Working with Complexity
The study of complex systems involves understanding how vastly different systems - composed of elements as diverse as sand, ants, or people - enter into more fit and resilient states by virtue of the special qualities of their internal dynamics. Despite the seeming diversity of such systems they are subject to the same Governing Features.
This website is intended to serve as a general orientation to understanding these governing principles and working with complexity. It is intended both for those new to the study of complex systems, and to those who may already be familiar with complex dynamics but wish to broaden their knowledge. Using non-technical language, it will help users:
identify complex systems;
understand their governing-dynamics;
unravel key concepts and terms;
frame problems in ways that lend themselves to solutions that employ complexity;
gain tools for applying this understanding to problem-solving in disparate domains.
What do we mean by complex?
When we speak of a system being a 'complex system' we wish to identify it as belonging to a particular class of systems, all of which are subject to the same general dynamics. To understand complexity it is perhaps useful to consider the word 'plexus' or 'braided' from which we get the word 'complex', referring to being "braided together." This term is apt as these systems can be understood as involving an intertwining of elements. Here, instead of there being clear chains of case and effect, the behavior of one system element is both a cause and an effect of the behaviors of other elements in the system.
A primary aim of this website is to understand what is, and what is not a complex system, so we can better apply our understanding of complexity across research domains. Accordingly, it is important to clarify what we do and don't mean by a 'complex' or intertwined system vs a 'complicated' system. Complicated systems are subject to an entirely different set of dynamics which, while interesting, are wholly unrelated to the causally intertwined systems we wish to speak about.
Consider an aircraft. It is a complicated system made of many sophisticated components that come together in very specific ways in order for the aircraft to fly. We can say that the aircraft is made of many individual parts, that these parts interact and sometimes exchange energy or signals. Together, these individual components are structured so as to form an 'emergent' aircraft that is 'complex'. This description of an aircraft is accurate and it employs terminology often used in Complexity theory.Now consider a sand dune. It is composed of many individual grains of sand that come together, steered by wind currents and by global dynamics involving the sand particles interacting both with the wind and one another. Together, the grains of sand gradually form an 'emergent' dune that has an integrated form, articulated by ripple patterns that are emergent and 'complex'.
If we were to put an aircraft next to a sand dune and ask what is the more 'complex' system, an intuitive response might be that the aircraft - with all its complicated machinery - is the more complex of the two.
But an aircraft is not a complex system whereas a sand dune - simple as seems - is.
Perhaps this is too extreme a statement - indeed, if we look at the formal definitions of the words 'complex' and 'system', it would be hard to argue that an aircraft is not a complex system. But it is not useful to position an aircraft as a complex system in order to gain a better understanding of it.
Suppose we identify an aircraft as 'a complex system'. We could then spend a lot of time learning how sand dunes form and how emergent patterns of sand ripples arise, in order to gain an understanding of complexity and emergence. These studies, informative though they might be, would do little to enlighten us regarding aircraft operations. This is not to say that comparing an aircraft to a sand dune would be pointless - it is possible that this novel lens would provide us with new insights into aircraft design - but we would not be employing a transfer of knowledge between systems that are subject to the same kinds of dynamics. The parameters that inform the emergence of aircraft flight are not part of the same class that inform the emergence of sand ripples.
The systems we wish to focus on are subject to the same universal or general governing dynamics. Other kinds of systems, that might indeed be complicated, are subject to different kinds of governing dynamics.
Beyond the hype
Many people are excited about complexity research and its concepts. There is lot of hype around words like self-organization, emergence, non-linearity, etc., and these are used to describe a host of systems. While there is nothing inherently wrong with this, it is nonetheless important to understand the difference between insights gained by metaphoric thinking versus insights due to intrinsic correspondences between systems. I might compare a city to a body, then state that suburban growth is like a cancer. I can then equate planning and zoning restrictions with chemotherapy (limiting growth). The analogy might be productive, but I shouldn't then imagine that by immersing myself into learning about the dynamics of cancerous growth I will glean valuable insights regarding the dynamics of suburban growth.
In order to learn from complexity, it is important to know the appropriate kinds of systems that might be framed this way, so that we can draw appropriate insights from the underlying dynamics operating in all. Regardless of system - be it sand dunes or ant colonies or netflix recommendations - there are consistent dynamics at work in complex systems. Consequently, if we understand one system - and the kinds of mechanisms governing its behavior - it is much easier to figure out what is going on within another, and much easier to use complexity dynamics to design solutions for specific problems.
The amazing thing about complexity is that we actually can gain insights about how cities change and evolve if we know more about how ants find food - and not just metaphorically.
Complexity for who? (urbanism and beyond)
A portion of this website is devoted to content specifically oriented towards how insights from complexity can be (and are) used to inform urban theory.
That said, it is not an urban theory website: urbanism is just one potential application.
The website is intended to be of use to those interested in coming to complexity from diverse perspectives. It can serve as a tool to understand how different research discourses (beyond urbanism) apply terms, tools, principles and methods from CAS research. Accordingly, it can serve to bridge gaps between discourses.
The website has a wealth of content to explore, including key thinkers, terminology, books, thought experiments, and videos that will assist in illustrating key ideas.
It is intended to introduce people to a new way of thinking about the world - one where we begin to perceive a host of phenomena operating as complex systems.