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Intelligence Analysis: Behavioral and Social Scientific Foundations 9 Social Categorization and Intergroup Dynamics Catherine H. Tinsley Imagine that the Central Intelligence Agency (CIA) suspects a Pakistani national living in Canada is planning a terrorist attack against the United States. The CIA has been working with Canadian authorities to track the man’s movements and analyze his future intentions. Border patrol has been alerted because the suspect appears to be part of a Canadian-based terrorist cell that may soon try to enter the United States. The National Security Agency (NSA) has been contacted to monitor the suspect’s telecommunications. Last week, the suspect phoned a U.S. citizen and resident, which triggered the involvement of the Federal Bureau of Investigation (FBI). As this scenario illustrates, current threats to U.S. security can be global, can come from varied nonstate actors (including isolated individuals), and can require extensive coordination across intelligence community (IC) agencies. Indeed, the IC has recognized a need to integrate information and analysis, as captured in various agencies’ strategic plans. The Director of National Intelligence writes that “information sharing is a top priority” and that we must move from a mentality of “need to know” to a mentality of “responsibility to provide” (Office of the Director of National Intelligence, 2008). The Defense Intelligence Agency (DIA) Strategic Plan lists “support[ing] unification of effort across the IC to promote horizontal integration fostering access to data and sharing information” as one of its five major strategic actions (Defense Intelligence Agency, 2007). This coordination goes beyond simply the need to share information with each other. Instead, it requires analysts to understand and appreciate the experience and knowledge that each different agency brings to the table. This deeper
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Intelligence Analysis: Behavioral and Social Scientific Foundations understanding will help attenuate communication problems (Fischhoff, this volume, Chapter 10), such as agents talking past each other or dismissing each other’s analysis. Unfortunately, cross-agency collaboration can be thwarted by the familiar pathologies found in all intergroup endeavors. These include misaligned organizational incentives, ossified bureaucratic policies, and conflicting political pressures. For example, agencies within the IC are “mission specific” (Sims, 2005), meaning they serve different customers who may be asking different analytic questions about the same target or event. Each agency in the IC naturally has “its own terminology, routines, and expectations about what people can ask for” (Simon, 2005, p. 150). Moreover, interagency “turf wars,” which appear to arise from historical inertia and budgetary conflicts (Sims and Gerber, 2005), provide inherent challenges to interagency collaboration. Discussing any particular bureaucratic, political, and budgetary conflicts is beyond the scope of this chapter, which instead focuses on how the pluralistic structure of the IC can engender cognitive and motivational biases that hinder effective cross-agency collaboration. Special attention is paid to the agency grouping and how social categorization processes can influence individual behavior. Social categorization is the process by which we make judgments about individuals (and who they are in relation to ourselves) based on their group membership. When we encounter other people, we tend to encode not only individual information about that person, but also social information—in particular, whether he or she is a member of one of our “in-groups”—the groups to which we belong—or is an “out-group” member, or outsider. In the context of the IC, where a salient group boundary is agency (or subagency) affiliation, social categorization suggests that analysts register whether other analysts are members of the same or different IC agency.1 This encoding can produce mental roadblocks to coordination by eliciting well-documented intergroup dynamics, including differentiation, ethnocentrism, and integration neglect (explained below). These roadblocks are not unique to the IC, but rather are fundamental 1 This agency grouping does not mean that other social groups are irrelevant. Indeed, within some agencies there are large distinctions between analysts and collectors (e.g., the CIA). Groups are people’s subjective representations of others vis-à-vis the self. These groups may exist because people interact regularly and share a common fate (Campbell, 1958), such as with workgroups, or groups may be large collectives where individuals are connected by virtue of common symbolic attachments (Geertz, 1973). The motivational and cognitive biases discussed in this chapter would pertain to any social group distinction that is relevant for the actors involved. For simplicity of presentation, however, I choose the agency level as the focal social group because this follows both the formal organizational structure and other work describing agency affiliation as a dominant social category in the IC (see Sims and Gerber, 2005, or Fingar, this volume, Chapter 1).
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Intelligence Analysis: Behavioral and Social Scientific Foundations aspects of organizational life, unless deliberate efforts are made to overcome them. More relevant to the IC is how these dynamics play out and how they might be managed. Before describing the usual pathologies that can arise from an intergroup environment, I briefly detail research in organizational behavior to explain why these pluralistic structures evolve. In most organizations, and particularly for the mission-diverse IC, social groups function to simplify tasks and create high-quality (i.e., well-grounded and solidly analytic) products. The idea is not to restructure the IC to rid it of multiple social groups (which is likely to be impossible anyway), but rather to attenuate negative externalities that this intergroup environment can produce. INTERGROUP DYNAMICS AS A FACT OF ORGANIZATIONAL LIFE Social groups exist in all organizations and often create cognitive and motivational roadblocks to cooperation and collaboration. Despite their pernicious consequences, organizations cannot eradicate groups. For organizations, groups are necessary for efficient coordinated action. For individual employees, groups are necessary for constructing identity and making sense of their workplace. The Organization’s Need to Form Groups All organizations differentiate—meaning they split their employees into different groups (Lawrence and Lorsch, 1967). Differentiation allows for specialization, production efficiency, and accountability. Imagine if every employee was responsible for the same job tasks—no one would master any special skills, and failure to accomplish job tasks would rest with everyone and hence with no one. The IC can be modeled as a decentralized conglomerate organization (Chandler, 1962). In one organizational chart2 the Office of the Director of National Intelligence is at the top. One level below it are the program agencies (CIA, DIA, FBI, NSA, etc.). On the next level are the “departmental agencies” or those that primarily report directly to a Cabinet member (Drug Enforcement Administration, Department of Homeland Security, Department of State’s Bureau of Intelligence and Research (INR), Department of the Treasury, etc.). On the final level are the “service agencies” (Army, Air Force, Navy, Marine Corps, and Coast Guard Intelligence). Of course, the IC can be grouped in other ways (e.g., on the basis of whether the agencies’ primary function is collection 2 Chart published in National Intelligence: A Consumer’s Guide to National Intelligence (Office of the Director of National Intelligence, 2009, p. 9).
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Intelligence Analysis: Behavioral and Social Scientific Foundations or analysis, or whether their primary concern is foreign intelligence or law enforcement). Yet, alternative ways of grouping personnel does not threaten the central thesis that the multiorganizational character of the IC creates groups that differentiate themselves from one another and engender cultural barriers to collaboration. The important point is that the IC is structured, and the basic structural unit is the agency. In the IC, the first order differentiation of analysts is based on agency affiliation. The structure allows each agency to produce intelligence products tailored to the needs of its primary customer base. For example, in April 2001, when a U.S. EP-3 surveillance aircraft collided in mid-air with a Chinese fighter plane and the EP-3 landed on the Chinese island of Hainan, different IC agencies produced intelligence assessments that answered very different types of questions reflecting the interests and responsibilities of their different customers. Thus, the INR, whose primary customer is the Department of State, produced intelligence to answer questions such as: What are the diplomatic implications of the collision? What signals has the Chinese government sent that might help to resolve the crisis? What is the government telling its own people about the incident? The DIA, whose primary customers are in the Department of Defense, addressed different questions: Are the Chinese moving any military assets? Are there any signs that units have increased readiness levels? What are Japanese and South Korean media saying about the incident and U.S. forces based in those countries? The NSA and National Geospatial Agency (NGA) addressed more technical questions about the types of equipment on board and what the implications would be of some or all of it falling into the hands of the Chinese government. The CIA, reflecting its broad customer base and responsibilities, provided a second take on many of the questions posed and answered by other agencies. These illustrations make clear that specialization is necessary, appropriate, and essential to address specific customer concerns. Only by being close to customers can analysts know what they require and produce truly useful intelligence products. Throughout the differentiation process, organizations make trade-offs about where and how much to differentiate, with the aim of maximizing goals such as: (1) resource efficiency, (2) time efficiency, (3) employee accountability, (4) responsiveness to the environment, and (5) adaptability over time (Nohria, 1991). For the IC, resource efficiency would be the ability to produce quality intelligence with economy of labor and capital; time efficiency would be the ability to do so rapidly. Employee accountability describes the ability to hold employees responsible for required activities. Responsiveness to the environment means satisfying the requirements of U.S. policy makers as well as the need to protect sources and methods. Finally, adaptability refers to the ability to innovate to meet changing
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Intelligence Analysis: Behavioral and Social Scientific Foundations security threats and policy decisions. To maximize this portfolio of issues, the organization decides how much to differentiate and where to draw the distinctions. Naturally, this differentiation process creates groups (e.g., agencies) that have their own unique intelligence priorities and routines. Although agencies may share common rules for evaluating source reliability or explicating underlying assumptions, the agencies develop different decision rules on what topics to cover and different standard operating procedures on which streams of data are the most reliable to use. For example, the INR may rely more heavily on diplomatic and open-source information; the DIA may rely more heavily on military channels; the CIA may focus primarily on clandestine human intelligence collection; and the FBI may use other human informants with information relevant to law enforcement. These decision rules and procedures are likely to align with the agency’s mission, but they will in some sense dictate how data are collected, fused, used or discarded, interpreted, and presented. Thus it is not surprising that differentiated agencies can produce intelligence that is not completely uniform, even if each is a well-researched product reflecting solid evidence and analysis. Some systemic tension is natural; the idea is to understand and manage it rather than try to eliminate it. Individuals’ Need to Group Differentiation benefits organizations through efficiency gains and specialization. This specialization can also benefit individuals because it encourages employees’ skill development. Yet skill specialization can also make the employee more dependent on the organization because high-asset specificity cuts both ways (Williamson, 2002). Do individuals benefit from the presence of multiple social groups in their environment? Some have argued that social categorization processes (constructing social groups) is a natural human process. As social creatures, we tend to carve up our social landscape into groups (see social categorization theory, Deschamps and Doise, 1978; Vanbeselaere, 1991), in part to construct our own identities (Tajfel, 1969; Tajfel and Turner, 1979). Generally, we come to understand who we are by virtue of the groups to which we do and do not belong (Smith and Berg, 1987). In fact, we tend to view other people, first and foremost, as members of a particular social category (in-group or out-group) (Brewer and Feinstein, 1999; Fiske et al., 1999). This social categorization happens relatively effortlessly (Fiske, 1998) and is often based on visually prominent and culturally relevant features, such as age, race, and (here) agency affiliation (Brewer and Feinstein, 1999; Fiske, 1998). Of course, people have multiple in-group identities (Stryker and Statham, 1985; Tajfel, 1978), but when these categories compete for
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Intelligence Analysis: Behavioral and Social Scientific Foundations attention, one usually dominates, depending on contextual cues (Brewer and Pierce, 2005). For example, a female professional may think of herself as an analyst at work and as a mother at home. Moreover, an analyst might think of herself as an analyst when talking to collectors and as a CIA employee when talking to a DIA analyst. This type of automatic characterization not only helps us self-identify, but also allows us to form a basic understanding of a socially different “other” (Bodenhausen et al., 1999). Social groups can be thought of as social categories, and people tend to form prototypic representations of these categories in the form of exemplary members (actual members who best embody group features) or ideal members (an amalgamated abstraction of group characteristics) (Kahneman and Miller, 1986). As individuals self-categorize, they represent themselves less as unique individuals and more as embodiments of the relevant prototypic features (Hogg and Terry, 2000). That is, self-categorization cognitively assimilates the self with the in-group prototype. Therefore, this social grouping process gives an individual direction or guidance because group prototypes “describe and prescribe perceptions, attitudes, feelings, and behavior” (Hogg and Terry, 2000, p. 124). People tend to conform to their groups (Asch, 1955) for both cognitive and motivational reasons. Cognitively, conformity reduces uncertainty—when confronted with a situation, individuals know how to react based on prototypical group norms. Social norms carry both a descriptive and injunctive/prescriptive function (Cialdini and Trost, 1998). Motivationally, conformity increases that member’s attractiveness in the eyes of other in-group members (Mowday and Sutton, 1993). Thus social categorization processes give people a sense of identity at work (who they are) and provide them with guidance on how to behave. Yet, these processes function like any other heuristic in constraining people’s thoughts (e.g., expectations and attitudes about people and situations, and attributions for events) (Salancik and Pfeffer, 1978) and behavioral repertoire. Social categorization may be natural, effortless, and in some ways beneficial, but is not without the ethnocentric consequences discussed next. HOW SOCIAL CATEGORIZATION INFLUENCES INDIVIDUALS As noted above, individual thought and behavior is influenced by the social environment, such as how employees are split into groups, what behavior is rewarded, and what institutional routines develop. Interestingly, people are often unaware of the extent to which their thought and behavior have been shaped by their social context. We often believe that we think and act as unconstrained free agents, when in fact, our “rational” thoughts and behavior, including our awareness and imagination, are bounded by
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Intelligence Analysis: Behavioral and Social Scientific Foundations our own frames of reference. In particular, we underestimate the extent to which our thoughts and behaviors are shaped by subjective construal rather than direct perceptions of an objective reality (Griffin and Ross, 1991). “Culture” is one term that is often used to label a shared frame of reference or a shared social context. Culture can be defined as a constellation of values, assumptions, beliefs, behavioral norms, and routines that define a group of people united by ethnic or organizational membership (Benedict, 1934). It is what makes a collection of people a “group” (or as Tylor, 1871, first described it—culture is a “superorganic” entity). Culture offers members a social blueprint that interprets stimuli and guides group members (Boas, 1940). Groups can differ according to how tight or how loose their culture is, meaning how much “deviance” group members are allowed before being sanctioned (Triandis, 2002).3 Most groups have complex cultures, meaning one type of behavior (e.g., competition) is rewarded in some contexts and a different behavior (e.g., cooperation) is rewarded in another context.4 Yet, all cultures outline expected beliefs and behaviors (although they may be context dependent) and reward conformity to these ideals. In this way, cultures shape individual thought and behavior. Decades of research supports the idea that culture influences group members’ thought and behavior by showing that people of different cultures respond to the same stimuli with different attitudes, beliefs, and activities (Berry, 1980; De Vos, 1975; Erez, 1986; Leung and Bond, 1984; Triandis, 1989; Wagner, 1995). Dearborn and Simon (1958), for example, showed that socialization through organizational training systems produces “managerial mindsets” that limit how people conceptualize problems and solutions. In their study, they asked groups of executives from a manufacturing firm to study a particular company, and asked the executives to identify the company’s most pressing problem. The study had three groups from three functional cultures—sales executives, production executives, and human and public relations executives. Each cultural group viewed the same company data through a different lens, and thus offered three entirely different proposals about the company’s most pressing problem (sales, operations, and human relations, respectively). 3 Furthermore, depending on the size of the cultural group boundary, cultures can include “subcultures.” Echoing footnote 1, for example, the CIA can have a dominant culture (certain values, norms, and routines), then different subcultures for analysts versus collectors. This level of analysis issue should not detract from the basic sociocognitive dynamics outlined in the chapter. Social categorization processes can occur at any organizational level. The purpose here is simply to document the intergroup dynamics that emanate once these categorization processes occur. 4 For more on cultural complexity and its relation to context-dependent behavior, see Brett et al. (2007).
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Intelligence Analysis: Behavioral and Social Scientific Foundations Similarly, Tinsley and Pillutla (1998) found that socialization into different national cultures led people to interpret the same negotiation task in different ways. One cultural group assumed the goal of the negotiation was to maximize joint gain, whereas the other cultural group assumed the goal was to minimize the difference between each party’s outcomes. This goal discrepancy corresponded with the groups’ actual outcomes and with parties’ satisfaction with those outcomes. In sum, cultural profiles offer members a roadmap for interpreting stimuli and guiding behavioral reactions. At the same time, by focusing attention and behavior, these roadmaps also constrain thought and action. By institutionalizing an optimal way to think and behave, these roadmaps can suggest that other thoughts and behaviors are suboptimal or even wrong. Accordingly, interactions among members of different cultural groups that have different missions, approaches, and routines can be strained. INTERGROUP DYNAMICS FROM SOCIAL CATEGORIZATION PROCESSES One of the most robust findings from cultural research is that of ethnocentrism, which literally means putting one’s own group at the center of the universe. Anthropologists (Boas, 1940; Mead, 1964; Kroeber and Kluckhohn, 1952; Lowie, 1966; Malinowski, 1944) find that people learn to be ethnocentric through socialization in a particular social system, which rewards appropriate thought and behavior while sanctioning inappropriate thought and behavior. Hence, members come to believe that their group’s values, beliefs, behaviors, and organizing principles are superior to those of any other group. In the IC, this might be reflected in the CIA believing its practices to be “the gold standard” (Goss, 2005) or in the INR being promoted as “the biggest little intelligence shop in town” (Aspin quoted in Ignatius, 2004). Evolutionary psychology considers ethnocentrism to be an innate outgrowth of nepotism (van de Berghe, 1981), meaning ethnocentrism has a natural survival value for the group. In-Group Bias Psychologists tend to focus on the costs of ethnocentrism, including “in-group bias” or the tendency to see members of one’s own group in a more positive light relative to members of other groups (Tajfel, 1970). For example, in the IC, this might be reflected in a predisposition to favor types of information (e.g., clandestine human intelligence) produced by the agency in which the analyst is embedded. Across a variety of studies outside the IC, people have judged members of their in-groups to be smarter, more attractive, more
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Intelligence Analysis: Behavioral and Social Scientific Foundations cooperative, fairer, more trustworthy, and more hard working than members of out-groups (cf., Brewer, 1979; Tajfel, 1970, 1982). This prejudice generally seems to entail withholding positive traits from the out-group rather than actively assigning negative traits to them (Fiske et al., 1999), and it is found to enhance the status of the in-group rather than degrade the out-group (Tajfel, 1982). Strikingly, this in-group bias occurs not only across real-life groups, but also can be activated with groups created in the laboratory based on minimal or random criteria, such as having the same birthday or similar final digits in Social Security numbers (Brewer, 1979; Brewer and Kramer, 1982). Moreover, in-group bias can occur with or without direct interaction (e.g., attitudinal biases that arise simply through observation or awareness of an out-group member), and without any prior personal history between the parties involved (Kahn and Zald, 1990). From a practical standpoint, in-group favoritism is problematic in social landscapes with more than one group. First, it leads to discrimination, with in-group members being treated better than out-group members. People award higher monetary payouts and emotional payouts, such as helping behavior, to in-group members than to out-group members. Second, the bias leads to perhaps the most common problem in intergroup relations, “reciprocal antipathy,” or the difficulty of getting groups to cooperate with each other. As Kramer notes (2005, p. 407): The problem of securing cooperation between interdependent groups has been a central and recurring theme in the study of intergroup relations from its inception (Sherif, 1966a; Sumner, 1906). Whether they are minimal groups created in laboratory settings (Tajfel, 1970), groups of boys at summer camp (Sherif et al., 1961), groups within organizations (Mouton and Blake, 1986), or even nation-states (Kahn and Zald, 1990), reciprocal antipathy between groups seems to develop with surprising frequency and alacrity. In the IC, for example, this might create problems with respect to information sharing and create various “security regulations” that make it difficult for analysts to access information not collected or disseminated to their agency, or rules that limit access to certain databases (see Fingar, this volume, Chapter 1). In-group bias impairs actors from different groups from cooperating with each other, even to achieve a mutually desired end state. Often simply associating oneself with an in-group leads to biases favoring one’s group over others (Cadinu and Rothbart, 1996; Smith and Henry, 1996; Turner, 1987). Homophily, or the tendency to be attracted to those who are similar to oneself (Blau, 1977; Berscheid and Reis, 1998), suggests that the simple categorization of others into a different group can produce bias and decrease cooperation.
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Intelligence Analysis: Behavioral and Social Scientific Foundations Therefore, in-group favoritism does not necessarily stem from faulty incentive structures. Actors from two different groups can be given incentives to solve a particular problem or to share mutually needed information, yet still suffer coordination difficulties. Rather, in-group favoritism is rooted in the sociocognitive categorization mechanism, which primes a sense of difference that eschews cognitive and motivational roadblocks to cooperation. Recall that self-categorization is a process where someone cognitively assimilates his or her self-concept to the in-group prototype. A critical feature of group prototypes is that of meta-contrast, meaning prototypes maximize similarities within each group and differences across social groups (Hogg and Terry, 2000). For example, Ledgerwood and Chaiken (2007) find that people tend to radicalize their attitudes to assimilate to those of the in-group and contrast from those of the out-group. This might play out in the IC, for example, in predispositions to dismiss alternative judgments and hypotheses that originate outside of one’s agency (the “not invented here” problem). Out-Group Homogeneity A second outgrowth of ethnocentrism is the “out-group homogeneity effect,” or the tendency to see members of one’s own group as differentiated, but to perceive out-group members as similar and unvaried (Quattrone and Jones, 1980). Seeing in-group members as more varied cannot be attributed to knowledge and exposure, as this effect is found between groups, such as “men” and “women,” who interact frequently (Mullen and Hu, 1989). The problem that arises from out-group homogeneity is stereotyping. A stereotype is a mental model that an actor has of another person based on the target’s social category membership (Lippman, 1922; Fiske and Taylor, 1991), so that the actor ascribes personality traits to the whole social category and subsequently confers these personality traits onto any member of that social group (Spencer-Rogers et al., 2007). Holding stereotypes about another social group is useful to the extent that members of the group behave in stereotype-consistent ways. Unfortunately, research shows that actors tend to discount stereotype-inconsistent behavior from targets. For example, actors tend to follow stereotypic information about an interdependent work partner, even when this information is fictitious and assigned on a random basis (Tinsley et al., 2002; O’Connor and Tinsley, 2009). Although stereotypes are technically a cognitive phenomenon, they elicit an emotional concomitant that can be negative.5 The IC, like other 5 Although most stereotypes are thought to elicit negative emotions toward others, not all stereotypes do so. Fiske and colleagues (1999, 2002) detail four general types of stereotypes
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Intelligence Analysis: Behavioral and Social Scientific Foundations organizations, has many stereotypes that affect the way analysts in one agency think of and deal with their counterparts in other agencies. Common stereotypes include the perception that INR analysts are predisposed to believe what foreign officials claim to be the case and attach greater weight to diplomatic reporting than other forms of intelligence; that CIA analysts give greater credence to clandestinely acquired human intelligence; and that DIA analysts are prone to exaggerate military threats and to favor worst case possibilities. Whether these stereotypes are true or not (or are based on truth but exaggerated, or were true but no longer are so) is irrelevant. Any stereotypes that analysts hold of each other will influence their expectations of each other and their decisions about whether or not to reach out and ask one another for help. Stereotypes can cause collaboration problems because the actor is conferring group-level information on an individual, who may or may not “fit the profile.” Thus, analysts can misunderstand each other’s needs and abilities. Moreover, because we tend to discount situational explanations for others’ behavior (Ross, 1977; Jones and Harris, 1967), and these attribution errors are more pernicious for out-group members (Allison and Messick, 1985), an actor could easily misperceive a target’s intent and ascribe a more sinister motive, making any interaction more emotionally trying than it needs to be. Do these intergroup problems pervade every organizational interaction? Of course not, but social categorization and intergroup dynamics represent the backdrop against which everyday organizational activities occur. Like background music that sometimes fades out of awareness and at other times becomes an annoying distraction, intergroup issues can remain quiet or create a disconcerting amount of static. The next sections describe research on when intergroup dynamics are relatively dormant versus when they come forward as a powerful force shaping the interaction. WHEN MIGHT INTERGROUP DYNAMICS BE MORE ACUTE? In certain circumstances intergroup biases have an especially acute influence on members’ cognitions and behaviors. Generally, the degree of along two dimensions, the warmth of the target and the presumed competence of the target. Thus, an actor’s social categorization of a target can elicit feelings of: (1) low warmth/low competence, (2) low warmth/high competence, (3) high warmth/low competence, or (4) high warmth/high competence. Presumably, actors who think the target belongs to this last social group should have a relatively easier time working with this target than with a target categorized in one of the other three groups. Indeed, in a collaboration task, O’Connor and Tinsley (2009) found that people’s positive stereotypes of each other lead to high collaboration and high output, even when the information was false and even when only one party made such a positive inference about the other. Unfortunately, however, Fiske et al. (1999) find that people tend to reserve this high-warmth/high-competence stereotype for fellow in-group members.
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Intelligence Analysis: Behavioral and Social Scientific Foundations to imagine a day in the life of an out-group target decreased stereotype activation and in-group favoritism. Similarly, decreasing group distinctiveness by having out-group members disclose personal information or by removing cues of social dissimilarity likewise decreases intergroup bias (Bettencourt et al., 1992; Brewer and Miller, 1984; Gollwitzer et al., 1999). All these interventions are likely to reduce in-group favoritism because they function subconsciously on the actor. The actor is not aware of the social categorization processes or, more specifically, that the target’s categorical distinction from the self has evaporated. Social Networks Once actors are individuated, integration still requires a way for them to connect. Network scholars insist that every organization has a complex web of informal ties among individual employees (Krackhardt, 1990; Granovetter, 1985). Many kinds of social networks exist, such as advice networks, trust networks, and communication networks. These networks can literally be mapped by asking employees whom they go to for advice, whom they trust, whom they talk to every day, whose job they could assume with only 1 day of training, or whom they would recruit to support a proposal that might be unpopular. Generally a tie is said to exist between two people only if both individuals claim it does (Wellman and Berkowitz, 1988). Network scholars also advance the idea that these social ties grow organically during the natural course of task accomplishment and that they can either be functional or dysfunctional to the organization (Krackhardt, 1990). Because managerial perceptions of social networks are usually inaccurate, upper managers are exhorted to uncover these networks through objective mapping. One configuration that is particularly problematic is an “imploded relationship,” in which a group of actors tightly linked within a group have no (or few) links outside the group. Also problematic is the “bow tie,” in which two imploded groups are linked to each other by only one (or a few) connections (Krackhardt, 1990). Most prescriptive research in this area focuses on how individuals can build more personally useful social networks. Granovetter (1985) discusses the “strength of weak ties,” or the notion that the most useful people in your network may be those who are one tie removed from you, as they are likely to have access to novel information and opportunities; by contrast, people to whom you are immediately linked tend to have the same information you have. Thus, Uzzi and Dunlap (2005) caution us to beware of networking only with people we like or with those who are geographically convenient because they are not likely to offer new information or perspectives. Because most scholars look at networks within firms, where they appear
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Intelligence Analysis: Behavioral and Social Scientific Foundations to flourish without encouragement, only scant research is available on how to promote the organic growth of networks. Gulati’s work (1995; Gulati and Nickerson, 2008) that looks at network ties across firms discusses the importance of trust in alliance formation. Generally, alliances grow from the motivation and instigation of individual actors. Actors must feel they need something the target has (e.g., another type of intelligence) and must trust that if they ask for it, the target will be responsive. When someone allows himself or herself to be vulnerable and the other person does not violate that vulnerability, trust grows. In the context of the IC, collaboration across agencies both requires trust and can engender trust. Collaboration requires trust because the initiating analyst will identify and admit to a need (making the initiating analyst vulnerable) and responding analysts will share sensitive information to meet these needs (making responding analysts vulnerable). Trust helps bridge this chasm of risk. When initial acts of faith result in fulfilled promises, reciprocal disclosures, and non-opportunistic behavior, then trust builds. Unfortunately, the process of building trust can take some time. Building trust among analysts of different agencies can be difficult to engineer from above. “Bonding” experiences, such as Outward Bound trips that are not task relevant, risk becoming trite. However, creating a work-related task in which analysts from different agencies must cooperate with each other should build trust, assuming the agents perform well together. Allowing these agents space to cooperate in a task-focused manner, and giving them a little extra time to get to know each other, might foster mutual trust. One intriguing idea is that analysts may be able to develop “swift trust” (Myerson et al., 1996), which is the collective perception that vulnerability that may exist in temporary systems will not be exploited. Swift trust seems to occur for people whose personalities predispose them to trusting others. Highly trusting people look for confirmation in other’s behavior, in particular whether those others have been helpful and enthusiastic (Popa, 2007). Therefore, some (e.g., high trusting) analysts who might be able to achieve a high rate of production collaborate rather quickly, despite the temporary nature of this interaction. Online tools such as A-Space, Intellipedia, and the Analysts Resource Catalogue offer resources for analysts wishing to network with each other in real-time to solve discrete tasks and find answers to less well-defined research questions. In these new communication spaces, people may feel less vulnerable, and this “swift trust” might develop more readily. The burgeoning research on social networking sites, such as Facebook and LinkedIn, might be useful to investigate because many of these social networking sites are now being used for transactional purposes (e.g., online marketing and product promotion). Traditional communication literature makes a great distinction between the types of messages that can be effectively
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Intelligence Analysis: Behavioral and Social Scientific Foundations communicated online versus face to face. For example, Media Richness Theory (Daft and Lengel, 1984; Daft et al., 1987) contends that the more ambiguous and uncertain a task is or the more equivocal the communication needs, the richer8 the communication medium should be. However, whether this is still true for the generation bred on virtual communications and connections is unclear. Casciaro and Lobo (2005) instruct upper managers to leverage the power of likable people to initiate connections among various unconnected individuals. They find that most people would rather interact with a “lovable fool” than a “competent jerk” in an interdependent work task. Thus, they argue that likable people (those who are empathetic, generous, and socially skilled) can reach out to others and even serve as brokers among different groups. Although the idea that people will respond to likable others makes sense (even if they are relative strangers asking for resources), whether any of these connections would flourish once the “likables” are no longer involved is uncertain. The emphasis on likability calls to mind Cialdini’s extensive work on persuasion—how to get people to do something for you that they otherwise might not do. His six “weapons of influence” (Cialdini, 2008) include (1) likability—we are more likely to say yes to someone we like than to someone we do not like; (2) authority—we are more likely to say yes if we’ve been instructed by an authority figure to do so (see above section on integration through managerial hierarchy); (3) commitment and consistency—we are more likely to commit to larger favors after having already done a smaller favor (the “foot-in-the-door” technique); (4) social proof—we are more likely to do something if we see others doing it (see above section on culture and conformity); (5) reciprocity—we are more likely to do something for someone who has done something for us; and (6) scarcity—we are more likely to do something if we will get something scarce in return. Future research might look at whether these principles can be applied by analysts to encourage others to collaborate with them. Moreover, do analytic networks grow organically, emanating from pockets of likability, commitment, and scarcity? 8 A communication medium richness is a function of (1) the medium’s capacity for immediate feedback; (2) the number of cues and channels available; (3) language variety; and (4) the degree to which intent is focused on the recipient. Richer media are said to create a greater “social presence,” immediacy, and warmth.
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Intelligence Analysis: Behavioral and Social Scientific Foundations CONCLUSION: WHY INTERAGENCY COLLABORATION IS VITAL Hazards flourish in areas where no one is directly responsible. In the IC’s current environment of complex interconnected systems, risks are difficult to monitor, and uncertainty is inescapable. Unfortunately, because of this complex interconnectivity, even minor hazards can escalate to have large consequences (Perrow, 1984). This uncertainty is not all bad. New situations can bring new opportunities for process of innovation. At the same time, meeting new challenges can eschew unintended negative results that can be disastrous. Thus, integration processes should be undertaken mindfully. Intelligence needs to be as interconnected as the system of potential hazards might be. This interconnectivity means integrating intelligence analysis across agencies to help IC members “work the spaces between the cases” (Hayden, 2009). REFERENCES Alexander, M. G., M. B. Brewer, and R. K. Herman. 1999. Images and affect: A functional analysis of out-group stereotypes. Journal of Personality and Social Psychology 77:78–93. Allison, S. T., and D. M. Messick. 1985. The group attribution error. Journal of Experimental Social Psychology 21:563–579. Allport, G. W. 1954. The nature of prejudice. Reading, MA: Addison Wesley. Asch, S. E. 1955. Opinions and social pressure. Scientific American 193:31–35. Bateson, G. 1991. Sacred unity: Further steps to an ecology of mind. Chicago, IL: University of Chicago Press. Benedict, R. F. 1934. Patterns of culture. Boston, MA: Houghton Mifflin Co. Berry, J. W. 1980. Introduction to methodology. In H. C. Triandis and J. W. Berry, eds., Handbook of cross-cultural psychology, vol. 2. Boston, MA: Allyn and Bacon. Berscheid, E., and H. T. Reis. 1998. Attraction and close relationships. In D. T. Gilbert, S. T. Fiske, and G. Lindzey, eds., The handbook of social psychology, 4th ed. (pp. 193–281). New York: McGraw-Hill. Bettencourt, B. A., M. B. Brewer, M. Croak, and N. Miller. 1992. Cooperation and the reduction of intergroup bias: The role of reward structure and social orientation. Journal of Experimental Social Psychology 28(4):301–319. Blau, P. M. 1977. Inequality and heterogeneity: A primitive theory of social structure. New York: Free Press. Blumer, H. 1962. Society as symbolic interaction. In A. M. Rose, ed., Human behavior and social process: An interactionist approach. New York: Houghton-Mifflin. Boas, F. 1940. Race, language, and culture. New York: MacMillan. Bodenhausen, G. V., C. N. Macrae, and J. W. Sherman 1999. On the dialectics of discrimination: Dual processes in social stereotyping. In S. C. Trope, ed., Dual process theories in social psychology (pp. 271–290). New York: Guilford. Brett, J. M., C. H. Tinsley, D. L. Shapiro, and T. Okumura. 2007. Intervening in employee disputes: How and when will managers from Japan, China, and the U.S. act differently? Management and Organization Review 3(2):183–204.
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