Flock Theory - A New Model of Emergent Self-Organization in Human Interaction

Flock Theory 1 Running Head: Flock Theory

Flock Theory: A New Model of Emergent Self-Organization in Human Interaction

Flock Theory 2

Flock Theory: A New Model of Emergent Self-Organization in Human Interaction Tracking # - ICA-7-11675

Abstract

This paper introduces a new theory of emergent self-organization in human interaction.

Flock theory draws from a theoretical basis of emergence and self-organizing systems (Contractor, 1994; Hodgson, 2000; Monge & Contractor, 2001; Monge & Eisenberg, 1987).

Likewise, two other important theoretical works are offered, Eric Eisenberg’s work on the transcendent organization of jamming (Eisenberg, 1990), and R. Keith Sawyers’ work on the Emergence of Creativity (Sawyer, 1999). Catalyzed by a computer graphic simulation of a flock of birds by Craig Reynolds (Reynolds, 1987), and conceived to model jazz improvisation, Flock Theory is presented axiomatically. Focusing on the optimization of group members’ distance, the maintenance of leadership, and matching of direction of other individuals, this theory poses a model of human interaction that captures the potentially egalitarian effects of a cooperative evolution. Methods and applications of Flock Theory extend across disciplines, from task groups to online interaction.

Flock Theory 3 "...and the thousands of fishes moved as a huge beast, piercing the water. They appeared united, inexorably bound to a common fate. How comes this unity?"

--Anonymous, 17th century

Introduction At the very heart of human communication is cooperation, more specifically emergent cooperation. Whether the situation is a regular conversation, an Internet chat room, or an improvisational performance, communication is an emergent and evolutionary process. The nature of emergent systems translates to communicative systems in that a system can only emerge if the components of the system interact in a communicative manner. These components can be agents in computer simulations or humans in an improvisational music group, but in either case, interaction is fundamental as the basis for emergent interaction.

Emergence theorists have outlined the some of the substantive elements of these evolutionary systems because the nature of the states of the entities of the systems in contexts are fairly well defined. Yet, there is a lack of understanding of the properties of how these entities operate within the emergent context, or what role communication plays. To fill this gap, Flock Theory is introduced. Flock Theory models the cooperative evolution of human interaction via communication. A combination of self-organizing systems theory, network theory, and emergence theory, Flock Theory bridges across interdisciplinary boundaries. Conceived to model jazz improvisation and catalyzed by a computer graphics simulation of bird flocks, this theory pulls from several unique sources. The literature covered in this paper attempts to explicate and also serve as a call for research in capturing the essence of Flock Theory.

This paper provides a definition of emergence and its relation to scientific explanation, along with commentary on the shortcomings of emergence theory to date. Next, organizational

Flock Theory 4 communication research by Eric Eisenberg on jamming and organizing is covered, followed by R. Keith Sawyers work on the emergence of creativity, and an explanation of Autopoiesis. Craig Reynolds’ work on the successful simulation of flocks is then described as an initial model of flock behavior leading to the presentation of Flock Theory using formal axioms and tenets.

Finally, methods for testing and contributions to social science are offered.

Literature Emergence Role of Emergence in Scientific Explanation “Emergence … refers to the arising of novel and coherent structures, patterns, and properties during the process of self-organization in complex systems,” (Goldstein, 1999, p. 49).

Emergence has a rich and multidisciplinary history of investigation into the characteristics associated with emergent phenomena, often falling under the titles of complexity theory or selforganizing systems (see Contractor, 1994; Contractor & Grant, 1996; Contractor & Seibold, 1993; Darley, 1994; Gilbert, 1995; Gleick, 1987; Hodgson, 2000; Maturana & Varela, 1980; Monge & Contractor, 2001; Monge & Eisenberg, 1987; Prigogine & Stengers, 1984; and Wheeler, 1928).

Emergence functions as a descriptive concept directing attention to the patterns, structures, and properties that systems embody on the macro level. Emergence provides a basis on which to develop an explanation, not its terminus.

A common criticism of emergence has been that it does no more than provide provisional status. It is argued here that the provisional nature of emergence can actually be a supportive element because science must be able to deal with phenomena in which there is less than perfect knowledge. In complexity theory a limitation that is unavoidable is predictability concerning the

Flock Theory 5 non-analytically solvable nonlinearity of such systems, where emergent phenomena will be different at each point in their trajectory. Roger Sperry (1988) pointed out that the mind emerges out of brain functions, yet the mind can have contributory power in affecting the brain – if emergents have causal power than they cannot be simply provisional.

The basis of the provisionality issue is not a scientific one but a metaphysical assumption that there is one ontological level and the goal of scientific inquiry is to reduce new levels to this basic one, called ontological-level monism. With the increase of work in fields such as nonlinear dynamics and complexity theory (see Gleick, 1998; Nicolis, 1989; and Prigogine & Stengers 1984), natural systems and processes that can not be explained by an overly reductionistic perspective due to the mathematical complexity of such phenomena (Goldstein, 1999).

Likewise, chaos theory suggests that apparent uniqueness may arise from deterministic nonlinear systems. The estimation of initial conditions will not suffice for accuracy, undermining the prospect for simplified prediction and reductionist explanation.

Developments in the study of emergence challenge how both the social and natural sciences have traditionally worked. Since reductionism traditionally assumes the notion that the elemental parts should explain the whole, complex phenomena must be elaborated in terms of one level or type of unit (Hodgsen, 2000). Reductionism remains conspicuous in social science because it characteristically appears as methodological individualism (Elster, 1982). Hodgson (2000) points out that reductionism should be distinguished from reduction, which involves the fractional breakdown of elements at one level into parts of some different level. As Popper (1974) points out, there is frequently an “unresolved residue� (p. 260) left by attempts at reduction, even if successful. Emergent properties are, by definition, not explainable in

Flock Theory 6 conditions of basic elements and to explain systems of complexity it is essential to rely on more macro levels.

Emergence is crucial for social sciences in that it allows for a means to explain higherlevel relations, avoiding the problem of analytic reduction to lower-level units. Yet, while emergent phenomena provide the ability to analyze at a more macro level, “we must never lose sight of the dependence of these higher-level properties on lower-level units. The marks of an emergent property include its novelty, its association with a new set of relations, the stability and boundedness of these relations, and the emergence of new laws or principles applicable to this entity� (Hodgsen, 2000, p. 75). As Goldstein (1999) points out, where traditional physics has had the ability to study complete order or utter randomness, emergence offers the ability to understand the middle ground. As a result, the absence of adequate frameworks for emergent order acts as a hurdle to emergents being accepted as ontologically viable.

Shortcomings of Emergence Theories to Date Central to the discussion of emergence is the inability to use reductionism as a focus of description. However, Hodgson (2000) points out that reduction must be distinguished from reductionism, it is in this sense that the logical-causal-temporal pattern can be revealed.

Likewise, what is being challenged is the idea of complete analytic reduction, not reduction as a concept. As a result the inherent macro view of emergence has led to a general lack of understanding of the micro phenomena that the agents in emergent systems display.

As a result of this macro focus, the majority of the emergence research has been dedicated to the substantive domain by focusing is on the phenomena, states, actions, and entities of systems. The actors are mainly viewed as behaving in context yet the properties that let these actors emerge is not well understood. Most of the attempts at developing methods to study

Flock Theory 7 emergence result in looking at patterns of interaction or at the process and the relations therein.

While there may be an understanding of emergent systems as a whole, a more complete understanding of the components is needed. If these components are human, it is crucial to understand the paradigmatic assumptions of the theories. Likewise, it is important to approach these emergent interactions from an embedded systems perspective of social units as higher levels of organization in which elements and relations are embedded. As a result, further insight is needed into the philosophical assumptions within which the concepts and their environments are embedded. Even though there is substantial investigation into the substantive domain there is still a generative approach being taken. Researchers have identified and analyzed patterns of occurrences of states (Gilbert, 1995; Hodgsen, 2000; Eisenberg, 1990, Sawyer, 1999), but there is still little understanding of the causal aspect of the phenomena.

This paper attempts to explore the causal aspects of change by providing a framework for a model of emergence based on naturally occurring phenomena. Two main areas of work that have attempted to visit cooperative evolution are Eric Eisenberg’s writings on Jamming and R. Keith Sawyer’s research on the Evolution of Creativity Jamming: Transcendence Through Organizing Eisenberg (1990) describes characteristics of “jamming” experiences, or fluid behavioral coordination that occurs without detailed knowledge of personality. These experiences are seen as sparking a balance between autonomy and interdependence (and can even be transcendent).

Four pre-conditions for jamming are presented; skill, structure, setting, and surrender.

According to Eisenberg (1990, p.139), “Jamming celebrates the closeness that can arise through coordinated action.

Jamming is nondisclosive but fulfilling. Jamming experiences are worthy of study because they are an often ecstatic way of balancing autonomy and interdependence in

Flock Theory 8 organizing. As such, they offer a different route, other that reciprocal disclosure, to community.�

Jamming Eisenberg (1990) notes that traditional perspectives on communication and organizing fail to account for several aspects of organized action, mainly experiences associated with minimal disclosure. “Jamming encourages both cooperation and individuation,� (p. 146) Similar to mutual equivalence structures (Weick, 1979), jamming situations may be highly rule governed, structured, activities where little to no personal information is exchanged.

Yet, goals are accomplished and a strong bond is formed amongst jammers. Such jamming situations become appealing because they enable the actors to feel a part of a larger community, without the commitment of revealing much personal information. As a result of the lack of personal disclosure required in jamming, self-consciousness can disappear.

Jamming, however, may not be a condition easily attained or maintained. Eisenberg argues that jamming requires a clear set of rules and structures, such as a persons need to surrender to the experience, engaging respectfully in the interaction, and dominant leader qualities such as using the exchange to unload on or control others dissolves the possibility for such an interaction.

Structurally, jamming illustrates a case where structure can be seen as liberating instead of constraining. There are low expectations for future interaction as a result of the lack of emphasis on individual personality traits, allowing the actors to cooperate without selfconsciousness. Likewise, this highly structured setting places relatively few requirements on dealing with and accounting for individual personalities.

Improvisation thus becomes an important aspect of jamming. This notion of structure includes formal and informal rules. For example, in jazz these can be seen as rules of musical

Flock Theory 9 keys or progressions (formal) and how long you can play (informal). As local conventions vary, there is a set of core rules that a person must know and follow in order for the interaction to take on a jamming situation. However, too much attention to the rules increases the possibility of ego by moving the individual toward self-consciousness, illustrating that jamming is only possible when rule and role structures are assumed and taken for granted.

Another important element of jamming is the surrender of control, because one cannot jam at will and without interdependence with the other actors, and much can be gained by preparation and development of the right attitudes as well as seeking compatible partners.

Organizational settings must foster a structure for surrender, where risk is rewarded and work groups are kept sufficiently autonomous to ensure an influx of novel ideas.

Emergence of Creativity Working on the emergence of creativity, R. Keith Sawyer has established a body of work visiting notions such as collaborative emergence and emergent evolution as support. Properties of what Sawyer calls the emergence of creativity via emergent evolution capture the essence of cooperative evolution. Discussion of these concepts stems from a seminal paper by Sawyer (1999) entitled The Emergence of Creativity.

Central to his constructs is wholeness, or that a result is not necessarily reducible to the sum of its parts. Similar perspectives as are discussed at length by Lewes (1877), “Every resultant is either a sum or a difference of the co-operant forces … and is clearly traceable in its components … the emergent … cannot be reduced either to their sum or their differences,” (Lewes, 1877, pp. 368-369).

Borrowing from Lewes’ concept of emergent evolution, C. Lloyd Morgan began a series of lectures in 1922 with a discussion of evolutionary developments and their emergence over time.

Flock Theory 10 Morgan discussed how higher levels of complex organization emerge from lower levels (Morgan, 1923).

Sawyer uses his analysis of improvisational theater as analogy to these concepts. Much as actors create a dialogue with no preconceived notions of where they will go, an understanding of this knowledge cannot stem from each individual actor. Understanding can only arise out of the collaborative creation and the analysis of the group as a whole.

Wholeness in group behavior is emergent in instances where a structured plan directing the group is not present or where there is no defined leader directing the group. Thus collaborative emergence occurs in such routine situations as conversations and brainstorming sessions, where improvisation results from the lack of a director or script.

Improvisational theatre, much like jazz improvisation, is egalitarian by default. There is no group leader and any attempts to control the situation corrode the structure and are often shunned by other members. The communication in these situations is collaboratively emergent because with each actor’s input a possible path is chosen, closing off a multitude of other paths.

It is this element of the emergence of creativity is related to self-organizing systems in that the moves of each actor cause a need for internal organization based on a series of rules intended to maintain the egalitarian (and thus cooperatively emergent) setting, and these rules provide the impetus for this paper. However, it is important to establish the nature of the self-organization that is most applicable to emergent phenomena when a system has a set organization that is closed to environmental forces, yet remains structurally open to these forces, as explained below.

Autopoiesis

Flock Theory 11 The process that individuals undergo to attempt to increase the level of understanding between each other is a function of autopoiesis, or the recursive self-reproduction of components in a system. One of the main functions of an autopoietic system is to maintain it’s autonomy, and thus can be further defined as “a network of processes that produce all the components necessary to embody the very process that produces it.” (Krippendorff, 1991, p. 138). In this sense, autopoietic systems recursively produce all the components necessary to have a historically reproductive network, and likewise self-reproducing. Yet, Maturana and Varela (1987) argue that within this reproduction it is important for organization, or the system (and in this case the “flock”), to maintain its identity while it’s structure can change to adapt to the environment. Thus, autopoietic systems have the ability to maintain an organization in relation to a structure while remaining operationally closed. The system is structurally coupled with the environment and organizationally closed to it at the same time. This can be applied to emergent systems where a set of parameters of interaction can remain constant regardless of structural changes, both internally and environmentally These concepts focus on the axis of change being the relationship, not identity, similar to Eisenberg’s (1990) balance of autonomy and interdependence. Likewise, the structural coupling of the system and the environment, or other systems, does not necessarily direct the internal rules of the system. Instead, the environment only causes structural changes within the system, revealing recurrent interdependencies between the environment and system (Maturana & Varela, 1987). Thus, a system lacks the ability to undergo structural change without structural coupling, explaining the foundation of the emergence of the system.

The convergence of communication via emergent systems is then a coupling of the individual pattern system with other pattern systems, be it another individual or a flock, in which

Flock Theory 12 the individual organizes the internal structure to adapt to the environmental forces. Yet it is important to maintain the internal organization, so this coupling and evolution operate on a pattern based recognition and accommodating replication. It is in this sense that a set of rules of interaction can maintain the cooperative evolution of a group regardless of the shifting of group members or the setting the group is in.

Boids In 1987 computer scientist Craig Reynolds undertook the task of creating a computer rendering of a bird flock. He comments on flocks, “A flock exhibits many contrasts. It is made up of discrete birds yet overall motion seems fluid; it is simple in concept yet is so visually complex, it seems randomly arrayed and yet is magnificently synchronized. Perhaps most puzzling is the strong impression of intentional, centralized control.” (Reynolds, 1987, p.2).

As Reynolds was tackling with the representation of such group movement, he derived three simple rules that can incorporate the vast complexity of a flock.

Rule 1. Collision Avoidance: avoid collisions with nearby flockmates Rule 2. Velocity Matching: attempt to match velocity with nearby flockmates.

Rule 3. Flock Centering: attempt to stay close to nearby flockmates.

Using these rules Reynolds is able to successfully represent flocks as “boids” in computer simulation. These boids can avoid environmental objects as well as split of from and rejoin the flock (see Figure 1, or go to http://www.red3d.com/cwr/boids/).

Flock Theory 13

Figure 1. The flock of boids steers around the obstacles and rejoins with the larger flock, maintaining the group regardless of environmental input.

Reynolds’ ability to capture coordinated evolution in a flock setting is extraordinary, yet to apply this phenomenon to human interaction is quite a different task. Humans interact using symbol sets as the means of understanding, thus any coordination therein needs to use assume that the agents will use the symbols to maintain organization. However, one of the main aspects of a flock is that the flock as a whole is moving somewhere but the direction is unknown to the flock before each moment in time.

The transition from simulated physical flocking of birds to human interaction includes a theoretical model based on efforts of other researchers to investigate similar phenomena and a method to test such a model.

Flock Theory Combining the central concepts of Emergence (Goldstein, 1999; Hodgson, 2000; Monge & Contractor, 2001; Monge & Eisenberg, 1987), Jamming (Eisenberg, 1990) and the Emergence of Creativity (Sawyer, 1999), and autopoiesis (Maturana &Varela, 1980) as explanatory processes, and groupthink (Janis, 1971) as the null situation, Flock Theory models the selforganizing principles of cooperative evolution in human interaction. The axiomatic structure is based on the rules that Reynolds (1987) used to simulate a bird flock is extended to include concepts based on social science research, such as leadership concerns, and further specify

Flock Theory 14 original tenets of “Boids” in human contexts. What follows are the formal axioms and corresponding tenets of Flock Theory, presented with supporting social science research.

Axiom 1: Distance optimization Tenet A: Separation; close but not too close (Extreme Cohesion) Tenet B: Cohesion; far but not too far (Extreme Dissenters) Axiom 2: Motion Replication Tenet A: Direction Matching; match direction of group members (Goals) Tenet B: Velocity Matching; match velocity of group members (Tempo) Axiom 3: Leadership maintenance (Goose Rules) Tenet A: Group leaders must shift in an efficient and timely manner (Passing the Gavel) Tenet B: Leaders must guide the group towards the goal or destination (Purpose) Explanation of Axioms Axiom 1: Distance optimization Axiom 1 captures the concept explained by Eisenberg (1990) as the balance of autonomy and interdependence, the “close but not too close, far but not too far” element. This is because groups that foster excessive autonomy dissolve and groups that foster too much independence stifle creativity. This also allows for the importance of coordinated beliefs to diminish as the focus is on the coordination of action. Organization is created by the shared repertoire of communicative behaviors. The balance of the two tenets being presented is a motivation to reveal that they are separate factors, much like Herzberg's Motivation-Hygiene Theory (Herzberg, 1968) where job satisfaction and dissatisfaction were found not to be opposites, but distinct factors.

Flock Theory 15 This axiom is also related to cohesion networks, where distance is modeled as cohesion.

Too much or too little cohesion can thus be seen as a productivity decay function. The actors need to maintain a level of cohesion that allows for individual input without sacrificing group acceptance.

Distance in this case is also related to communication convergence. Convergence implies that the individuals are moving toward a point, which could be toward each other or toward a common interest (Kincaid, 1988). As actors attempt to converge, they must maintain an optimum distance from each other as to allow for the inclusion of all actors to converge, thus resulting in mutual convergence of the group. Likewise, as the interaction progresses, the amount of convergence will fluctuate and the structural needs of the flock will require the individuals to monitor cognitive as well as cohesive distance.

Tenet A: Separation; close but not too close (Extreme Cohesion).

Tenet A states the first half of Axiom 1, where the actors avoid situations where the others within the group are too convergent, or too homogeneous. If this tenet is not maintained then group cohesion will increase resulting in groupthink from self-censorship and unanimity.

Research has found that high levels of cohesion can lead to Groupthink and decay the quality of the group interaction. For example, Turner & Pratkanis (1992) found that in Groupthink occurred more frequently in situations of extremely high cohesion.

Another interpretation of this tenet is that of accountability. If cooperation is to happen within the group each member must be accountable for their own actions without relying on cohesion to bail them out. Accountability can be related to two antecedent conditions of Groupthink. First, accountability inhibits the possible insulation of the group by forcing the members to consider other party’s point of view. Second, the lack of impartial (promotional)

Flock Theory 16 leadership and accountability makes it crucial for all individuals in the group to be able to justify the decision reached by the group, resulting in the decrease in the concentration of power in one domineering leader. For example, Groupthink typically occurs in decision making about nonroutine, crucial issues, that may affect large numbers of people (Kroon, van Kreveld, & Jacob, 1991). Kroon et al. (1991) also postulate that accountability is expected to reduce the likelihood that group members will give in to conformity pressures. Accountability is also expected to induce evaluation apprehension, catalyzing normative behaviors and causing one to have a tendency to “cover one’s tracks� and underestimate the performance of ones group.

Kroon et al (1991) found that accountability led to more complexity in reaching consensus, better decisions, and less risky decisions.

Tenet B: Cohesion; far but not too far. (Extreme Dissenters) Tenet B completes Axiom 1 by maintaining the balance of Tenet A. This tenet operates under similar theoretical justification as Tenet A but balances potential situations where efforts to maintain individuality is suppressed. The actors must attempt to converge with others to maintain a cooperative group, even if this movement is simply for greater uniformity in situations of system breakdown.

Another important implication that the Turner & Pratkanis (1992) study revealed is the slight reformation of groupthink theory to include tactics of social identity maintenance, where members of the group attempt to maintain a shared, positive view of the functioning of the group. A precondition to cohesion is the categorization of the members as a group, thus they tend to develop a positive image of the group and desire to protect that image. The application of the social identity maintenance (SIM) perspective draws interesting parallels to the groupthink model.

Flock Theory 17 “…groupthink symptoms of stereotyping of out-groups bears a distinct resemblance to the out-group discrimination that can accompany the induction of social identities.

Pressures toward uniformity and self-censorship induced with groupthink can be compared with the process of referent informational influence (whereby group members form and subscribe to norms of their shared categorization) that may accompany social identities.” (Turner & Pratkanis, 1992, p.70)

The final aspect of Tenet B states that if the group is faced with the presence of an actor with a level of extreme dissention, as to lead the group in a drastically different direction, the other actors must converge to support the potentially beneficial change, or eliminate the divergent actor. This operates on the theoretical basis of cybernetic systems theory (Wiener, 1948), where a goal parameter is to be maintained and any deviations from this parameter require correction. Moves by group members may seen to be drastically divergent (such as the case of a scientific revolution, see Kuhn, 1962) but it is these very moves that should be initially supported for a multitude of reasons. First, these inputs are frequently the main means of avoiding groupthink, in that they prevent two of the main causes of Groupthink, pressures and the resulting self-censorship. Second, the Tenet A implies that the group should (at least initially) support direction changes of others as to maintain the collaborative nature of the interaction. Ingroup and out-group effects are another element and are supported by the findings of Turner & Pratkanis (1992), as discussed above. If dissention is found to be beyond the goal parameters of the group, the group can then take corrective action to handle the deviation. This may be in the form of repackaging the dissenting concept in a way that it won’t breakdown the group, or eliminating the group member that is the source of breakdown. Regardless, the structure of the outlined interaction will ensure that it is a group decision and not an individual effort.

Axiom 2: Motion Replication

Flock Theory 18 Axiom 2 offers the means by which the distance optimization is obtained and maximized in Axiom 1. Whereas in Axiom 1 the group members must maintain a balance of distance, this axiom posits that the maintenance of this distance is done through matching the “motion” of the other individuals. If distance is to be maintained in the evolutionary processes, than the direction of change (either topically or task oriented) and the rate of change needs to be a cooperative function amongst the group. This relates to Sawyer’s (1999) concept of processual intersubjectivity, or the establishment of a constantly changing emergent shared understanding.

Where that which is currently being established, as well as future emergence of creativity, has to proceed within the frame being created by this emergent interaction. Thus, to have a shared understanding, or processual intersubjectivity, and operating within the current frame, the group members must attempt to match both the direction and velocity of the other members. This axiom also draws from the concept of the norm of reciprocity and communication accommodation (see Gallois, Franklyn-Stokes, Giles, & Coupland, 1988; Kincaid, 1988) Tenet A: Direction Matching (Goals).

Tenet A of Axiom 2 states that the group members converge to the direction that the other group members are moving. This could be a change of topical direction in a conversation, a novel idea in a brainstorming group, or a change of key in improvisational music. Regardless, if the group is to evolve in a collaborative manner than the members’ organization about this change maintains the structural properties of the system. Even if the direction posed by a group member is a drastic move by comparison to recent moves, the group should (at least initially) support the new direction. The norm of reciprocity provides theoretical justification for this Tenet (Gallois et al., 1988; and Kincaid, 1988), where the tendency already exists amongst communicators to match the topical direction and depth of relativity of other individuals.

Flock Theory 19 Illustrating this point is the case of a scientific revolution (Kuhn, 1962), where the group is defined as an academic community and the direction is the communally defined body of knowledge. For example, when a scientist introduces a revolutionary concept there should ideally be initial support from their colleagues to facilitate the exploration of the concept. This also relates to Axiom 1, where the idea must be relatively different from the current knowledge base, but not too far or the academic community may reject the concept altogether. Likewise, the proposed structure is designed to foster a climate that catalyzes the birthing of potential revolutionary concepts.

Tenet B: Velocity Matching (Tempo).

Tenet B of Axiom 2 states that the group members must accommodate the rate that the other members are delivering messages, making successive moves, and allowing for space between these moves. In a face-to-face context this is theoretically justified through communication accommodation theory (Gallois, Franklyn-Stokes, Giles, & Coupland,1988; and Kincaid, 1988), defines further moves of the group whether convergent or divergent. As presented by Gallois et al. (1988), the marginalized other is converged toward when they are not a threat to a dominant group’s identity, but this changes when this person’s identity is perceived as a threat to the dominant group. The marginalized other is diverged from when a threat to a dominant group’s identity, changing when this person’s identity is not perceived as a threat to the dominant group. This happens in conjuncture with Tenet A of Axiom 2, direction, for if the velocity is matched but not as to converge to a similar direction, than the system breaks down.

A cross-functional team, for example, must maintain the rate at which the attention moves from function to function amongst its members. Likewise, as bursts of activity are demanded from the group, it becomes increasingly important for the individuals to attempt to

Flock Theory 20 match the velocity of moves of the group. Central to this shift, especially in the case of crossfunctional teams, is the maintenance of leadership, as offered in the next axiom.

Axiom 3: Leadership maintenance.

Axiom 3 states that if a leadership role is present, it must shift in a manner that no one actor maintains leadership for too long, and that the group is lead in a purposeful direction.

Tenet A: Group leaders must shift in an efficient and timely manner (Passing the Gavel) This can be conceptualized as the “goose rule,” where a goose flock must shift leadership in an effort to maximize energy decay. This energy decay can be related to groups in that a leader can exhaust their energy within the group, and the individual that has not led for the longest time has build up the most potential energy, and should then lead in one of the successive moves. This also guarantees the efficient use of intellectual capital, much like a brainstorming session. This effect can also be conceptualized by the “passing of the gavel,” where the leader will often voluntarily exchange the gavel. Eisenberg (1990) and Sawyer (1999) both stress the importance of the lack of leadership within a collaborative evolution. This axiom also secures that Janis’ (1971) Groupthink does not ensue, as strong leadership is one of the main causes of Groupthink. Flowers (1977) studied directive or participative leaders and found that groups with directive leaders proposed fewer solutions, covered less case information, and used fewer case facts both before and after reaching a decision. Leana (1985) used a similar design as Flowers by assigning leaders to be either participatory or directive. These groups were then given twenty minutes to select five employees to lay off from a hypothetical business. As in the Flowers (1977) study, the groups with directive leaders discussed fewer solutions than the groups with participatory leaders.

Flock Theory 21 Tenet B: Leaders must guide the group towards the goal or destination (Purpose) Central to the role of leader is to maintain that the group is moving in a direction of purpose, related to Axiom 2: Direction matching. Often the goals of group interaction can get lost over the course of the interaction, thus it is even more important that the shifting of leadership is done so that there is understanding at the point of the shift. Thus it should be noted that in an emergent group, the leadership shift does not need to be clearly defined, in that there can be more that one leader at any given moment. This is most clearly revealed during the actual shift of leadership, much as a relay racer successfully passes the baton by having both runners maintaining a firm grip until an understanding is reached that the new runner has control.

Although not a necessary condition, the multi-leadership model allows for the building of knowledge or novel ideas where any given move may indeed spark a vibrant trajectory in another potential leader. Thus the role of leader is indeed passed from one actor to another in such a manner that intersubjectivity can exist at the point of leadership shift.

The above axioms and tenets provide a structural breakdown of situations of emergence and autopoietic self-organization in human interaction. There are of course situations that do not call for this type of structure, yet it is claimed that these groups will foster maximum utilization of intellectual capital, as well as creating an egalitarian situation. The axioms and tenets are presented separately in Table 1.

---------------------------------Insert Table 1 About Here ---------------------------------Future Applications and Methods Three main streams of research are underway to test and elaborate elements of flock theory. The first is an application to online communication via Internet newsgroups and chat discussion groups. Newsgroups are currently being examined with respect to their networked

Flock Theory 22 interaction over time. These groups are being used to gain insight in accordance with the axioms presented above. Collaborative research efforts also examine the use of 3-D Graphical Chat Rooms for informal science education. This research focuses on the use of semantic network analysis tools incorporating word co-occurrences in chat conversation using Catpac (Woelfel, 1998) to provide insight into the nature of immersive chat based interaction. The focus of this path is two fold, first to test whether online environments already exemplify an increased likelihood of cooperative evolution; second, as a potential means for experimental testing of cooperative task and social groups.

The second research stream involving flock theory is in cooperation with sociology researchers in an effort to replicate flocking behavior using cellular automata and Hopfield networks to simulate multi-agent interaction using the conditions of flock theory. Proposed applications to explore these dynamic networks include task groups and simulated musical improvisation. Likewise, different forms of cellular automata are being considered such as cellular automata simulations utilizing irregular grids.

Contributions to Social Science The majority of research in the area of emergence has been limited to conceptual and substantive investigation. Given the complexity of the concepts it has been extremely difficult to contribute to the methodological treatment. The exception to this is research in artificial societies and the use of powerful heuristic computer simulations (Axelrod, 1997). Such simulations have “created artificial social worlds, in which modeled agents interact in various ways, often to create surprising, systematic outcomes,� (Hodgsen 2000, p. 71). These simulations have shown the emergence of order and higher-level properties in complex systems.

Flock Theory 23 The transition from simulations to human interaction has been limited and for the most part unsuccessful. So the problem remains, how can emergent human interaction be measured without sacrificing macro approaches? The solution may be in the analysis of online interaction and comparing the results with similar face-to-face interaction. The main difference is that in online situation the individuals have “perfect� information, in that each person has access to the exact same information as everyone else. Where in interpersonal settings there is substantial nonverbal action as well as assumptions of character.

Since there has been investigation into the substantive elements of emergence, the conceptual relations are still somewhat understood. However, there is still a gap in an analytical method of analysis. Flock theory poses a potential outlet for this hurdle, and thus may indeed expand our knowledge of human cooperative interaction, and the proposed methods offer a unique window into this interaction.

Given the similar nature of emergent systems, as they follow a similar set of rules, there remains potential for implications of Flock Theory to be largely generalizable. This is not limited to communication, for many social sciences suffer from reductionistic problems.

Likewise, a deeper understanding of the relations in emergent situations can be extended to the natural sciences as well as artificial simulations.

As discussed in the review of the emergence literature, there is a fundamental gap in social scientific theory and research as a result of the dominance of reductionistic thought. This gap comes in response to the continued attempt to replicate the validity and overall success of the natural sciences. However, the nature of social science is that the main unit of analysis is social behavior, which is inherently non-reductionist in that there is no social if the unit of analysis is

Flock Theory 24 reduced to the individual. As a result the theories and methods developed in social science research are designed to reduce the social nature of human interaction to non-social measures.

The study of communication offers the potential to gain a crucial understanding of the interaction in emergent systems. Thus, theories must be developed that capture the elegance of human communication, the elements that separate humans from most other animals, elements of emergence. It is these emergent elements that allow humans to evolve in a cooperative and nonreducible manner, a manner that allows for the continuous birthing of novelty and creativity.

Flock Theory combines the macro views of emergence theory with the cooperative nature of human interaction. At the core of this interaction is communication, as communication is the way we traverse reality and maintain a collective consciousness. Yet, it is odd that most of the theories to date treat the individuals as micro elements of a greater whole without stepping back to see the forest for the trees - for it is a beautiful forest. And much as a forest ecosystem is completely interconnected, as any slight change in any way will effect the entire ecosystem, such is human interaction because our interaction is just as tightly interconnected. Acknowledging this interaction we may be able to understand the human ecosystem and the beauty of its web.

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Flock Theory 28 Table 1: Flock Theory Axiom 1: Distance Optimization

Tenet A: Separation; close but not too close (Extreme Cohesion)

Tenet B: Cohesion; far but not too far (Extreme Dissenters)

Axiom 2: Motion Replication

Tenet A: Direction Matching; match direction of group members(Goals)

Tenet B: Velocity Matching; match velocity of group members (Tempo) Axiom 3: Leadership maintenance (Goose Rules)

Tenet A: Group leaders must shift in an efficient and timely manner (Passing the Gavel) Tenet B: Leaders must guide the group towards the goal or destination (Purpose)