“If a factory is torn down but the rationality which produced it is left standing, then that rationality will simply produce another factory. If a revolution destroys a government, but the systematic patterns of thought that produced that government are left intact, then those patterns will repeat themselves… There’s so much talk about the system. And so little understanding” -Robert Pirsig, Zen and the Art of Motorcycle Maintenance
Syntheses & Analysis
Reductionism is a process of reasoning used to describe things by breaking them down into their constituent components, analyzing the properties of these components in isolation and then recombining them in order to get a description of the whole system as a set of its individual parts, their properties and the linear relations between them. This is a process of reasoning that comes very natural to us, we can take anything from a planet to a bird, to a car or business organization and use this method of reasoning in order to understand how it works and then from this we are able to change its functioning by changing the parts or how they interact, this process of reasoning is also called analysis and it is central our engineering of technology.
There is, of course, another method for describing things called synthesis, instead of breaking things down, with synthesis we put them together, that is to say, we look at the system within the context of its environment and its relations to other systems in that environment. From this perspective, a bird is the way it is because of its place within the ecosystem it is a part of. The bird has wings because of the makeup of the atmosphere, water resistant feathers because of the nature of water, and a beak because of the structure to the other creatures or plants it preys upon, it is the product of its relations and functioning within the environment it is a part of. Syntheses recognizes how new levels of organization emerge at different levels because of the interaction between the system and other systems within its environment.
These are two very different ways of seeing the world and unfortunately, they don’t always sit too comfortably with each other. The aim of the game within the reductionist paradigm is to break things down in order to itemize their parts; the whole is thought to be nothing more than the sum of its parts. Thus once we have this set of parts and know how to put them together we can then, of course, change the parts in order to alter the functioning of the entire system, we can alter the parts in order to optimize the system to our advantage, and this is what we call engineering. Once we understood the workings of plants within the biosphere we could create farms, once we understand atoms we could engineer new molecules and now that we understand DNA it is thought that we can do bioengineering.
With relatively simple linear technologies the whole is simply the sum of its constituent parts and the reductionist paradigm can work well but with increased complexity it starts to breakdown
From The Micro To The Macro
These two visions of the world are in many ways focused on different levels, synthesis is often looking at the macro level with analysis focused on the micro level, but of course, what happens on the micro affects the macro and vice versa. Macro-level systems like ecosystems are regulated by a complex set of feedback loops that hold them in balance; the system is regulated by the interaction between all its parts. In a mature ecosystem, the creatures and the feedback loops that they maintain have evolved over a very long period of time, the same is true for economies, societies, cultures and our technology infrastructure, they are complex systems that are maintained and regulated by many interacting parts that create feedback loops.
Analysis by focusing on the components fails to recognize this emergent macroscale system of organization. When we re-engineer some system to have different properties or functioning within this environment without taking into account its effect within this network of interaction, then we do not know what will happen, particularly when we do not yet understand how this set of feedback loops actually work, as is often the case with complex technologies. Because of the way modern science has developed under the reductionist paradigm we often have a far superior capacity to understand and engineer the components in isolation, as opposed to the system as a whole. Now, this may not be a problem if the scale of our engineering only affects a few elements that are not critical to the system as a whole and do this at a relatively slow pace, as was the case in pre-modern times. But increasingly this is not the case, as we engineer more systems within our environment at a greater scale and pace of change, because we don’t understand all the interactions and feedback loops that are being altered, what emerges out of this is a world of volatility and uncertainty.
“Certainly, 10,000 years ago, the civilization’s beginning, the human portion was less than one-tenth of one percent… Humans, livestock and pets are now 97 percent of that integrated total mass on earth and all wild nature is three percent. We have won. The next generation doesn’t even have to worry about this game, it is over. And the biggest problem came in the last 25 years: it went from 25 percent up to that 97 percent. And this really is a sobering picture upon realizing that we, humans, are in charge of life on earth; we’re like the capricious Gods of old Greek myths, kind of playing with life — and not a great deal of wisdom injected into it” – Paul MacCready: Nature vs. humans
These complex systems are held within their current configuration through negative feedback loops that stabilize them, if we break these negative feedback loops by re-engineering components without having some understanding for these links that regulate the entire system, this releases the components that were being constrained by the regulatory loops and we get an imbalance of positive feedback loops. A simple example of this might be removing all the wolfs in an ecosystem, this would break the negative feedback loop between that creature and its prey, and would create a positive feedback loop as the prey get overpopulated, which would affect the other elements in the system and so on, as the system goes out of balance due to the removal of this regulatory loop.
This might be fine if the overall system is able to adapt to it, but if you have too many of these interventions then the system becomes unbalanced and may collapse. If you remove too many negative feedback loops that regulate a system you get an increase in positive feedback, and positive feedback leads to runaway effects and a phase transition as the system moves towards the emergence of a new regime. Exponential growth is a hallmark of systems in a phase transition and of course something we see all around us from the growth in population to the growth in computing power, to the growth in agricultural harvest and across many other domains of technology. The engineering of subsystems without understanding the macro system that they are a part of takes us into a world of volatility and uncertainty, that is characteristic of the 21st century, the so-called VUCA world.
Understanding the macro scale feedback loops that regulate our engineered environment is key to achieving a sustainable method of technology development
Unfortunately, the capacity to understand and engineer some subset of a system does not mean we understand the entire system. The reductionist paradigm focuses on the components within a system, meaning we often have a much greater understanding of the sub-systems than the whole. We might understand the greenhouse effect and even be able to engineer it but we don’t understand earth’s systems in their entirety and what effect this would have on them. At some point the scale to which we engineer the components of a system reaches a critical level where it affects the fundamental structure and governing dynamics to the entire system. This is the idea behind the Anthropocene, that human activity has reached a critical scale that it is now becoming the primary factor in regulating and shaping earth’s systems.
What we are talking about here is in many ways captured by the term hacking, which can be understood as the re-engineering of some component within a larger system in order to optimize it for a function that it was not originally intended for, in so doing the hacker breaks the integrity of the original design to the system. We are altering a subsystem in order to optimize it for our specific interest, and this is one way to understand the Anthropocene, as we “hack” the natural environment, creating engineered environments that are optimized according to our own set of instructions without integration into the broader system they are a part of.
The next generation of technologies, what is called NBIC (Nanotechnology, Biotechnology, Information technology, and Cognitive science) will enable us to engineer our world on all levels and at all scales, from the molecular level to the planetary level, organic and inorganic and with digital manufacturing and the Internet of Things we are increasingly connecting all this up to information systems. This is vastly expanding our capacity to engineer our environment, as we are increasingly capable of engineering everything from the scale of an atom up to the global level through geoengineering. This takes us into a much more complex engineered environment, it also gives us greatly more power to manipulate and affect our environment.
We can only develop systems based upon our level of understanding to the world, when we try to get to the end faster, to progress without understanding the context; technology gets developed on one level, a single dimension, in a linear fashion. Because of this we don’t know what macro scale feedback loops we are affecting and the world becomes more uncertain and volatile. It is only through a systems-level view of the environment that we can understand the mechanisms preserving its stability, and how to progress in a sustainable way