Saturday, July 14, 2018

RhizoRhetoric: ANT Roots

I'm reading Bruno Latour's 2005 book Reassembling the Social: An Introduction to Actor-Network Theory, and the implications for a rhizomatic rhetoric are worth careful exploration over several posts. This is the first.

The first chapter of Latour's book presents his reasons for devising actor-network theory (ANT) and for writing the book: his discomfort with the assumption by conventional sociology of the social as an existing domain within which to embed and define groups. Latour prefers to start with the emerging group to follow the connections and interactions both within the group and with its environment to uncover how the social emerges. To my mind, Latour wants to define from the inside out rather than from the outside in. Following the actual, existing traces of the group's activities means being willing to follow tracks that might not be recognized as social from the perspective of any given social theory.

In her review of the book, Barbara Czarniawska begins with a quote from Giles Deleuze: "There is no more a method for learning than there is a method for finding treasures...(Giles Deleuze, Difference and Repetition, 1968/1997: 165)". I like this nod to Deleuze as recognition of the more open-ended approach both Deleuze and Latour bring to their studies. Learning demands a willingness to re-examine existing structures, points of view, methods, and theories and then to reinforce those that prove helpful and to change or abandon those that prove harmful. Our existing knowledge both enables us to know more and limits what more we can know. When we already know what will happen, then we are more likely to miss what actually happens. Deleuze and Latour are both looking for ways around this dilemma of knowledge. Shunryu Suzuki says it best for me in his book Zen Mind, Beginner's Mind (1973): "In the beginner’s mind there are many possibilities, but in the expert’s there are few." Suzuki, Deleuze, and Latour are, of course, speaking of issues in the complex domain rather than the simple or complicated domains, as defined in Dave Snowden's Cynefin framework. Like these thinkers, I think that most of life is complex, and I'm certain that rhetoric is, despite the myriad attempts by rhetoricians to render it simple or at least merely complicated.

In a sense, then, all of these fellows, and certainly Latour, are resisting the tendency to view life through too narrow a lens, to put our experiments into too small a box, to render simple or no more than complicated that which is rightly complex. Latour makes this clear when he compares the shift in thinking required by ANT with the shift in thinking required by modern physics. He says:
A more extreme way of relating the two schools is to borrow a somewhat tricky parallel from the history of physics and to say that the sociology of the social remains ‘pre-relativist’, while our sociology has to be fully ‘relativist’. In most ordinary cases, for instance situations that change slowly, the pre-relativist framework is perfectly fine and any fixed frame of reference can register action without too much deformation [Cynefin's simple/complicated domains]. But as soon as things accelerate, innovations proliferate, and entities are multiplied [Cynefin's complex/chaotic domains], one then has an absolutist framework generating data that becomes hopelessly messed up. This is when a relativistic solution has to be devised in order to remain able to move between frames of reference and to regain some sort of commensurability between traces coming from frames traveling at very different speeds and acceleration. Since relativity theory is a well-known example of a major shift in our mental apparatus triggered by very basic questions, it can be used as a nice parallel for the ways in which the sociology of associations reverses and generalizes the sociology of the social. (12)
I particularly like this comparison of ANT sociology with modern physics, as it seems to me that modern physics has moved us from the modern world of the Enlightenment and Newton into the postmodern world of Einstein, Bohr, Deleuze, and Carlos Casteneda. I mention Casteneda because he provides the perfect image of ANT years before Latour thought of it. Also, Deleuze and Gauttari mention Casteneda in their book A Thousand Plateaus, where they note that in The Teachings of Don Juan, the Yaqui sorcerer Don Juan Matus gives his student Carlos instructions about how to cultivate a garden of hallucinogenic herbs:
Go first to your old plant and watch carefully the watercourse made by the rain. By now the rain must have carried the seeds far away. Watch the crevices made by the runoff, and from them determine the direction of the flow. Then find the plant that is growing at the farthest point from your plant. All the devil's weed plants that are growing in between are yours. Later … you can extend the size of your territory by following the watercourse from each point along the way. (ATP, 11)
This makes Latour's point quite nicely and most graphically: start with an initial observation of a functioning group, then follow the traces (the watercourses and crevices) that are actually there (not the ones you think should be there based on your fixed, rectangular theory of what a garden should look like), scribbling like mad to capture as much as you can.

Though as often happens, the poets and prophets were there first. In a 1956 interview in The Paris Review, William Faulkner says of theory: "Let the writer take up surgery or bricklaying if he is interested in technique. There is no mechanical way to get the writing done, no shortcut. The young writer would be a fool to follow a theory. Teach yourself by your own mistakes; people learn only by error." He says of his own method for writing Nobel-quality novels: “It begins with a character, usually, and once he stands up on his feet and begins to move, all I can do is trot along behind him with a paper and pencil trying to keep up long enough to put down what he says and does.”

This may be the heart of ANT: start with an observation and trot along behind to see where it goes, what it connects to, and what energy and information it exchanges. There's your novel, your sociology, or your physics. Or your rhetoric.

Czarniawska explains Latour's intentions for his book this way:
The question for social sciences is not, therefore, ‘How social is this?’, but how things, people, and ideas become connected and assembled in larger units. Actor-network theory (ANT) is a guide to the process of answering this question. (1)
Latour devotes much of his first chapter to distinguishing his approach to sociology from established approaches. As Czarniawska says, "Students of the social need to abandon the recent idea that 'social' is a kind of essential property that can be discovered and measured, and return to the etymology of the word, which meant something connected or assembled" (1). Latour says it this way:
Even though most social scientists would prefer to call ‘social’ a homogeneous thing, it’s perfectly acceptable to designate by the same word a trail of associations between heterogeneous elements. Since in both cases the word retains the same origin—from the Latin root socius— it is possible to remain faithful to the original intuitions of the social sciences by redefining sociology not as the ‘science of the social’, but as the tracing of associations. In this meaning of the adjective, social does not designate a thing among other things, like a black sheep among other white sheep, but a type of connection between things that are not themselves social. (5, italics in original)
A social group for Latour is not defined from the outside by measuring how well the group matches a definition of social, regardless of how sophisticated or admirable the definition might be; rather, a social group is defined from the inside as the researcher crawls into the group to trace the associations at work within the group and between the group and its environment. The working out of these associations -- these dynamic exchanges of energy, information, matter, and organization among actors -- define the group. For Latour, this is the work of the ANT sociologist.

I am deeply attracted to this orientation to study, analysis, and understanding, and it helps explain what one of my writing groups tried to do in a recently published paper "Pioneering Alternative Forms of Collaboration", in which we explored how our online group formed to write several documents and presentations about the #rhizo14/15 MOOCs we all participated in. We wrote this particular paper from the inside out, or tried to, and I think we were able to capture a few points that we might have missed had we done a traditional rhetorical study of our work together. In this document, we did not start with a rhetorical definition of how academic scholars should collaborate online to write their documents; rather, we tried to trace what we actually did to see if we could figure out how and why it worked. I'm proud of this paper, though I think we could do a much better job of it now than we did then. Still, for me it was a step in a rewarding direction. And this is worth adding: it was not a destination, just a direction. We will not likely create a swarm method of scholarly writing for other groups to follow, though we may trace a few paths that others may walk, more or less. That remains to be seen.

So like Latour, I can orient myself to my studies by starting with an observation of an actor/action and then tracing as carefully as possible the connections and interactions within the actor and between the actor and its environment of myriad other actors. I will almost certainly rely on my existing models of reality to try to understand the actor/action, but I also must be willing to relax those models to allow for the connections and interactions not included in my model. Like an ant, I must be willing to follow any trail -- especially those that lead to wrong turns and dead-ends on the map of my theory -- for that is precisely when I am positioned to learn.

Thursday, April 5, 2018

RhizoRhetoric: 7 Self-Organize

The ability to adapt, or self-organize, is Cilliers' final characteristic of complex systems. He says it this way:
Complex systems are adaptive. They can (re)organize their internal structure without the intervention of an external agent.
I reveal my professional bias by saying it this way: complex systems can learn. And though we typically think of learning in human terms, learning is a characteristic of all complex systems from microbes and bacteria to galaxies. Some systems learn incredibly slowly (rocks, for instance, seem to adapt over millions of years) and some quickly, but all take in energy and information from their environments and reorganize themselves to accommodate changes in that environment.

Self-organization is key to a writing swarm, and in some ways, I can consider all of the previous characteristics of complex systems as the foundation to this: the ability to learn and self-organize. A writing swarm is a learning hive, and I think we all learned much.

First, we all learned more about the tools we were using. All of us in the swarm are computer literate and network savvy, yet each of us learned to use a new tool (for me, Slack) and to use new techniques for familiar tools. Here we can easily see the wonderful creative tension between memory, or existing knowledge which strives to keep the practices and structures that it has, and dynamic new knowledge which strives to change the swarm's practices and structures. Learning requires this interplay between the ability to change and resistance to change. Self-organization requires both the ability to change and the ability to resist change, adaptability as well as resilience.

Then, we all learned more about how academics are interacting on the Net, both in planned MOOCs and in looser, unplanned swarms. All of us in the swarm are highly educated academics with a substantial body of knowledge to bring to the swarm, and this body of knowledge forms a rich backdrop and resource within which to test, temper, and integrate new knowledge. As such, it both enables our ability to add to knowledge and brakes any impulse to change too quickly.

Finally, we all learned more about each other. Though few of us have met physically, all of us have gotten to know each other virtually. We are colleagues, and in some cases, friends. Whether friends or not, we trust each other, and in the few cases where trust has been undermined, the offending or offended persons have left the swarm.

In many ways, the self-organization of our particular swarm is mediated by the documents that we write. Unfortunately, the formal character of a finished, printed document obscures the tracks of the interactions that led to that formal arrangement. It's something like a formal family portrait that shows too little of how all these people are connected and interact. The history feature in Google Docs is able to reveal some of the traces of composition, and it is a vastly underutilized feature of Docs that merits substantial research. The data is there and should be mined.

We have much to say about how our swarm learned, but I wonder if we can say it all. I suspect that some learning takes place at the swarm scale, somewhat over our heads. I base this speculation (and it really is speculation) on the analogy of the bridges and rafts that army ants can build to overcome obstacles. In her Quantamagazine article "The Remarkable Self-Organization of Ants", Emily Singer explains how army ants build bridges of themselves to get the foraging swarm across gaps in their path, "a marquee example of a complex decentralized system that arises from the interactions of many individuals," much like our writing swarm. Singer says:
Bridges are built based on simple rules and possess surprising strength and flexibility. As soon as an ant senses a gap in the road, it starts to build a bridge, which can reach a span of tens of centimeters and involve hundreds of ants. Once the structure is formed, the ants will maintain their position as long as they feel traffic overhead, dismantling the bridge as soon as the traffic lightens.
The key point for me is that the ants are mostly responding to local conditions and to the few ants immediately around them. The bridge is an emergent property at a higher scale of the ants' local and simpler behavior. I have to wonder if any of the ants actually knows that it is building a bridge, or is it just doing what makes sense at the moment? Similarly, did our swarm learn things that are literally over our individual heads? Well, this will take much more thought.

RhizoRhetoric: 6 Emergence

The sixth characteristic of complex systems covers the concept of emergence:
The behavior of the system is determined by the nature of the interactions, not by what is contained within the components. Since the interactions are rich, dynamic, fed back, and, above all, nonlinear, the behavior of the system as a whole cannot be predicted from an inspection of its components. The notion of “emergence” is used to describe this aspect. The presence of emergent properties does not provide an argument against causality, only against deterministic forms of prediction.
The identity and value of a writing swarm is not the result of some characteristics or features innate to the various people in that swarm or to the various tools they use or the topics they write about; rather, the identity and value of a writing swarm emerges from interactions and exchanges among the actors and activities of the swarm. For instance, the topic of swarm writing was not a concept that we were all thinking about; rather, the topic emerged from our discussions and our interactions as we struggled to identify what we were observing people do in the #rhizo14/15 MOOC.

The swarm emerged and was defined from within, not from without. For instance, the various actors in the swarm were not selected by MOOC leader Dave Cormier beforehand based on some specific expertise of each and some goal of #rhizo14/15; rather, the swarm organized itself around discussions and tasks that interested various people at various times. People dropped in and dropped out of the swarm for their own reasons and according to their own trajectories, and the characteristics of the swarm changed as the swarm's actors and tasks changed. Enough actors have persisted to maintain the identity and some of the memory of the swarm, but enough actors have changed so that the swarm can respond to new ideas and tasks and take new directions.

As Cilliers points out, this is not a chaotic process that undermines causality and reason. The trajectories that all actors and activities in the swarm follow can be traced back to sufficient causes; however, the complex interactions of the actors do undermine our ability to predict absolutely what the swarm will do next. There is no guarantee that past activities will be accurate predictors of future activities. While the swarm does have memory that preserves past activities and structures, it is also open to new energies and information that can change those activities and structures.

This is all a way of saying that a writing swarm should expect novelty. What emerges from the swarm cannot be absolutely predicted by even a thorough examination and analysis of the constituent elements. The properties of a complex system such as a writing swarm emerge at a different scale, and the swarm develops its own agency, rules, and trajectory. The unexpected is not necessarily a sign of malfunctioning, and a writing swarm should not suppress the unanticipated new out of hand.

Tuesday, April 3, 2018

RhizoRhetoric: 5 Memory

The fifth characteristic of complex systems according to Paul Cilliers reads this way:
Complex systems have memory, not located at a specific place, but distributed throughout the system. Any complex system thus has a history, and the history is of cardinal importance to the behavior of the system.
As a complex system organizes itself, it develops memory: those repeated and eventually stubborn processes and structures that the system depends upon for its identity and functioning. In a sense, these stubborn habits of body and mind are the counterpoints to the dynamism that allows the complex system to learn new things. Memory is vital to complex systems, and eventually serves as an invaluable aid to a complex system, automating some processes and tempering if not dampening new energies and information. As the memory of a complex system develops and becomes stronger, it enters into what Edgar Morin calls a dialogic relationship with a system dynamism, or in educational terms: growth, learning, and development. Memory resists change, and change modifies memory. Complex systems, then, come to rely upon the constant tension between memory and learning, with memory sometimes taking the upper hand, and sometimes losing to new knowledge. This tension is not dialectical as there is no resolution or synthesis; rather, the complex system depends upon the constant, non-equilibrium and tension between memory and change.

Our writing swarm and its documents, for instance, cannot be understood and accounted for without some knowledge of its history and memory. Most immediately, the people in our swarm all shared the #rhizo14/15 MOOCs facilitated by Dave Cormier of the University of PEI. #rhizo14/15 takes its name (I think of it essentially as one course) from the rhizome of Deleuze and Guattari's philosophical work A Thousand Plateaus, and the swarm is in many ways another metaphor like a rhizome for complex systems. Thus, all of us were primed by #rhizo14/15 for thinking in terms of swarms and complex open systems.

Then, we are all connected to higher education either as students, professionals, or both, and we all share an interest in the new forms of higher education emerging and being discussed on the Net—hence, our attraction to #rhizo14/15. Particularly relevant to our current writing projects, we have all mastered the art of academic research and writing that is required for academic success. Some of us even teach research and writing to our own students. Thus, the new kinds of writing emerging on the Net are of keen interest to us professionally and personally, and our curiosity must be framed within the context of our professional work.

Next, we are all competent or better users of modern information technology. If we haven't used a particular tool that interests the swarm, then we are all adept at mastering the new tool in short order. Google Docs, the tool that we have focused on the most, was an easy decision for all of us, and we were all able to push it to its technical limits.

We need to talk about our swarm memory, such as we can remember it. And this brings me to a final point about memory in swarms: memory is distributed and not necessarily evenly. Thus, no one member of the swarm has all the memories. Even Google Docs, which records and date/time stamps every key stroke, does not have any memory of the tweets, texts, and Facebook messages among the humans, nor of their readings and research. Yet all of this memory is necessary for a full understanding of the identity of the swarm and of the documents that it has produced.

Monday, April 2, 2018

RhizoRhetoric: 4 Open

I just realized that I merged two characteristics of complex systems in yesterday's post. Cilliers' third characteristic has to do with direct and indirect feedback loops, but I won't correct my mistake here. I think I covered it sufficiently yesterday.

Cilliers' fourth characteristic reads this way:
Complex systems are open systems—they exchange energy or information with their environment—and operate at conditions far from equilibrium.
In my previous post, I explored how complex systems exchange energy and information among the elements within the system. This is the complementary process in which the system exchanges energy and information with its ecosystem. In some ways, this is the external process that feeds the internal process. A complex system (think here of a zygote or a writing swarm) may bring an internal store of energy and information (think of DNA and college degrees), but without regular exchanges of energy and information from the ecosystem, any complex system will die. Again, this is a fundamental process that accounts for the formation and functioning of stars and atoms as well as of writing swarms.

One cannot understand a writing swarm without understanding the energy and data streams that feed that swarm. The identity of the swarm emerges as the nexus of all those internal and external flows and exchanges of energy and information, and the swarm functions and sustains itself only so long as flows and exchanges persist.

The energy and information flows are dynamic, constantly evolving, which means that the complex system such as a writing swarm operates "at conditions far from equilibrium." Direct and indirect feedback loops are at work between the swarm and its environment just as they are within the various elements of the swarm itself. New information and energy feeds into a swarm, which processes that energy and information, dampening some and amplifying other but all the while modifying itself to accommodate and respond to that new data, and then the swarm feeds back new information and energy, which modifies its ecosystem across all scales. Constant feedback cycles process energy and information and feed back energy and information at both local and global scales.

This processing is at times synchronous within a writing swarm, but more often it is asynchronous as different writers across the world work and write at different times, so that documents emerge in fits. A whole section can emerge in a somewhat new direction with new energy and information, and then the entire swarm must process that new direction and adjust itself to it. Sometimes the new section finds a home, sometimes it is pruned. It is always edited and always leads to other edits as the swarm reconfigures itself.

This network of dynamic exchanges within and without the writing swarm defines the swarm and the writing that it produces. Eventually, the exchanges of energy and information stop and the document attains equilibrium. It is completed. The writing swarm, however, does not attain equilibrium; rather, it remains dynamic if it does not disband or die. Tension can emerge between the static, completed document and the dynamic, constantly reforming swarm, which can move beyond or away from the document in a very short time.

Swarm writing, then, can be a very messy process. While the swarm will try to manage its internal processing, it is always open to new information and energy streams which can surprise, delight, and confuse the swarm. Swarm writing makes great demands on the resourcefulness and resilience of the swarm to find its place within its ecosystem. This has certainly been the case with our swarm, which has struggled to find a way to express itself within an ecosystem not quite ready to listen to its song.

Friday, March 30, 2018

RhizoRhetoric: 2 & 3 Rich Interactions

Paul Cilliers' article "What we can learn from a theory of complexity" posits seven characteristics of complex systems, and I'm exploring each of the seven to illuminate the concept of swarm writing. Like Deleuze and Guattari, Cilliers begins with the characteristic of multiplicity, which I explored in my last post. In short, a complex system is composed of multiple elements at multiple scales.

In this post, I apply to swarm writing Cilliers' second characteristic of complex systems, rich interactions:
The elements interact dynamically by exchanging energy or information. These interactions are rich. Even if specific elements only interact with a few others, the effects of these interactions are propagated throughout the system. The interactions are nonlinear. There are many direct and indirect feedback loops.
This single characteristic could easily be parsed into half a dozen characteristics, but I think the main idea for me is that the emergence of a complex system such as swarm writing depends upon the ability and tendency of various elements to interact with one another. Prior to this rich interaction, a collection of elements is no more than a random scattering of people with no connection and no interactions with one another. Not until these elements—say, a group of people who happen to share a MOOC—begin to interact can a complex system, such as swarm writing, emerge. The coherence and identity of the swarm emerges from the rich interactions among the elements. The entity that emerges—in our case, a swarm—functions and has its identity at a scale different from its individual elements.

The network of interactions within a complex system is kickstarted by the exchange of energy and information, and in the case of swarm writing, mostly by the exchange of information—though I think most of my fellows in the swarm will agree that we exchanged lots of energy as well. Flows of energy and information inform all complex systems, and this process connects the emergence of writing swarms with the emergence of stars, galaxies, earths, life, nation states, the Internet, and love affairs. This flow of energy and information is about as fundamental a process as humans can imagine, and I find it gratifying to imagine a rhetoric that begins at the same place as the Universe.

I think, then, that our document about swarm writing should say more about the exchanges of information and energy that informed the emergence of our particular swarm. I believe this would clarify for recalcitrant readers what we are trying to say. I can begin a list of the information and energy that I know about, but I really need my swarm here. Flows of energy and information are much like the flows of streams that feed a river: they come from a thousand different sources and take a million different paths. I cannot know all of them. Even my swarm cannot know all of them, but they can know enough of them to give a sense of the complex ecosystem that we are trying to describe. We should do this.

Then, the interactions among the actors in a swarm are mostly local, but because they are nonlinear with many direct and indirect feedback loops, they can propagate throughout the swarm. This makes great sense of any swarm, writing or otherwise. For instance, I interacted mostly with a handful of people and mostly through Facebook and Google Docs. Others in the swarm interacted with a different group of actors, similar to mine, but not the same (note the fractal flavor here). Moreover, my local, immediate connections morphed from the beginnings with #rhizo14 until this latest version of the swarm writing this document.

Like all the different actors in the #rhizo14 swarm, I brought certain ideas and energy to the group mostly communicated to my immediate, local connections. Those connections then muted some of my ideas, or amplified some. The amplified ideas propagated to the rest of the #rhizo14 swarm, perturbing the group in various ways, changing the flavors of its interactions and identity. In communication terms, I was helping to develop and re-channel the conversation, as were other actors in the swarm. These complex set of interactions are what made #rhizo14 and its sub-swarms what they are. I think we need to say that in our current essay. We can at least hint at it, providing a general sketch.

Then, note the interactions between the different scales of the swarm. The entities that function at different scales—the total #rhizo14 swarm, the sub-swarms, the individuals—are not insulated from each other. Rather, energy and information are exchanged across scales in direct and indirect feedback loops that inform and modify each other. Each scale feeds on the other scales, modifies its own internal structures and functions, and then feeds back to the other scales, which modify in turn, around and around in a mostly elegant swarm.

Finally, the nature and identity of the swarm emerges from the interactions among the actors, not from the individual characteristics—such as intelligence or beliefs about education—of the individual actors. The documents that emerge from swarm writing are a result of the network of rich interactions among the actors. The documents are the result of non-linear mathematical operations, not the result of simple linear addition or subtraction. Thus, small events such as using Slack or not can lead to big effects. Similarly, large events such as the failure of #rhizo16 to actually convene can lead to small effects. Moreover, the interactions are not all nice. Our writing swarm did not simply hold hands and sing Kumbaya. Interactions are at various times cooperative, collaborative, and competitive. We challenged each other, usually courteously, but not always. We should discuss this in our paper.

I think our paper will benefit from a brief description and discussion of the rich interactions in our swarm, and I challenge our group to consider it.

Thursday, March 29, 2018

RhizoRhetoric: 1 Multiplicity

I'm working with a #rhizo15 group to revise a document we've submitted for publication in a scholarly journal. The document tries to map the swarm writing that emerged from the Rhizo14/15 MOOCs, and I think our problems are two-fold:
  1. We find it difficult to demonstrate and discuss open swarm writing within the narrow boundaries of a traditional scholarly study, and
  2. We find it difficult to connect readers with a traditional research agenda to the concept of swarm writing.
One sympathetic reviewer suggests that we focus more on swarm writing, and I want to explore some ideas in the next couple of posts. One of the personal problems I have in revising this particular document is that my own thinking about swarm writing has developed much since we first wrote this document, and I find myself wanting to add new material to the document rather than merely editing the existing material. I'll try the new material here first rather than in the document to see how it wears.

I'm starting with an article about complexity from Paul Cilliers entitled "What we can learn from a theory of complexity" first published Mar 31, 2000, in Emergence: Complexity and Organization. I'm drawn to this particular article from the many I've read by Cilliers because, paradoxically, of its simple list of some relevant characteristics of complex systems. I consider swarm writing a function of a complex system, and I think these seven characteristics will help our article address the problems we have with discussing swarm writing in a traditional scholarly context.

Cilliers begins his article by listing seven characteristics of complex systems:
  1. Complex systems consist of a large number of elements that in themselves can be simple.
  2. The elements interact dynamically by exchanging energy or information. These interactions are rich. Even if specific elements only interact with a few others, the effects of these interactions are propagated throughout the system. The interactions are nonlinear.
  3. There are many direct and indirect feedback loops.
  4. Complex systems are open systems—they exchange energy or information with their environment—and operate at conditions far from equilibrium.
  5. Complex systems have memory, not located at a specific place, but distributed throughout the system. Any complex system thus has a history, and the history is of cardinal importance to the behavior of the system.
  6. The behavior of the system is determined by the nature of the interactions, not by what is contained within the components. Since the interactions are rich, dynamic, fed back, and, above all, nonlinear, the behavior of the system as a whole cannot be predicted from an inspection of its components. The notion of “emergence” is used to describe this aspect. The presence of emergent properties does not provide an argument against causality, only against deterministic forms of prediction.
  7. Complex systems are adaptive. They can (re)organize their internal structure without the intervention of an external agent.
I want to write seven posts applying each characteristic to swarm writing to see if this can help me illuminate swarm writing for those who see it as little more than standard writing in a Google Doc.

Cilliers' first characteristic involves a multiplicity of interacting parts, as I see it: "Complex systems consist of a large number of elements that in themselves can be simple." This first characteristic drives to the heart of what makes swarm writing different from the long tradition of Western rhetoric: swarm writing undermines the idea of a single, or at least unified, authorial voice usually declaiming on a single, unified topic. This also pinpoints the issues the #rhizo15 swarm is having with our document: we struggle to create a single, unified voice addressing a single, unified topic to meet the demands of traditional scholarship. In other words, we are trying to describe an open, dynamic process in a closed, rigid scholarly document.

So let me restate Cilliers in terms of swarm writing:

Swarm writing consists of a large number of actors (human and non-human) that in themselves can be simpler.

Note my changes. First, I say actors rather than elements to reflect my belief that everything in a complex system has agency. I could have used the term agent, but we use actor network theory (ANT) in our document, so I'm using actor. Also in keeping with ANT, I'm including all actors: pens, pencils, paper, Google Docs, smartphones and tablets, global communication networks, college educations, and Becky, Maha, and AK—most all the actors that play in our writing swarm, human and non-human.

Also note that I change simple to simpler to reflect my belief that most everything is complex. Consider the elements of our swarm that I list above. Perhaps a pencil is simpler than a human, less complex. Still, I see a pencil as a complex system. If you take the ANT approach to understanding a pencil, then you quickly see how the simple pencil becomes complex. A finished pencil emerges at the end of incredibly rich and complex mining, manufacturing, and marketing systems that interact with countless other actors, and then that one pencil takes a path through the world that can be incredibly rich, even unique among all pencils. For me, then, simplicity is a relative state, not an absolute characteristic.

I also should add here that while it is easy to see a million people tweeting #MeToo as swarm writing, I also think that a single person writing—me writing this current post, for instance—is swarm writing. I, too, am a swarm—no doubt a less complex swarm than my #rhizo15 swarm or the #MeToo swarm, but a swarm none the less.

Still, the way Cilliers phrases this first characteristic lays the groundwork for his later comments about emergence. As a large number of elements or actors begin to swarm together, a more complex actor can emerge: the complex system, or a writing swarm, or a novel, a nation state, a galaxy. This emergent actor is usually more complex than its constituent actors and can function at another scale.

But much needs to happen before a collection of people and their tools become a writing swarm. That's what the next characteristics and posts are about.