It’s not everyday that you see complexity science propped up in big type in a major newspaper like the New York Times, but a couple weeks ago in that’s what happened. The article, titled: “It’s Complicated — Making Sense of Complexity” is enough to get a professor like me all giddy.
In the piece, authored by frequent contributor David Segal, took a light look at the distinction between complicated and complex situations, something I’ve discussed in other posts, pointing out that the confusion between these two concepts often leads us to trouble. To illustrate this, Segal quotes Dr. Brenda Zimmerman from York University’s Schulich School of Business, one of the leading proponents of complexity science in social systems like organizations. Dr. Zimmerman states:
What we need, suggests Brenda Zimmerman, a professor at Schulich School of Business in Ontario, is a distinction between the complicated and the complex. It’s complicated, she says, to send a rocket to the moon — it requires blueprints, math and a lot of carefully calibrated hardware and expertly written software. Raising a child, on the other hand, is complex. It is an enormous challenge, but math and blueprints won’t help. Performing hip replacement surgery, she says, is complicated. It takes well-trained personnel, precision and carefully calibrated equipment. Running a health care system, on the other hand, is complex. It’s filled with thousands of parts and players, all of whom must act within a fluid, unpredictable environment. To run a system that is complex, it’s not enough to get the right people and the ideal equipment. It takes a set of simple principles that guide and shape the system. For instance: Teach everyone the best practices of doctors who are really good at hip replacement surgery.
So here’s a leading proponent of complexity science, providing clear examples of the distinctions between complex and complicated in a major newspaper, and finishing it off with a health example. What more could I want?
Yet, I was disappointed by this piece, and particularly the examples described above. The reason was not because they were wrong or inaccurate per se, but rather they are well-worn (to complexity scientists) to the point of being a ‘pat response’ and it is that feeling that stirs concern.
The idea of the simple principles concept comes from work done on ‘Boids‘ and other simulations of complex systems where lots of activities happen simultaneously to produce order out of a situation that is ripe for chaos. Research on flocking or swarming behaviour shows that, despite the volume of actors in the system (like a flock of sparrows), a few simple rules can guide complex behaviour, almost reign it in. With birds flocks, rules such as:
1. Stay equidistant between the closest other members of the flock;
2. Avoid hitting other objects, but keep moving;
3. Steer towards the average position of your flock mates
This produces something that researchers believe approximates the behaviour simulated in the video below:
This is a theory that has been explored with many species and been found to be robust enough to warrant serious consideration. The problem comes when we take these same principles and apply them to human systems. Unlike birds or fish, we are actually quite horrible at following rules, even the most simple of them. It is for this reason that many best practice efforts in health cease to gain widespread adoption. And while there is a movement afoot to use simple rules like checklists to guide certain behaviour in health and other fields, the cases in which these checklists work like surgery are ones that are complicated, not complex.
Human and social systems might be described as ultracomplex because they are governed by chaos, complexity, complexity, simplicity at the same time (for those interested in the relationship between these, I’d recommend studying the Cynefin Framework developed by Dave Snowden and the folk at Cognitive Edge). We humans have rules, but we apply them indiscriminately and consistently depending on the context — which includes person, place and time. Unlike the bees that will create elaborate hive behaviour that resonates with complex systems, bees don’t worry about their self-esteem, tend not to create elaborate myths to guide their collective actions, or empathize with the plight of other insects. Humans ability to self-reflect, to engage in metacognition, empathize, and morally reason makes them different from other natural phenomena, making them problematic for applying the rules of complexity to without some considerable reservations or contextual binding.
I write this as an avid believer in the potential applicability of the laws and rules of complexity from the natural world to the human one, but one also troubled by how quickly we systems scholars apply these concepts without deeper thought on the theoretical and empirical problems that they pose in transferring evidence from domain to domain. There is relatively little good, quality evidence on the use of complexity science as a guiding framework for human action based on studies with humans — insofar as other bodies of evidence are available on similarly tricky subjects. And yet, conceptually, complexity-based concepts like emergence, sensitivity to initial conditions, self-organization and fractal patterning often do a better job explaining plausible connections within human systems than much of the normal, linear science.
Yet, possible face validity does not excuse our need to develop a science that can enable us to speak with confidence on the patterns we see and the meaning — if any — that comes from them. As scientists, it is our job to develop this and take the risks that come with that charge. Perhaps once this evidence based has developed, we’ll see experts discuss the differences between complex and complicated situations citing more than just analogies, but empirical research too.