Capitalism arose on an industrial base characterized by machinery. The development of machinery was both a result of and an influence towards a mechanical theory that began with the immense scientific discoveries of Isaac Newton in England in the 1600s.
Thus mechanical thinking became anointed with wondrous powers. It certainly could make far more accurate and certain predictions than any other school of thought. Newton proved the famous "Two-Body Problem": if you know the original the position, direction and velocity of two interacting balls or objects, you can predict their position at any moment infinitely into the future. The power of this method enthroned a mechanical system of science that prevails to this day.
Calculus was one of Newton's great discoveries (actually discovered independently by Leibnitz at the same time). Calculus is a mathematical discipline of measuring smooth, continuous, regular, linear systems. Calculus studies "linear" relationships, where variables can be plotted against each other as a straight line.
If you are heating water, for example, a small increase in heat produces a small increase in temperature. A large increase in heat produces a larger increase in temperature. Therefore by adding the small increases together you can accurately make a larger prediction about how a system will behave. Calculus represents, by far, the most powerful mathematical tool humans have devised, with successes in almost every field of scientific and technical endeavor.
The limits of this method result from the fact that Nature is not always - in fact, not usually - linear, smooth or continuous. For the most part, things and processes are jerky, interrupted, irregular, complex, and dynamic They really aren't linear at all; instead they are "non-linear".
You are heating water and the temperature changes degree by degree Ö97, 98, 99. Suddenly at 100oC something qualitatively different happens. The nature of the process completely changes. The water changes its physical state and turns to steam. What's more, no matter how much heat you now add, no matter how high the flame, the water's temperature will no longer increase. It will stay at 100oC until all the water is gone.
Suddenly a small, incremental, quantitative input no longer produces a small, incremental, quantitative output. Instead it produces a qualitative change - a disproportionately leaping change in behavior and completely destabilizes the system.
Two hundred years later after Newton, by the beginning of the 20th Century, the limits of mechanical thinking were becoming increasingly clear. The criticism of mechanical thinking began with the development of dialectical materialism by Marx and Engels in the mid 19th Century. If you add a ball to the Two-Ball Problem and make it a "Three Ball Problem", suddenly its impossible to make predictions, even after a little time had elapsed. This defines a very simple system with only three variables. Science began to encounter other phenomena that could not be approached with mechanical thinking.
In fact, most things are complex dynamic systems. They are ubiquitous. Such systems include how snowflakes form, combustion, how caterpillars become butterflies, biological evolution in general, or problems of large populations of organisms. Whether rivers, melted steel, the weather or economies - there are universal patterns to how flow, develop and change. By addressing such issues, modern science finds itself on the doorstep of dialectics in spite of itself, since it has pretended for 150 years that the science of change doesn't exist.
I. Complex Systems
What features of such systems are currently under study?
"Complex" refers to both the organization and the behavior of such systems. Mechanical systems are usually quite simple: each part has a regular function which it does every time. Turn the key of our car and the car will start - or it won't, if there is mechanical failure.
Complex systems have interacting processes made of interacting parts which change, adjust and interact upon one another. Think of a basketball team. A given part, or player, doesn't always behave in predictable ways. The behaviors are complex and the interactions are complex. Such a range of behaviors often make such systems globally stable, but locally unstable and in flux.
Think of a rainforest. There is nothing more chaotic, yet the incredibly complex interactions of species and individuals actually keep the rainforest stable. Local instability also allows organisms to adapt to local conditions.
Think of New York City. The city is made of over 12 million human beings. As component parts, they engage in daily flows and many varieties of aggregate behaviors. Yet its still New York. (This is quite similar to the millions of red blood cells flowing through your blood vessels at this moment), The whole is greater than the sum of its parts. One amazing characteristic of complex systems is that a very few, simple rules - once interacting - produce and explain an astounding complexity of behaviors.
Complex systems are self-organizing. They are driven by internal developments and are not simply the result of external forces. The development of a chicken in an egg, a hurricane, or even a raindrop, are self-organizing systems. Such systems exhibit new qualities that emerge as development continues.
Complex systems thus are dynamic, rather than stable or regular. Their behavior Anyone who has tried to pour catsup out of the bottle is familiar with such complex behavior. It just doesn't act right. It is irregular and unpredictable. The internal dynamism generates a history, since their behavior changes over time.
Modern computing power is providing some of the first tools scientists have found to begin to study such complexities. By analyzing processes as varied as the boom and bust of locust populations over the years, leaky faucets, forest fires or how oil seeps through rocks, etc., scientists are beginning to pose larger questions:
How do a few, simple laws lead to such an intricacy of structures, processes and behaviors? How does randomness at one level (for example, the micro level of atoms and molecules) lead to order at another level (the macro level of the human body)? What are the universal characteristics of such systems? Why are such systems so common? What is emergent behavior? How is self-development a result of self-organization?
These are all questions, though phrased differently, that the science of dialectics has studied for over 150 years.
II. The "Butterfly Effect"
One central question that modern science is studying is known as "the butterfly effect". Everyone gets frustrated by weather predictions. The weatherperson says that it will be sunny tomorrow, but there's a sudden storm or a fog. Why can't they just get it right?
Studies of dynamic systems have proven that it is simply impossible to predict the weather more than a few days ahead. Sure we know its winter - and that means we can expect certain general things about the weather - but what weather will specifically occur can only be guessed at. This unpredictability is a due to the fact that the weather is the result of a huge number of variables. If one changes, the whole thing can change. This is referred to as "the butterfly effect" because a butterfly flapping its wings in China can set off a series of changes which can cause a storm in Chicago (where, as we all know, it sometimes gets to be 60oF in February)
This is one way that modern science approaches the dialectical question of the Leap - the point where a quantitative change triggers a leap into a change in quality. What causes a disease to suddenly spread and become an outbreak? There's no master cell in an embryo, so how can it possible have coordinated development? How do you understand September 11 if you don't understand what was happening on September 10? At what point did that sweet child of yours become a surly, combative, independent-minded teenager? These questions simply don't admit simple, mechanical answers. They require, as Lenin said, the concrete analysis of concrete conditions.
Scientists use a variety of terms to describe this dialectical moment. "Phase change" refers to qualitative leaps, since chemistry has shown that water makes a phase change at 100oC, as it boils, to become a gas. Another term is "bifurcation point". Here they mean that the behavior of a dynamic system follows a certain pattern up to a certain point. At that point, when the butterfly flaps its wings, the behavior changes. Often it bifurcates - or splits into two - where one of two types of behavior become possible. Often there is a temporary period where the behaviors oscillate back and forth before the qualitative leap takes over.
Explaining the "3 Ball Problem" (mentioned earlier), scientists often say that "the system is sensitive to initial conditions". Alter the push on one ball by a tiny amount and the system will become qualitatively different. The same is true of two balls that are thrown into a river. They may float together for a long time, but when the water gets turbulent, their positions will change drastically due to the tiny initial differences in the current and the waves around each one.
Dynamic systems are nonlinear - a small change (like the butterfly's wings) produces a huge, unpredictable, qualitative change. This doesn't always happen, of course, for if it did, the system would be linear. Such changes occur only at certain critical points - bifurcation points or nodal points - that characterize the Leap.
Scientists, economists, and militarists are currently excited by the possibility of finding these critical points. If you could predict exactly where and when the system would leap into a different quality, you would "gain leverage" over the system. At what point, for example, should the Federal Reserve adjust interests rates to keep the cyclical crisis of capitalism at bay? At what point in warfare can you radically transform the situation with a specific military strike? If you knew these "bifurcation points", you could begin to predict and to control the process. The Pentagon is examining these concepts because they suggest new ways to wage war.
Studies of simpler systems, such as how weather changes affect vegetation, which in turn, influences the deer population, reveal some small breakthroughs in this direction. Dynamic systems are an interrelation of dynamically changing parts or processes. The regularity of the overall system is determined by feedback loops that link the component processes.
Feedback loops are how two systems couple together. For example, you eat a big breakfast. Suddenly your blood sugar level goes above a certain level. Cells in your pancreas detect the qualititative difference. They signal other cells in the pancreas to release insulin. Insulin is a protein that bonds to the surface of each cell in your body. Insulin then tells the cell to open its cell membrane so that sugar goes in. This step causes the blood sugar to fall. When it reaches a certain point, the detector cells tell the insulin-releasing cells to stop releasing insulin.
Feedback occurs with the message from the sugar level to the detector cell. The message from the detector cell to the insulin-releasing cell is more feedback. The feedback keeps the blood sugar within an acceptable range. Too little sugar quantitatively and you pass out - definitely a qualitative leap. Too much sugar and you not only get a little hyper, but your cells begin to be destroyed. That specific condition - hyperglycemia - is what causes the damage in the disease diabetes.
Positive feedback loops amplify. Our language contains lots of references to amplifying cycles: "self-fulfilling prophecies", "the snowball effect", "vicious circles" and "juming on the bandwagon". The "rich getting richer" is a positive feedback loop, just as "the poor getting poorer". In the stock market we know that "momentum is everything" when "its on a roll", but we get worried when we see "the rats jump off the sinking ship".
Negative feedback loops regulate. Such feedback systems maintain communication between the parts and quantitatively stabilize the system within qualitative limits. Often itís the regulating structures than balance the process so that it doesn't "runaway with itself" and "begin a meltdown". When problems appear, pushing harder on the same old levers often just makes the resistance stronger. There is interesting research on how handling the limits keep the structure under control.
In an organism, or in dynamic systems generals, myriad feedback loops are hooked together in such a way that its internal organization can continuously adjust to the demands of its environment. Scientists are exploring ways to control quantity and quality by focusing on feedback systems.
Sometimes breaking these feedback loops trigger qualitative changes. At other moments coupling certain processes together to make a system more regular and prevent qualitative changes from happening.
Dynamic systems, with their complex behaviors, pose qualitatively new and different problems. Often these systems generate too much information. All their nonlinear forms - the leaps, wiggles, jerks, starts and stops - make traditional quantitative analysis impossible. Such systems simply aren't predictable in the traditional sense. Scientists, economists, generals and CEOs are attempting to develop different methods to determine how a system will change.
Trying to get all the data, attempting to quantify everything or analyze every chain of causality often proves impossible and fruitless. Rather scientists are beginning to look for templates to identify the objective patterns that control events. They seek the nodes where feedback loops join. Then they tweak the system here and there, in various ways, playing with the variables to learn more about the systems critical points where a little leverage (a little quantitative input) controls its qualitative leaps.
III. Dialectical Materialism
Early in the last century, Lenin pointed out that materialism had essentially won the day and that idealism was no longer the principal theoretical problem. The primary limit to real comprehension was then and remains today the anti-theoretical, narrow, mechanical materialism of those who caught only a glimmer of how to proceed.
In describing the art and science of dialectics, Lenin referred to an old Russian game. A group of people would take a long chain and toss it onto the ground in a pile. Then someone drew a line in the ground at some distance from the chain. The challenge was to determine the "key link". This was the single link, which, if you grabbed it and pulled, both ends of the chain would cross the line at the same time. This was the central link in the chain, the one that guaranteed the quality.
Lenin used the concept of the key link to criticize mechanical materialism. The science of dynamic systems has yielded some important ideas, yet, as the discussion of "leverage" above shows, it is generally mired in a mechanical, non-dialectical approach. The clearest thinkers among modern scientists recognize the struggle for theory is a critical and excitingtask.
"Simplicity achieved by idealized isolation of systems and variables within systems, deterministic laws, clearly delineated boundaries, linear causal trains, and other tools with which to forge analytical prediction have become the hallmarks of good theory. By using such techniques, rooted in the parsimonious and deductive power of logic, we have searched for - and therefore overwhelmingly found - static equilibria, consistent explanations, periodic regularities and the beauty of symmetry.
"Of course, as Ian Stewart noted, all this comes at a price, namely the restriction of our vision to low-amplitude vibrations, shallow waves, small perturbations and their analogs. We have trained our imaginations to be fundamentally linear. " Alan D, Beyerchen. "Clauswitz, Nonlinearity and the Unpredictability of War" (p 16 of van Creveld, below))
If dynamic systems are universal, and mechanical ones are relatively scarce, then it follows that mechanical concepts must be subordinate to dialectical ones, not the other way around. Real theory is never a passive description of reality. It is a tool, a necessary framework, a method for intervention.
Without a full comprehension of dialectics, developing a systematic approach to the complexity of reality is impossible. This means applying the full scope of dialectical conceptions, including such questions as:
How is the system in motion? What are the contradictory opposites that drive the system? What are the internal contradictions? What stage of development is it at? How does it interpenetrate with other processes? How does it influence its environment and vice-versa? How precisely do quantity and quality interact within the system? What is arising and developing, what is decaying and dieing away?
[draft by Steven Miller, Oakland, Jan, 2002]
Good Reading on these topics:
Briggs & Peat. Turbulent Mirror. 1989 (The best book available on these issues. A very readable, excellent book on non-linear, complex systems.)
James Gleick. Chaos. 1987 (The first popular book on this revolution in science. Still quite good.)
Peter M Senge. The Fifth Discipline. 1990 (This is the book that defined the structure and organizational issues for the corporation in the Information Age. An absolutely essential book to read for anyone interested on feedback, vision, values formation, organization etc)
Martin van Creveld. Coping With the Bounds: Speculation on Nonlinearity in Military Affairs. October, 2001. http://www.dodccrp.org/copfor.htm (van Creveld was one of the theorists who have crafted the reorganization of the US Military into a force designed to aggressively use violence to control low-level, prolonged, domestic conflict - the form of warfare they expect to see in this century)
Kevin Kelly. New Rules for the New Economy. 1998. (Kelly uses non-linear complexity and biological metaphors to establish principles for organizations)
