Systems Science 3 — Organization and Its Conceptualization
I can't think of another noun in the English language that gets so much mileage as the word 'thing'. It can act as a placeholder for essentially any kind of noun. For example:
- Object(s): That 'thing' over there.
- Idea: The 'thing' is...
- Relation: They have a good 'thing' going on.
- States: 'Things' looked grim.
- Quantification: Something, nothing, everything
In my series on sapience I indicated that one of the core aspects of sapient thinking is systems thinking. It is the basis, I claimed, for the construction of models of 'things' in the world, which are what we call knowledge. Those models are what we use to both recognize patterns in the world outside of our brains and to make anticipations about how those patterns will change in time. Patterns, in this sense, are a general category of all things that have some consistent internal structure and behave in consistent, usually causal, ways. My hunch is that the word 'thing' exists because the brain is hardwired to have a placeholder for all such patterns even if there is no need for a name for that pattern. That is language arises out of a built-in semantics that includes an automatic recognition of and tendency to organize the world into patterns. The world is comprised of many things.
The absence of pattern is chaos (in the vernacular sense), randomness, disorder, and disorganization. There is no system. And our minds do not deal with that state of affairs very well. So strongly are we compelled to see the world as organized that people see images in a scatter diagram of randomly placed dots. They see common things in the shapes of clouds.
So 'things' are identifiable and representable patterns. But what are patterns? For our purposes lets suppose there are two kinds of patterns we are interested in, one a spatial, the other temporal. By pattern we mean a stable arrangement of component things that are somehow bound together in space and time. The bounding may be obvious like an envelop or shell or box. Or it may be due to internal bindings on the components that prevent them from wandering too far off, like the planets in our solar system held by gravitational force. What makes these things patterns is that you can recognize the continuity from moment to moment. There are usually repeating themes (e.g. component type A is usually found next to component type B) based on various kinds of physical relations (e.g. 'next to'). Prepositions capture many of these relations.
A pattern exists when the thing has an internal organization that persists over time. Atoms bind to other atoms to form molecules. Molecules can interact with other molecules to form larger-scale structures. The components are organized by any of numerous forces and constraints to become a 'whole' object. This doesn't mean that the exact same components persist in the exact same relations for all time. What is important is that the pattern of organization persists even if individual components come and go. What persists is the information needed to describe the pattern! I will return to this aspect in a future post.
Organization is relevant over all scales of size and complexity. As noted before, a system is both composed of subsystems and is itself a subsystem of some larger system. "Greater fleas have lesser fleas upon their backs to bite-em. And so it goes, on and on, ad infinitum." (Johnathan Swift). There are logical and philosophical problems with 'ad infinitum' claims (see: Turtles all the way down!). There probably is some lower bound and upper bound (e.g., boundaries of the universe) limits to system composition, at least as far as technology enhanced human perception is concerned. But those boundaries are very fuzzy and whatever their status in some truly objective reality, they need not cloud the validity of the argument that systems are composed. Unity is a property that gives the sense of internal connectedness of all the components that make up a system. We see things as wholes. We are predisposed to observe boundaries that encapsulate 'things'. Boundaries might be cleanly observed, like skin or containers. Others might be inferred from the fact that all the parts of a thing seem to act in concert. An example of 'fuzzy' (vs. discrete) boundaries is found in things like ideas (concepts).
This is not to say that systems are always maximally organized internally. When we take a look at the evolution of systems we will delve into how systems start out essentially unorganized (or actually minimally organized) and progress through stages to maximal organization, provided energy is available to motivate the processes. Organization is not the same thing as order, though there is a deep connection. Order, in the physical sense, speaks to the rigidness and persistence of connections between components. A crystal is a highly ordered system, whereas a living cell is a highly organized system. If you were to reduce the thermal energy of a living cell, lower its temperature, without disrupting the molecular arrangements at or near absolute zero temperature the cell would have no internal activity; its chemical processes would be frozen in time. But it would have maximum order — you could, for example, predict with high confidence the position or momentum of molecules (the former fixed by freezing, the latter essentially zero!).
Many systems look similar to many other systems. They all have similar kinds of components, arranged in similar fashion. They behave similarly. If we dig deeply into their histories we find they have similar origins and developmental trajectories.
In large meta-systems many, seemingly disconnected, subsystems seem to be related. They can be recognized as similar patterns and our brains quite automatically form categories into which these are all fit. As we are learning, especially when young, we are quite good at generalizing (indeed very young children tend to over-generalize - everything round is a ball). This means we ignore variations in some of the details of a particular instance of a system relative to similar systems. Everything that looks like 'xyz' is an xyz. Only over time and multiple observations of specific xyzs where the previously minor differences become important do we particularize and individualize with attached significance and meaning.
It is incredibly wonderful that one subsystem, the brain, can form neural networks representing patterns, which in turn represent things, physical subsystems, in the world outside themselves. More wonderful still is the natural way in which the brain reuses circuitry to deal with so much diversity by forming categories or classes of things that have features in common. Of course brains aren't infallible, as when corals were first classified as plants (OK so corals harbor algae, you get the point). This is the crux of cognition. That a brain can construct an organized and efficient representation of things in the world as well as their interrelations and behaviors. Systems science is as much about cognitive neuroscience, the mind, and consciousness, as it is about the things themselves.
The world is not static, it isn't frozen. Things move and change. Along with capturing the essence of 'thingness' and categories of things, it is necessary to understand how the world is forever in flux. As long as energy flows, things will move, will interact with each other, sometimes in new ways, and will often decay or lose their unity status (decompose). Fortunately for us, the world is dynamic in an organized way! While individual interactions may have a stochastic (probabilistic) aspect, all interactions follow some laws or law-like principles that make it possible to make sense out of the dynamics. Making sense, in this sense, means being able to anticipate or predict outcomes of interactions and combining that with likelihood of the interactions occurring provide us with unprecedented opportunities to control the world. We can capture the essence of patterns in time and analyze these to extract laws of nature and law-like principles to use in commanding how the world moves, to our advantage. That is, after all, the objective of the sciences. Systems science is about the process of capture and the meta-laws governing the capturing of those laws.
There are different kinds of change that need to be understood. One, for example, is the simple flux in components mentioned above. The CHNOPS (carbon, hydrogen, nitrogen, oxygen, phosphorus, and sulfur) atoms in a living cell are constantly under flux, yet the pattern of structure remains. People in an organization can come and go, but the pattern of jobs persists. A second form of change is obvious dynamics — things move about under the laws of motion and thermodynamics. A third, much more subtle form of change is when something entirely new comes along that changes composition, dynamics, and behavior. A genetic mutation that leads to a new phenotype and possibly evolution of a new species is such a change. Any observing system, such as a human individual, lives in a world, an environment, where new things can and often do happen. The technical term for this is non-stationarity (meaning that one or more of the statistical properties of the system change over time). The two former types of change are, to an extent, predictable or can be anticipated. The third kind is what we mean by 'out of the blue'. By definition, it can't be anticipated. [Technically some kinds of non-stationarity have aspects which are predictable. For example a trend in, say, average behavior allows us, to some extent, to predict a future state of affairs of the system. What I am referring to here is when truly 'new' stuff happens.]
In conclusion, the world is organized in both time and space. Sometimes, as when the world was new, that organization is simple (I will be talking more about complexity in a future post). Sometimes, after time passes and energy flows, that organization becomes more complex and nuanced. Sometimes, complex systems age and fall apart. But one small subsystem in the world, the human brain, has itself evolved to capture the patterning in all kinds of organization. It recognizes systemness, categories of systems, and specific system instances. And it recognizes patterns of systems changing in time (or the disruption of a pattern as in the case of non-stationarity). Organization and conceptualization are like two mirrors reflecting each other. In future postings I will tackle the nature of information and knowledge as the mechanisms by which organization and conceptualization complement one another (epistemological principle), are indeed reflections of a unified underlying principle of existence (ontological principle).