This article describes the role of the cultural expert as open source intelligence (OSINT) capacity within the military intelligence (MI) organization, supporting the operational planning process (OPP) in a complex battlespace. The article begins with the ontological foundation for the development of cultural knowledge in a battle space, then synchronizes this understanding with current effects based philosophy, and then illustrates how it is used in the field to support course of action (COA) production. Examples presented in this article specifically illustrate how cultural experts working with identity and norm attribution can help with network identification, generating hypotheses, populating iterative models, and target generation in an area of operations (AO).
Learn all you can about Ashraf and Bedu. Get to know their families, clans, and tribes, friends and enemies, wells, hills, and roads. - T.E. Lawrence, The 27 Articles of T.E. Lawrence (“Lawrence of Arabia”) The Arab Bulletin, 20th August, 1917 US Army Manual (2009), FMI 3‐24.2, Tactics in Counter Insurgency, March 2009
The role of cultural intelligence to support leadership in their decision‐making has once again come to the forefront of warfare. It is not as new as one would like to think, it was for the most part the mainstay of the British & French Colonial Empires. Here a few troops could maintain a colony through the knowledge of local cultural norms and identities: “/…/ captains, lieutenants and sergeants must perform with excellence in areas such as local politics, as well as social, education and economic development of the population.”2 My own experiences with the French Foreign Legion training the local military units in Chad, Central Africa, and Zaire, certainly impressed the value of integrating a high level of updated political and cultural intelligence into our daily planning. With limited logistical support and no close air support (CAS) ‐ our lives simply depended on it. 15 years later I can still remember of names of key actors in my areas of operations (AOs) from the Zaghawa and Tama clans of Eastern Chad.3
This article is an introduction to the role of cultural experts as a battlespace intelligence capacity to support our war fighting organization and its decisionmakers. To be clear, this article is not about how we use cultural awareness to win hearts and minds, it is about how we exploit cultural intelligence within our operational planning process (OPP) to support course of action (COA) production. This includes target generation and evaluation within an effects based approach to operations (EBAO) framework by our military intelligence (MI) organization. The mainstay of our organizational sense‐making4 support available to battlespace leadership is our MI organization and analysts. Intelligence in its most generic sense is the sum of what is known, integrated with new information, and interpreted for meaning.5 Therefore a fundamental assumption of this article is that operations in war are intelligence enabled, and commander driven. If operations are not intelligence enabled and commander driven, what are they enabled by?
It is within this organizational context, and the age of complex battle spaces, that having a cultural expertise within the MI organization has a direct role to play in COA production and the resulting actions in the battlespace. Focusing on the role of the cultural expert integrated in the processing stage of the MI cycle as an Open Source Intelligence (OSINT) capacity, this short article will only be able to present a limited picture of the role of cultural knowledge in the processing stage of MI. Specifically it will illustrate how cultural expertise concerning identity and norms can inform MI network identification and management, hypotheses generation and evaluation, and iterative model generation in an area of operations (AO). The article is divided into three sections; the theoretical foundation for exploitation of cultural knowledge in the battlespace based on social constructivism, existing war fighting philosophy, and illustrated examples of the integration of cultural expertise in war fighting.
PART I: A Constructivist Foundation
Sense‐making, at every level of decision‐making, in any organization or individual, in any situation, is subject to some ontological foundation or worldview that will inform that process. One can choose to engage the metatheoretical level in self‐reflection as to one’s methodology, as done in this article, or one can choose to ignore it, and hope by doing so it does not undermine your attempts to manage uncertainty in the search for knowledge. Discussions concerning knowledge development in war are no different, and despite my preferences for discussions grounded in anecdotes from the battle space, it is my belief that the management of uncertainty is always better served by a self‐reflecting engagement of the ontological positions we inherently adopt when building those anecdotes. Symmetrical measures for strategic reference within the logic of strategic choice6 for parties to a conflict can no longer stand alone. The last 15 years has seen the development of war fighting environments that depict two distinct ontological7 domains for strategic reference, one physical and the other cognitive.8 An example of this shift in strategic interaction understanding comes from the Taliban leadership themselves, where 15 years ago they defined victory by the taking of Kabul (physical dimension) – today they define victory by a cognitive term roughly translated from several Pashto words as – legitimacy (cognitive dimension). They plan their operations to de‐legitimize the Afghan government. Conversely, based on a two pronged strategy promoting security and development, the NATO plans operations to legitimize the Afghan government.
Social constructivism as it is used here to explain battlespace complexity is defined as the view that the material world shapes and is shaped by human action and interaction dependent on dynamic normative and epistemic interpretations of the material world.9 Constructivists consider interpretation as an intrinsic part of social science that stresses contingent generalizations, meaning that they do not freeze our understanding but open up the social10 world. The issues currently focused upon, originate from the belief that reflexive knowledge (interpretation of the world) when imposed on the material reality of the world becomes knowledge for the world (see Fig. 1). This understanding suggests that ‘social facts’ such as identity or norms, can act as the objects of the intelligence cycle emerging from the interaction between knowledge and the material world – intersubjectivity11 – neither of which are fixed.12
Fig.1 Constructivist Sense‐Making:
Adopting a constructivist framework provides a theoretical foundation for our understanding of complex battle spaces that incorporates both the cognitive and physical domains. Ontologically speaking it is this intersubjective dynamic that suggests directly that understanding the battlespace does not just depend on understanding the material ‐ but also the ideational.13 That concepts such as culture, identity, and norms that have played a role in understanding the international environment14 in which we have made security policy for over a decade,15 can also play a role in battle space sense‐making.
Epistemologically, constructivism is well developed as the methodological bridge16 between positivist and behavioural approaches; this is extremely helpful in terms of sense‐making in a complex battlespace, opening the social sciences to a greater degree than ever before, for use in MI analysis and operational planning, without rejecting the material/efficiency concerns of positivists.17
Traditionally MI has been dominated by positivist approaches to sensemaking based primarily on material/efficiency descriptions within the time and space dimensions of World War I, World War II, and the Cold War,18 where the social‐sciences were given very little place in MI.19 This is not an easy shadow for MI to shake. Constructivism as a theoretical approach, like intelligence analysis as a process, does not lay claim to an objective certainty. Instead, it is in the fundamental nature of both to advocate a pragmatic approach to managing uncertainty, a characteristic also shared with C2 research in general.20 Civilian intelligence analysis has for some time used constructivist techniques to supplement or even direct collection processes.21 Profiling personalities or governments, such as assigning them an identity as a radical or a moderate, has been used to help predict which norms are relevant, and based on those norms, predict patterns of behaviour.
In Ted Hopf’s “Promise of Constructivism in International Relations Theory” presented in International Security in 1998, there is a clear theoretical outline of a brand of constructivism fully capable of an instrumental role in the MI cycle, particularly where it concerns the attribution of identities and norms. Identities are understood as having three accepted functions in a society. They tell you who you are, and who others are, and they tell others who you are.
Identities are necessary in social systems to maintain a minimum level of predictability or stability.22 Therefore any actor that is socially organized has an identity as a unit in the system, and this identity implies it has its own preferences and consequent actions within the system.23 Thus this identity is a functional concept in MI analysis methodology because it can contribute to establishing the subjective context for evaluation in a battle space. A conventional constructivist understanding of identity also allows evaluative access to norms, contributing to the construction/evaluation of strategic preferences. This in turn may be used to make predictions on how the actor will react under a given set of circumstances in the battle space. It does so by formally recognizing the existence of the intersubjective dynamics concerning the construction of an actor’s identity, including that the producer of the identity is not in control of what it means to others, and will therefore also include an ‘intersubjective’ degree of influence over the final meaning.24
Norms are also viewed by conventional constructivists as a functional concept and can generally be defined as the ‘shared’ understandings of standards for behaviour. The first is that norms are embedded in webs of preexisting meta‐norms. This allows for the establishment of a fixed understanding of systemic influence within the relevant system of social exchange such as a battlespace. The second, it allows for the establishment of fixed understandings where it concerns the perceived behaviours within the system of social exchange. Or if you will, it allows for the nature of behaviours adopted, producing objectively recognizable non‐material influence on decision‐making, to be fixed for consideration within a subjective assessment. Finally, and very important to the conceptual linkage of norms to strategic preferences, is that norms define interests and identities.25 Here the actual application of the intersubjective dynamic surrounding the influence of norms meets its’ contextual end state within MI through the evaluation of preferences and how actors go about achieving them.
Furthermore, constructivism’s inherent purpose is to understand the role of intersubjective interaction between the cognitive and physical domain, consequently it is naturally at ease with the current EBAO26 philosophy that informs current operational doctrine in the West. Quite simply both are based on recognition of the cognitive and physical domains with regards to sensemaking.
Part II: Existing Doctrine & Philosophy
The constructivist understanding presented here currently lies within a military context defined by a NATO in transition27 that started in the 90’s and a high profile mission in Afghanistan. The development of the concepts in this paper are not immune to this context, and are heavily influenced by what EBAO represents as a sense‐making framework for complexity requiring both the social and physical sciences.28
The analytical challenges of engaging this complex environment are reflected well in Tom Czerwinski’s ’billiard’ metaphor and the concept of tagging.29 NATO’s PMESII30 guideline attempts to do just that with the complexities of an asymmetric battlespace by dividing it up into different dimensions for strategic reference when decision‐making or planning. Instead of there being just a military dimension, they must now consider PMESII dimensions of their battlespace.31 By doing so the PMESII network hopes to make the predictions of the non‐linear interactions more manageable.
PART III: The Role of Cultural Experts in War Fighting
Most intelligence cycles32 in the military are iterative processes that reflect four stages; direction, collection, processing, and dissemination, in some way or form (see Fig.3). The purpose of the intelligence cycle is to deal with all the available information, decide relevance, search for the missing information, process it into something even more relevant, and make it ready for distribution.
Fig. 2 PMESII – A System of Systems Understanding:
Complexity in modern warfare requires more than Order of Battle styled reports (ORBATS.)33 ORBATS are one of the traditional products of basic MI output. It usually covers tracking primarily material/efficiency concerns from the military dimension such as aspects of the opponent’s equipment, capabilities, performance,34 and some relatively light socio‐political matters relative to leadership or logistical support.35 For the implementation of EBAO to be effective ‐ it must be supported by relevant36 intelligence collection from non‐military dimensions and an expansion of the knowledge base primarily through non‐ORBAT information.37 The nature of MI analysis has traditionally been descriptive in terms of the time and space dimensions.38 However EBAO requires a great deal more predictive battlespace awareness (PBA)39 for the commander and it is here the challenges lie in terms of adjusting the training of our MI analysts. In short, applying PMESII to meet the challenges of the complex battlespace within an EBAO context will require a shift from a focus on descriptive analysis to predictive analysis in terms of the nature of MI analysis40. It is here cultural experts have a role to play in the war fighting organization. Unclassified knowledge experts of any kind are an OSINT capacity, and current conflicts call for a greater role for cultural knowledge experts (see Fig.4).
The remainder of this section presents several examples of how cultural expertise can be exploited in the Operational Planning Process (OPP) through its contribution to the MI cycle. The examples will focus on the contribution of expertise concerning identities and norms to the MI cycle and COA production.
(1) Network Philosophy
The technological aspect of network centric warfare (NCW) is no longer the main challenge41, it is the human and social networks that we are now grappling with to improve our sense‐making in the battlespace.42 From the perspective of a constructivist approach to managing complexity, network thinking acts as method managing and communicating a representation of the intersubjective relationships between the physical and cognitive domains in the battlespace. Usually depicted as a system of systems (such as PMESII), it slows the intersubjective dynamic down relevant to the task at hand, and enable opportunities for a more comprehensive understanding of actions and effects within the EBAO framework. Fig.5 illustrates how network thinking can frame the intelligence cycle relevant to the commander’s intent in an AO in Afghanistan. The objective represented here is simply for the Coalition Forces (BLUE) to move more of the undecided population (WHITE) over to supporting the Government, than there was when they first arrived in theatre. Cultural expertise will come into service here where it concerns the attribution of identities and their objectives, for example vis‐à‐vis WHITE, as well as consideration of how their own actions affect this system as a whole.43 Ideally this would require cultural experts involved in the Intelligence Preparation of the Battle Space (IPB), input into the tasking or direction of collection assets, and management of collected data relative to the established framework of AO networks. It is important to note here that generic skills in terms of establishing or attributing identities and norms (patterns of expected behaviour), are more important than culture specific knowledge.
Based on this network centric framework for commander’s intent in the AO, standing iterative models for the AO can be established and maintained that will assist in timely effects assessments. For example in Fig.6, a standing model representing the compounds of the AO and the political leanings of their owners, if kept up to date, will support the Commander in making a timely decision. This could be whether or not to risk close air support (CAS) in an engagement, vis‐à‐vis their objective of moving undecided support towards the government. MI analysts with cultural expertise, particularly where it concerns attributing identities (in this case RED, WHITE, BLUE,) will be the most effective at keeping this standing model as accurate as possible through the iterations. Simply because they should be in a better position to judge what collected intelligence suggests in terms of populating the model based on identities.
From the standpoint of the MI cycle, cultural experts will contribute directly to how we determine what should be tasked, collected, processed, and disseminated. From a knowledge development standpoint, MI cultural experts as an OSINT capacity will assist in building our networks to counter opposing networks in complex battle spaces. Determining which networks are relevant to the commander’s intent for an AO, and what can be managed (information collected, collated, and interpreted) in a timely manner by your own knowledge development network is very challenging (see Fig.7.) It stands to reason that if local norms and customs play a large role in the behaviours and actions of actors in an AO, having MI analysts with a cultural expertise will assist in COA production.
(2) Iterative Modelling
From a constructivist standpoint iterative modelling converts the dynamism behind network thinking to more practical applications of managing intersubjectivity, within a ’tagging’ framework of inter‐systemic relations such as PMESII. It is also an essential skill if we are to have any chance at maintaining timeliness in a more complex battle space. A model can be a replication or representation of an idea, an object, or actual system.44 More importantly, it often describes how a system (or network) behaves.45 Models can be used to describe, explain, and predict. They can be used in the intelligence cycle to create baseline references and for building up databases of knowledge that can be manipulated to advantage (as in Fig.6). Specifically, the ability to systematically produce relevant mental models to increase the overall effectiveness of MI output is paramount.46 EBAO inherently places the weight of modelling application on prediction in terms of qualifying desired and undesired effects47 and the production or assessment of actions.
Fig.8 is an example of simple iterative modelling put into the Afghanistan context, depicting a local Improvised Explosive Device (IED) cell, and another network structure reflecting the local Taliban Command & Control (C2) structure or an ‘outer‐shura.’ In both models the organizational structure, process, and function are represented, and therefore are well suited for use with MI cycle iterations. However these networks exist against a background of social and cultural complexity. Providing cultural perspective on the context in which these networks exist is an important role for cultural experts. Basic iterative models for an AO quickly become part of the overall system of systems understanding through link analysis as well. Fig. 9 illustrates how a comparative analysis of the intelligence populating the two basic iterative models in an AO produce links between them that can be quickly represented and shared with other analysts. However understanding the nature of these links must include due consideration to the existing cultural dynamics that form the backdrop to any actions. It is here cultural experts, as part of an integrated OSINT platform, provide insight and perspective into COA production.
(3) Hypotheses Generation and Evaluation
From a constructivist perspective hypotheses generation and evaluation are the methodological skills necessary to slow intersubjectivity down by analytically forcing different systems into dynamic relationships with other systems for analysis. Managing a system of systems framework such as PMESII inherently places the weight of analysis and estimates on hypotheses defined relationships, primarily between PMESII domains. Managing the social dimension is the primary role of cultural experts in the MI cycle. They can do so through managing standing iterative models, such as land ownership by tribe, thus assisting in the generation of useful dynamic hypotheses for the AO. Fig. 10 and Fig. 11 illustrate how crossing known firing positions in an AO with known tribal divisions within the AO can produce some useful hypotheses for use by the MI and OPP cycles. Therefore ased on this, target generation and evaluation resources can be focused on key members of Khel B’s C2 structure, mutually supported by focused non‐kinetic operations synchronized with psychological operations (PSYOPS.) The validity of the dynamic hypothesis can be checked with each MI cycle iteration.
Fig. 10 Known Firing Positions in AO vs. AO Tribal:
Resulting dynamic hypothesis for use in the OPP for COA generation: Members of the Khel (Clan) B are more likely to directly support the Taliban than members of Khel A, C.
Within this context cultural expertise can also be used for the generation and evaluation of targets relative to an AO. In short, the use of pattern of life analysis to help focus collection assets, and ‘box in’ high value targets related to these models, are of particular use. Here local norms or customs could help us predict when a target will be required to talk or meet with someone. Elements such as tribal rankings and traditional communication processes are extremely useful to narrow the focus of collection assets and generate targeting opportunities.48 Fig.12 and Fig. 13 represent the same process but with processed signals intelligence (SIGINT) analysis exploited together with the relevant tribal information for the AO. Again the ‘what to put together’ and ‘how’ will sometimes be the result of already existing hypotheses, such as in this case the hypothesis used by the SIGINT to relate the SIGINT hits to movement and a pattern of transport with confidence. The role of the culture expert is to exploit the MI cycle to insure that such relevant tribal information is as accurate as possible and therefore giving the produced hypothesis validity in its role of COA production support.
Fig.12 Analysed SIGINT Hits vs. AO Tribal:
Resulting dynamic hypothesis for use in the OPP for COA generation: Members of Khel B are more likely to have knowledge of Taliban weapons caches in AO then members of Khel A, B.
Cultural expertise contributes directly to making the network philosophy, iterative modelling, and hypotheses generation and evaluation more effective in complex battle spaces. This short article attempted to illustrate that cultural expertise not only has a direct role to play in the MI cycle and COA production, but that this role is built on solid ontological foundation, that in turn, synchronizes well with current EBAO philosophy. These techniques have been in use by some elements of Western MI; however there is plenty of room for further research and a synchronization of standards. In the process we could build a common MI analytical language for use in complex battle spaces, and for promoting sense‐making tools, that will last well into the 21st Century. The further development of culture experts as an OSINT capacity for MI will likely be one of those tools.
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2 Raoul Giradet, La Société Militaire de 1815 à nos jours, Perrin, 1998, 228.
3 For a good overview of this period see Colonel Henri Boré, “Complex Operations in Africa,” Military Review, March –April 2009, 65‐71.
4 See the growing Command & Control (C2) epistemology engaging power to the edge (Alberts & Hayes, 2005) research with a specific focus on agile sensemaking (Alberts and Hayes, 2005, 27). The building of cultural expertise as an OSINT capacity as presented here will affect common C2 variables such as information, predominant information flows, information management, and sources of information directly, because of its focus on military intelligence (MI) analysis and planning. As a result, secondary affects on key C2 variables such a Command, Leadership, Control, Decision‐making, Organizational Processes (Alberts & Hayes, 2005, 218; SAS‐026 NATO 2002; SAS‐050 CCRP/NATO 2006).
5 This understanding includes classified and unclassified sources of information or knowledge and is widely accepted in intelligence studies. The inclusion of unclassified sources has always been there, but their role has become prominent as Open Source Intelligence (OSINT) in tact with the quantum leap forward of internet information sharing.
6 See Luttwak 2001, 3‐50; Luttwak 1998.
7 Understood in this paper as simply the nature of reality.
8 Nicholson 2006, 133‐136.
9 Adler 1997, 322; Adler 2002, 104‐109.
10 A general reference to the generic meaning in social science.
11 See conventional constructivism in Ted Hopf’s “Promise of Constructivism in International Relations Theory” presented in International Security in 1998.
12 Adler 1997, 327‐328.
13 Checkel 1998, 324‐348; Reus‐Smit 2001, 218.
14 See Katzenstein 1998, 1993.
15 The 1990s saw the fastest growth of constructivist thinking in security policy analysis: Hopf 1998; Barnet 1996, 1998, 1999; Finnemore 1993, 1996, 1998, 2001; Kratochvil 1996, 1989; Klotz 1995; and Wendt 1992, 1995, 1999.
16 See Adler 1997, 318‐363; Hopf, 1998; Checkel 1999, 2001
17 The US Marine Corps, Vision and Strategy 2025 document articulates this quite well within a military context.
18 For example see Daniel Yergin 1977, 123; David Hallloway 1983.
19 See Katz 1989, xii ‐xv.
20 See Johnson 1998, 1999.
21 See Goodman 2003, 3‐12; Herman 2004, 125‐126. For some of the earliest examples see Katz 1989, 137‐164 and the role of social science in the Cold War.
22 See Hopf 1998, 75. These three aspects of identity, made the concept more manageable within international relations when examining the behaviours of states. The same understanding is adopted in this study to provide a functional approach to the identification of normative behaviours.
23 Katzenstein, 1996.
24 See Hopf 1998, 176‐178. Hopf was referring specifically to the state actor, whereas I am referring to actors within a battlespace.
25 See Klotz 1995, 19‐20; Katzenstein 1996, 33‐75
26 EBAO calls for an expansion and exploitation of our knowledge base to support the planning, execution, and assessment of actions in a complex battlespace defined by a physical and cognitive domain.
27 See Rogers 1996, 22-23.
28 See Phister et al. 2004,1-2;Czerwinski 1996, 21-132;Owens 1995,35-39.
29 See Czerwinski 2003, 114-115.
30 PMESII – Political, Military, Economic, Social, Information, Infrastructure domains of a battlespace and represents a system of systems approach. It can also be portrayed accurately as interacting social networks.
31 NATO Bi-Strategic Command Pre-Doctrinal Handbook, 2007, 5-3.
32 For generic understanding see Clark 2004, Ch.1; Herman 2004, 293-296; Mitchell 2002, 486.
33 I am using the UK MOD Doc 1999, 1A‐2 definition.
34 For a good example of the comparative tech focus see Libicki & Johnson 1995, 48‐49.
35 Military intelligence output is divided generically into basic and current intelligence – current intelligence is situational and not referential in character.
36 See Schoffner 1993, 31‐35.
37 For example, ASCOPE in US Army Manual 2009.
38 See Phsiter 2004, 2. Known as Intelligence Preparation of the Battlespace (IPB), its purpose is to keep the commander aware of recent, current, and near term events in the battlespace.
39 Using SAB‐TR‐02‐01 2002 definition.
40 See Mitchell 2002, 481‐485.
41 See the ‘father’ of EBAO, Smith 2006, 195‐238; Smith 2005.
42 See Holmes‐Eber & Kane 2009, 31‐35.
43 This network model is an example of constructivism in action, where key concepts such as identities and norms, or patterns of expected behavior (Hopf, 1998) are exploited in conjunction with predictions or recommendations of physical actions, or COA production.
44 Taken from SAS 050 2007, 23.
45 See Clark 2004, 29.
46 See Mitchell 2002, 480‐485; Heuer 2006, 47‐105.
47 See Smith 2006, 149‐193.
48 Unfortunately actual targeting examples could not be cleared for an openforum at the time of writing.