Much of my work deals with theories of complexity, seeking ways to operationalize the concepts of these natural science theories for use in social science research, and develop new complexity-based concepts for the study of social phenomena. Eventually I’ll write a blog post (or six) that deals with some of these concepts in greater depth, but here’s a quick and dirty summary of some of the key characteristics of complex systems:
- they are made up of individual elements, or agents;
- these agents engage in local, recurrent interactions based on rules that may change as circumstances evolve;
- these interactions lead to patterns of self-organization among agents, as they form groups and develop modes of behavior to adapt to internal and external changes (self-organization is also often referred to as emergence);
- as a result, the system is dynamic and unstable, subject to both gradual and sudden change;
- everything that occurs within the system is dependent on what has come before: history plays a central role in self-organization and system change, even when the changes are nonlinear (cannot be immediately traced to a proximate cause);
- the boundaries of complex systems are highly permeable and not clearly defined: the extreme level of interdependency makes it difficult to say what lies “inside” the system, and what lies “outside”;
- for similar reasons, complex systems cannot be reduced: extracting part of the system, or statistical sampling, will necessarily lead to the loss of significant sets of relationships among agents, and thus obscure some sources and/or reflections of change.
One reason that the complexity sciences have resonated so deeply with me ever since I first discovered their existence, several years ago, is that I can so clearly see evidence of complexity in my own life. Seemingly random interactions form recognizable, emergent patterns over time, and an insistence on expecting linear a+b=c results is bound to meet with disappointment. Personally, I’ve found it less stressful and more satisfying to embrace nonlinear outcomes and allow myself to be surprised by where life takes me. (This doesn’t mean accepting fatalism: the importance of history and local interactions means that I have to focus on my own efforts, actions, and relationships. They just may not end up leading to where I think they will.)
My professional interest in complexity has produced some emergent patterns as well. First, it led me to pursue a doctorate, which wasn’t at all my initial plan, and to write the book that came out this past summer. Both were the result of my master’s thesis and my resulting relationship with Priscilla Murphy, who was the only person writing about public relations and complexity back when I first began studying these issues. It has led me to study networks and narratives, which in turn have introduced me to certain people and bodies of literature. And at the moment, it has led me to projects as diverse as my current research on Twitter in public relations, collaboration with my colleague Yushim Kim in the School of Public Affairs here at ASU’s downtown campus, and with the Consortium for Strategic Communication led by Steve Corman at the Hugh Downs School of Human Communication in Tempe.
As recently as six years ago, I never could have foreseen any of the above, yet in retrospect it all fits together perfectly. (That’s what I would call the narrative dimension of complexity.) I love seeing the emergent patterns in my life and my work.