, intelligence, and economic strategies such as the Belt and Road Initiative. China is vigorously promoting its version of 5G for the Internet, tying it to Huawei, and requiring users to employ Chinese standards and technology. It has been well observed that China’s “aid” turns nations into debtor states, could hamper free trade, and “could set global and regulatory and technical standards for new technology that could provide advantages to Chinese companies over others.” Its use of media warfare and other tactics helps present Chinese actions in a deceptive light that the United States and its partners should expose, discredit, and de-legitimize.

This report proceeds to examine the Russian hybrid warfare and the Chinese Three Warfare concepts in depth. It suggests elements both of a US and a multilateral allied narrative that could lend coherence to US military activities and could help shape Chinese and Russian behaviors in a manner that better serves US national interests. Understanding how to address their concepts and forging new strategies and tactics that leverage our unique strengths to gain a competitive edge is vital to our current and future security.

Author | Editor: Kuznar, E. (NSI, Inc.)

Executive Summary

Data

Two datasets on wealth and income distribution were analyzed for Croatia’s country report: the 2017 World Bank quintile and decile estimates of income and data collected by Croatia’s government that provides the mean monthly income and number of employees for specific occupations.

Results

Croatia’s Arrow-Pratt score is one of the lowest scores in this study, ranking it 151 of 158. Its low Arrow- Pratt score indicates that Croatia’s population is highly risk acceptant. This risk acceptance is constant across both datasets, with those who earn the highest incomes scoring as the most risk acceptant.

Implications for US Interests

Croatia is strategically valuable to the US and other Western countries due to the role it plays in the Balkans. Its acceptance into the European Union during 2013 gave the US and its allies in NATO and the EU an important ally that can be used to confront Russian encroachment into the region and help other former Yugoslavian states democratize and potentially join the EU. Croatia’s highly risk acceptant population poses a risk to the US and its Western allies in the EU that rely upon its political stability to lead other Balkan nations away from Russia and toward a more democratic state.

Implications for China’s Interests

China has been increasing its bilateral trade with Croatia in order to curry favor and further its Belt and Road Initiative (BRI), which Beijing has designed to flow through the Balkans and continue further into Europe. However, Croatia’s membership in the EU creates roadblocks for pursuing deeper economic or political interests in Croatia. The Croatian population’s risk acceptance provides Beijing the potential to influence Croatia through its BRI, if China can demonstrate how its increased influence will translate to socioeconomic opportunities for a population seemingly eager to take risks on new partners and opportunities.

Implications for Russia’s Interests

Croatia stands as a roadblock to Russia’s influence in the region. As a result, Russia only has minor economic investments in Croatia. It is plausible that Croatia is a larger threat to Russia’s aspirations in the Balkans more than ever before as Croatia has achieved both EU membership and has pledged to bring other Balkan states into the EU. Croatia and Russia’s somewhat confrontational relationship gives Russia little opportunity to increase its influence in the country even with Croatia’s risk acceptant nature. However, the ability to disseminate Russian propaganda and political influence is still possible for Moscow as in recent years Croatia has narrowly dodged political crisis after a 2016 vote of no confidence in its Prime Minister (Skrpec, 2017).

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Author(s): Astorino-Courtois, A. (NSI); Cooley, S. (Oklahoma State University); Dorondo, D. (Western Carolina University); Elder, R. (George Mason University); Kuznar, L. (NSI); Olsher, D. (Integral Mind); Popp, G. (NSI); Sleevi, N. (TRADOC); Suedfeld, P. (University of British Columbia); Wright, N. (Intelligent Biology)

Report Preview

Over the course of this project, multiple sets of questions were edited and added to the effort, resulting in a total of 29 questions. In this document, the individual teams have addressed as many of the questions in this list as addressed by their research and analytic efforts for this SMA project.

The list of 29 questions is divided into five sections throughout this report.

Section I: Regional Analyses includes questions examining the ins-and-outs, implications, and potential outcomes from a regional perspective. These questions investigate: key actor interests, the interplay of conceivable actions by these actors, conditions that would support or lead to potential outcomes. Many of the SMA teams were able to apply their individual methodologies or tools to address these questions. The modeling teams included TRADOC’s ATHENA, GMU’s Timed Influence Net (TIN) modeling, and Integral Mind’s cognitive simulation. The analytic approaches included: NSI’s I-R-C Analysis and Pathways Analysis, UBC’s Integrative Complexity, Intelligent Biology’s Cognitive Assessment, NSI’s Quantitative Discourse Analysis, and OSU’s Strategic Media Messaging Analysis. Finally, the SMA teams incorporated subject matter expert via NSI’s ViTTa effort and analysis from an expert from Western Carolina University.

Questions from Section II: DPRK Analyses focus internally on the stability of the DPRK state and economy. DPRK state stability are explored by modeling teams of ATHENA and Integral Mind modeling teams alongside the NSI analytic and ViTTa approaches.

In Section III: Proliferation v. Denuclearization, the I-R-C and ViTTa analyses thoroughly review conditions and options for denuclearization while the OSU team examines the messaging narratives from Russian and Chinese media. Three SMA teams, Intelligent Biology, UBC, and Integral Mind, take a cognitive approach to examining the way towards denuclearization.

Section IV: Regional Objectives, Actions & Implications covers future outcomes and explores the implications of regional actions. In this section, the modeling efforts by GMU and TRADOC submit future scenarios and examine the steps taken to get there. Two ViTTa analyses and work by the cognitive assessment and discourse teams address how the US can work with partners in the region.

In Section V: Cognitive Assessment of KJU Confidence, Cognition, and Discourse, four SMA teams shared a common corpus and conducted seven different analyses: quantitative discourse analysis, cognitive mapping, thematic content analysis, integrative cognitive complexity analysis and motive imagery scoring, application of the empathy checklist, basic emotive analysis, and discourse of deception. From these initial analyses, the teams went on to address questions of KJU’s regime confidence and assurance, and recommended communication strategies that would appeal to KJU’s communication styles and cognitive proclivities. For more in-depth reading, please refer to the full reports submitted by the individual teams. Links to these reports can be found in the appendix. Review the Part I report for a summation of the key findings across all of the individual efforts.