Another way of thinking about the corruption of purpose as complex systems age requires that we think of complex systems as having two core missions:
The Purpose of the System or the Original Mission
Over the aging of every complex system, the second mission gradually comes to dominate over the first. This systematic iterative alteration of the organization’s mission parallels both the potential for moral corruption and the corruption of purpose that is the unavoidable result of complex system aging.
This happens to each of us (how much more time do we spend on maintenance and repair of ourselves as we age?), but is most obvious in organizations:
Increase in bureaucracy, process requirements,
Increase in hierarchy and politics
Increase in management costs
All resulting in the degradation of actual customer or service support and
Eventually, the primacy of money/power over everything else
There are many more signs of system aging than the reasonably obvious ones I’ve discussed so far. The next few posts will identify some, especially those which trigger “solutions” that don’t actually “solve” the targeted problem. The first is that systems can be corrupt, not just people.
We tend to think that corruption is an ethical or criminal matter resulting from a moral failure. As a society, moral and law enforcement solutions are the only ones we actively support to such problems. This is a mistake in our thinking because there is a larger impact of such moral corruption on the complex system in which the corruption occurs. Additionally, the aging of complex systems creates a type of corruption of purpose even if, somehow, we are able to stop all criminal and moral corruption.
On its own, typical moral corruption gradually taints every transaction of a complex system, even when the people involved in the transactions are not participants in the moral corruption. This is obvious in financial corruption but also occurs when values and ethics are corrupted.
Also, complex system corruption occurs as a result of the aging process arising as system resources increase and are stored for later use. These resources (regardless of type) begin to be used increasingly for maintenance, repair, personal gratification, and personal power, undermining the purpose of the system. This process also creates an affordance that permits more extensive corruption, creating a vicious feedback loop.
Every complex system has a history, and there is no way to avoid the effects of that history. This means:
You can’t go back to the beginning.
You can’t even correct something and try again. There are no do-overs. The effects of history always become part of the aging of the system.
You can improve part of the system, like getting a hip replacement when arthritis impedes the use of your leg, but
You (and any complex system) is still aging.
Improving the function of a complex system makes it more complex and makes the use of affordances more difficult and resource intensive.
Eventually, the sum of all this is some kind of collapse. When and how are not predictable, but all complex systems collapse, slowly or quickly.
A good “concrete” example of the overall process of complex system aging is the development and current state of the US freeway system.
I am old enough to remember when the freeway system was built. I was in elementary school and I saw the building process because my extended family all lived in Detroit, while my father worked at Dow Chemical in Midland, Michigan. Before the freeway was built it took us nearly 4 hours to drive from Midland to our relatives’ homes. We had a long trip through small towns with two-lane 25mph roadways and stoplights. In bad weather, it was worse.
The first time we drove the freeway to Detroit, it took us less than one and a half hours. It seemed like a miracle. For a long time, the only problem was the increased use of the freeway by other drivers as they got more used to the idea of a freeway and its convenience.
Then the population grew, the number of people who used cars grew, the use of freeways for commutes allowed people to live further from their jobs, etc. So there were traffic slowdowns that increased the length of time it took us to drive to Detroit, and we had to be more careful when we made these trips so we wouldn’t run into the commuter traffic. And, of course, the increase in traffic density led to accidents that wouldn’t have occurred otherwise.
Then the roads needed repairs and maintenance, partly because of their increased use. We all know this led to our current experience of freeways, not a miracle, but an increasingly useless tool which we must use, like airplanes.
If it was possible, we could simply eliminate the entire freeway system and start over again from scratch. We could use modern materials that wouldn’t break down as fast, we could have more lanes, we could rethink the way we use freeways.
But of course, we can’t do that. And the core reason why we can’t start over again from scratch is that we must use the freeway every single day without fail. And buying an entirely new land base for the freeway would destroy the economic system that was built around the existence of the freeway. And all that concrete would have to be removed before the land the current freeway system is on could be used for any economic purpose. And all that concrete would have to be transported and deposited somewhere.
If all of this seems obvious now, the question you should ask yourself is why it wasn’t obvious from the beginning?
This model uses the commonly observed process of infant development as an analog for the growth of a complex system.
Infants are surrounded by a large, more or less infinite environment of possibilities. But it is in the nature of developing infants that the vast majority of these possibilities are of no interest and do not at any given moment contribute to the infant’s development. Instead only certain parts of the environment are of interest to the infant and these are exactly what the infant needs to engage with in order to further current development.
These parts ready for engagement are called “affordances” because they allow for action by the infant that supports the infant’s current development.
As development continues, those parts of the environment that can act as affordances shift because of the growing competence of the infant and their consequent shift in focus and interest. So, the infant’s “affordance interface” is constantly shifting as development occurs, and exactly tracks the current development of the child.
The deep part of this model is that even if you are 90 years old, you are still doing what the infant is doing, albeit at a different functional level and with a different set of strengths and weaknesses (i.e., a different affordance interface).
In this model (very abstract), the world starts with a bunch of nodes (actually self-sustaining processes) that act for their own reproduction, however that happens.
When there is a reason to do so, one node connects with another to exchange food, goods, information, whatever. These first connections are done less because of need and more because of the ease of connection. Maybe I form a relationship with a farmer at a farmer’s market to get vegetables that are hard for me to grow for myself.
Over time, especially with the growth of population, more and more of these connections are made. This process is fairly straightforward until we have to change a connection.
Maybe the farmer dies, and the family leaves the farm, and it’s turned into a housing development project which we don’t need.
Needing to change a connection can also occur because of changing technology (stores instead of individual farmers). Whatever the convenience of the new connection, it will almost always be more complicated than the one you had before, and there are additional costs associated with making the change and using the new connection.
This is the kind of change in a system that leads to aging at the large system scale.
The model above is the simplest version of the Adaptive Cycle I could find. There are a lot of more complex diagrams that are useful once you know how the basic model works. Think of how a forest comes back after a fire removes the previous forest. The recovery has 4 phases:
Fast Reorganization (Pioneer Exploration by First Weeds)
Fast Exploitation (Entrepreneurial Expansion by Most Successful Weeds)
Slow Conservation (Organizational Ecosystem Development by the Developing Forest)
Slow Degradation Followed by Fast Release (Collapse due to Increasing Brittleness over time)
This final phase of collapse creates the circumstances of a new cycle.
These cycles are not entirely predictable. But the larger phases can be recognized if not foretold by simple observation. (At least if you are looking for them.)
Complicated systems are ones that have many mechanical parts, like a 777 plane. The parts have relationships with one another, but the parts don’t change just because they interact. Aging in complicated systems is mostly that the parts wear out over the lifetime of the system.
Complex systems also have parts and relationships, but the parts change all the time because of those relationships. The relationships modify over the course of the system’s lifetime as well.
All complex systems age. Even the universe ages, though I suppose we won’t have to worry much about the effects of that. We all tend to think such aging has no relevance to us. Our society is so big, and our concerns are so local.
In a sense that was true in the past, but no more. Our larger system affects our lives in important ways every day, and the impact seems to be expanding and accelerating.
We have to understand the contours of this aging in order to make reasonable choices about our future and to preserve our flexibility for those parts of our future that we can’t predict or control.
Once we give up the idea that complex, adaptive systems are machines, we must confront the reality of system aging.
Deep down, there is in the substance of the cosmos a primordial disposition, sui generis, for self-arrangement and self-involution. Pierre Teilhard de Chardin
Mostly, we think about evolution as though it is trying to create the perfect organism. I suppose this reflects the importance that we humans place on reputation, social status, and power in our society. But evolution doesn’t care about our social values. Evolution is about continuing to evolve, and the key to that is creating variation. As much variation as possible.
Selection (what we tend to think is the important part of evolution because it is important to us) is automatic anywhere there is a scarcity of any kind of resource.
It is the variation that “drives” evolution. Selection works locally, variation works throughout the complex system of life.
Evolution is about continuing on despite uncertainty (the universe is a very uncertain place), and variation is the best way to be ready for what you just can’t predict.
Since the two most consistent forces in evolution on this planet have been gravity (a fulcrum for all movement that shifts in its impact with every movement) and the day/night cycle (framing the cycling of all processes in every complex system), change is constant.
Disruption is rooted in life itself…Life’s essence lies in accidents and interruptions, in conflict and tension. Jean-Marie Dru
Complex Systems Are Not Machines
If I were to ask most people if they thought their pet dog or cat was a machine, they would likely say “no”. I certainly agree with this having had, now, 5 dogs over the years. Most people get that the larger world does not consist of a bunch of machines.
But….We continue to try to solve problems by using models that are based on machines. We describe the problem we are trying to change as though it were isolated, like a broken part in a machine. Our problem solutions are all of the sorts, “This is what is broken; we can put a new part in place of the broken part. That will take care of the problem”.
This approach doesn’t work for complex systems like our society any better than it works for your pet. Every time we replace the “broken” part with a new one, we create new problems over time, called “unintended consequences”.
The unintended consequences are experienced as new problems, entirely separate from the one we “solved” earlier, so we try to replace those new broken parts as well. And so on……..
Because we focus on fixing parts, we keep making new problems for ourselves. Worst of all, we think we are actually improving the system by fixing the part.