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.

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"...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

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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 self-

organizing 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

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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

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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 higher-

level 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

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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

amodel 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

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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 self-

consciousness. 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

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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.

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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

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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

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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/).

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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 self-

organizing 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

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

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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.

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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)

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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.

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“…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. In-

group 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

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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.

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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

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match the velocity of moves of the group. Central to this shift, especially in the case of cross-

functional 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.

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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 non-

reducible 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.

Flock Theory 25

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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)