As we launch our new sponsored research project, Exploring Emergence in Complex Social Change Initiatives, we realize that the field of work on which it is based might be new to many of our colleagues. While much has been written about the field of Complex Adaptive Systems, much of it is written for scientists and often incomprehensible to non-scientists. Here is our attempt to define this important work in layman’s terms.
A complex system consists of many, diverse parts, all of which interact with each other and, in so doing, create patterns that are more sophisticated than any one part operating on its own. Human languages are capable of an endless variety of meaningful communication, using a fairly small set of letters and punctuation marks, with some rules about how to combine them into words and how to combine words into sentences. Snowflakes are formed in beautiful patterns, all of which are made through the random interaction of ice crystals. Both snowflakes and human communication are endlessly varied, without having to be consciously designed in advance. Human beings are also examples of complex systems. We are composed of many, diverse cells, each of which have limited capabilities. But through the cells’ many interactions, the behavior we are capable of is endlessly rich and complex. If our cells did not interact, if ice crystals did not adhere to each other, this quality of rich behavior would be impossible. These richer patterns of behavior are said to “emerge” from these many random interactions.
As a system, we are also adaptive. Unlike a snowflake, our collection of cells is capable of having a goal — survival, reproduction, comfort, wealth — and to adapt to feedback from our environment in order to achieve it. The same can be said for our immune system or an ant colony. Collectively, through the constant interaction of individual entities, or “agents,” as they are called by complexity scientists, the larger system of which they are a part, is capable of responding to our environments in ways that take us closer to a goal than any individual agent would be capable of on its own.
A complex adaptive system is non-linear. It can be distinguished from a machine, which exists because it had a designer who could predict in advance how a particular combination of components would operate together to produce a specific behavior. Complex adaptive systems are not predictable in the same way. Researchers at the Santa Fe Institute, an important center for complexity science, have done fascinating research using complex adaptive systems as a frame, for example, to understand how cities and economies behave.
As we describe in the announcement to our research on Emergence, the social sector has begun to understand that the systems it hopes to impact are also highly complex, which suggests that we need to think differently about what it takes to achieve the kinds of impacts we aspire to create.
For example, complexity scientists emphasize that agents in a complex adaptive system behave according to simple rules and it is through the simplicity of those rules that rich patterns of behavior emerge. A frequently cited example is how birds flock. The rules that generate that behavior are very simple and do not include identifying a leader, famously modeled by Craig Reynolds in his BOIDS simulation. The corollary to that, described by Stephen Johnson in his book Emergence, is especially relevant to philanthropists: “Emergent systems can grow unwieldy when their component parts become excessively complicated. Better to build a densely interconnected system with simple elements, and let the more sophisticated behavior trickle up.”
We anticipate that our research will help us understand better how to think about the process and benefits of emergence and help funders, grantees and other partners in the social sector understand what they can do to improve their impact as they work to achieve complex goals in complex systems.
For more information on Complex Adaptive Systems, we recommend Emergence by Steven Johnson as a comprehensible and enjoyable description of how this theory can be applied to understanding everything from ants to brains to cities to software design. A Hidden Order by John Holland gives an in-depth description of the principles of complex adaptive systems theory.