Copyright (c) 2013 John L. Jerz

Dancing With Systems (Meadows, 2001)
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The Case for Using Probabilistic Knowledge in a Computer Chess Program (John L. Jerz)
Resilience in Man and Machine

 
[JLJ - If you have done any Systems Engineering, there is a powerful feeling you get when you are able to construct large systems and make them do what you want them to do. However, the devil is in the details, and these systems survive or fail according to the attention and management as they come into being. These rules or guidelines reflect one author's experience.]

Excerpts:
 
self-organizing, nonlinear, feedback systems are inherently unpredictable. They are not controllable. They are understandable only in the most general way. The goal of foreseeing the future exactly and preparing for it perfectly is unrealizable. The idea of making a complex system do just what you want it to do can be achieved only temporarily, at best. We can never fully understand our world, not in the way our reductionistic science has led us to expect. Our science itself, from quantum theory to the mathematics of chaos, leads us into irreducible uncertainty. For any objective other than the most trivial, we can't optimize; we don't even know what to optimize. We can't keep track of everything. We can't find a proper, sustainable relationship to nature, each other, or the institutions we create, if we try to do it from the role of omniscient conqueror.
 
the uncertainty exposed by systems thinking is hard to take. If you can't understand, predict, and control, what is there to do?
 
We can't control systems or figure them out. But we can dance with them!
 
I will summarize the most general "systems wisdom" I have absorbed from modeling complex systems and from hanging out with modelers. These are the take-home lessons, the concepts and practices that penetrate the discipline of systems so deeply that one begins, however imperfectly, to practice them not just in one's profession, but in all of life.
 

1. Get the beat.

Before you disturb the system in any way, watch how it behaves.

2. Listen to the wisdom of the system.

Aid and encourage the forces and structures that help the system run itself.

3. Expose your mental models to the open air.

Remember, always, that everything you know, and everything everyone knows, is only a model. Get your model out there where it can be shot at.

4. Stay humble. Stay a learner.

Systems thinking has taught me to trust my intuition more and my figuring-out rationality less, to lean on both as much as I can, but still to be prepared for surprises. Working with systems, on the computer, in nature, among people, in organizations, constantly reminds me of how incomplete my mental models are, how complex the world is, and how much I don't know.

The thing to do, when you don't know, is not to bluff and not to freeze, but to learn.

5. Honor and protect information.

A decision maker can't respond to information he or she doesn't have, can't respond accurately to information that is inaccurate, can't respond in a timely way to information that is late. I would guess that 99 percent of what goes wrong in systems goes wrong because of faulty or missing information.

6. Locate responsibility in the system.

Look for the ways the system creates its own behavior. Do pay attention to the triggering events, the outside influences that bring forth one kind of behavior from the system rather than another.

7. Make feedback policies for feedback systems.

a dynamic, self-adjusting system cannot be governed by a static, unbending policy. It's easier, more effective, and usually much cheaper to design policies that change depending on the state of the system. Especially where there are great uncertainties, the best policies not only contain feedback loops, but meta-feedback loops–loops that alter, correct, and expand loops. These are policies that design learning into the management process.

8. Pay attention to what is important, not just what is quantifiable.

Our culture, obsessed with numbers, has given us the idea that what we can measure is more important than what we can't measure... Don't be stopped by the "if you can't define it and measure it, I don't have to pay attention to it" ploy.

9. Go for the good of the whole.

Don't maximize parts of systems or subsystems while ignoring the whole. As Kenneth Boulding once said, Don't go to great trouble to optimize something that never should be done at all. Aim to enhance total systems properties, such as creativity, stability, diversity, resilience, and sustainability–whether they are easily measured or not.

10. Expand time horizons.

The official time horizon of industrial society doesn't extend beyond what will happen after the next election or beyond the payback period of current investments. The time horizon of most families still extends farther than that–through the lifetimes of children or grandchildren. Many Native American cultures actively spoke of and considered in their decisions the effects upon the seventh generation to come. The longer the operant time horizon, the better the chances for survival.

11. Expand thought horizons.

Defy the disciplines. In spite of what you majored in, or what the textbooks say, or what you think you're an expert at, follow a system wherever it leads. It will be sure to lead across traditional disciplinary lines. To understand that system, you will have to be able to learn from–while not being limited by–economists and chemists and psychologists and theologians. You will have to penetrate their jargons, integrate what they tell you, recognize what they can honestly see through their particular lenses, and discard the distortions that come from the narrowness and incompleteness of their lenses. They won't make it easy for you.

12. Expand the boundary of caring.

Living successfully in a world of complex systems means expanding not only time horizons and thought horizons; above all it means expanding the horizons of caring... The real system is interconnected.

13. Celebrate complexity.

Let's face it, the universe is messy. It is nonlinear, turbulent and chaotic. It is dynamic. It spends its time in transient behavior on its way to somewhere else, not in mathematically neat equilibria. It self-organizes and evolves. It creates diversity, not uniformity. That's what makes the world interesting, that's what makes it beautiful, and that's what makes it work.

14. Hold fast to the goal of goodness.

Don't weigh the bad news more heavily than the good. And keep standards absolute.

 

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