Part 2 on What I Learned from "General Systems Thinking"

Welcome back. I want to continue my overview of Gerald Weinberg's "Introduction to General Systems Thinking". I thought that I could shorten the discussion and fit the rest of the book into one more post. But, the more that I re-read the book, the more that I found to talk about! So, I am going to continue my ramblings and discuss Chapters 3 and 5, building on my previous post.

Chapter 3 is all about "System and Illusion" (that is its title!). It starts by asserting that a "system is a way of looking at the world". Obviously, how we look at something influences what we see. And, after we have looked at something, we can try to write it down/produce a model that describes the thing (describes that piece of the world).

We have lots of ways of looking at the world, and lots of models that reflect our different perspectives. But, these models won't all agree. It is important to remember that even if models don't disagree, each one may be totally valid (since it is defined from a unique perspective). Wow ... how do we do anything with that?

Well, we start by acknowledging that the problem exists and not get into religious wars about why "my model is better than your model" (or substitute the word, "ontology" for "model"). We need to understand the systems/models/ontologies and look at the perspectives behind why and how they were designed. When I have done this in the past, I saw things that I missed because I lacked certain perspectives. I also saw things that I did not need to worry about (at a particular point in time), but felt that I might need later. And, if I did need them later, how would I incorporate them? The last thing that I wanted was to paint myself into a corner.

So, what do we need to consider? Systems in the world of "general systems thinking" are sets of things. The entities in the sets vary by perspective. For an example, consider a candy bar. In a system that is concerned with eating, the candy bar may be broken into chunks of certain size and weight. And, you may be worried about the size of your chunk. But, in a system that is concerned with the chemical components of the candy bar, the size of the pieces doesn't matter at all. The constituent molecules and their combination are everything.

Hall and Fagen in their paper, "Definition of Systems" (1968) state that:

A system is a set of objects together with relationships between the objects and between their attributes.

That sounds a lot like an ontology. But, in defining the objects and their relationships, be careful. Don't be limited by how you write your model. Often, we get tangled up in our notations and limit our thinking to what we can express. For example, we say "I can express xyz with XML, or abc with OWL, or mno with UML. So, that is all that I can do." Indeed, we will always be limited by our notation, but our thinking should not be. This is one of the general cautions or principles that Weinberg highlights:

The Principle of Indifference: Laws should not depend on a particular choice of notation.

Unfortunately, Weinberg later turns around (in Chapter 5) and states that reality is quite different than what we want or what should happen (remember that there will always be exceptions to our laws and principles :-). Reality is never fully perceived, and our abstractions may be flawed since "the limited mental powers of the observers influence the observations that they make". That leads us to another principle:

The Principle of Difference: Laws should not depend on a particular set of symbols, but they usually do.

We get involved in our own symbols and notation. In fact, we may be agreeing on perspective and modeling the same system with the same components as someone else. But, we won't realize it, because we can't see past our notation.

So, let's take a step back and try to look at a system from many perspectives, and understand the semantics independent of the notation. We need to look at the system broadly enough to understand its scope, and then try to "get a minimal view" ("one that lumps together [information that is] ... unnecessarily discriminated"). But, when we simplify (or minimalize), we need to feel that our model is "satisfying", that it conforms to what we know of the world, its past behaviors and our past experiences. Weinberg calls this his "Axiom of Experience".

Buckminster Fuller put it more eloquently, I think ...

When I am working on a problem, I never think about beauty. I think only how to solve the problem. But when I have finished, if the solution is not beautiful, I know it is wrong.

Andrea