Scientific Ideas and Education in the 21st Century

Ash Hartwell
http://21learn.org/arch/articles/ash_complexity.html

Abstract
The dominant metaphor for nature and society during the 18th-20th centuries has been mechanical. Our schools today reflect a Newtonian, positivist world view.
Schooling is the most conservative of social institutions. It takes about 100 years for scientific theories and ideas to affect the content, processes, and structure of schooling. But the pace of change accelerates. The 20th century has produced a radical shift in scientific concepts of nature, reality, and epistemology: relativity theory, quantum mechanics, the discovery of DNA and, since mid-century, the development of theories of chaos and complexity. While the popular concept of reality in the 20th century has been mechanical, the metaphor for the 21st century is likely to be organic. Public schools have not yet reflected this shift.
Every historical period believes itself to be at the pivot of turbulent change. At the dawn of the 21st century we have an especially strong claim to this position. It is evident that recent shifts in our knowledge of nature and ourselves, our ways of knowing, and our technology are rapidly transforming the way we live and learn.
One key current scientific idea, emerging from research into what are described as complex adaptive systems, is that human learning is the leading edge of the evolutionary process. This suggests that a concern for learning is likely to become central to our concepts of social development and this will accelerate the transformation of what has been known as the school into a more responsive educational environment.
Education and Positivism
"The belief in the instrumental power of reason and its corollary emphasis on scientific knowledge as the paradigm of understanding is firmly rooted in our bureaucracies and corporations...Scientifically informed, if not scientifically managed, social control is the ideal to which we aspire. It is the ground for our conception of planned change, our models of knowledge production, dissemination and utilization. (Schwand, 1989)
Our contemporary concepts and practice in politics, organizational change, and development assistance are defined for the most part by an intellectual framework that began with the development of physical mechanics in the seventeenth century. We speak of the machinery of government, re-engineering institutions, and the inputs, processes, and outputs for instructional systems.
The industrial age was built upon the theories that pictured the entire universe as a machine. The image of a uniform, mechanical, and ultimately predictable universe not only shaped the development of science and technology, it became the dominant metaphor in politics, economics, organizations and education. (Toffler in Prigogene 1984). The American Constitution regulated political forces with checks and balances, striving for equilibrium; economic theory strove to analyze trends, develop input-output matrices, and to bring the economic system into equilibrium; organizations were studied by the science of 'industrial engineering,' which analyzes the system to improve efficiency and fine tune operations. Within the development field, the education sector is analyzed by economists for rates of return, which drives the current argument for higher investments in girls' schooling. Education is described as an input-output-outcome system which good policy can make more efficient (Windham, 1990).
Positivism is the belief that science and the scientific method can ultimately fully understand physical reality, and use that understanding to predict and guide the future. This presumption led Laplace to his famous claim that, given enough facts, we could not merely predict the future but retrodict the past. (Toffler in Prigogene 1984 p.xiii). The spread of positivism was a pragmatic response to the remarkable success in the application of science for the invention of new technologies. It was this technology, applied to production, transportation and warfare that made Europe and America dominant world powers into twentieth century.
The University of Berlin, founded in 1810, established a model of what became the most successful and widely copied national system of higher education. By the mid-nineteenth century the modern, secular university had largely displaced traditional universities which were founded by religious orders, staffed and led by clergy, and had the central mission of preparing churchmen. By the end of the nineteenth century the establishment of secular education systems, emphasizing scientific, engineering and agricultural knowledge, was seen by leaders as an essential national strategy. Newly independent countries, first in South America and Asia, later in Africa sought to replicate this strategy, and placed a significant proportion of state resources into scientific and technical secondary and higher education.
Although there is a rich and continuing history of alternative schools and experiments with constructivist learning (Brook, 1993), these movements are on the periphery. The mainstream public schools in America, in Europe, in the East, and certainly in the Third World, are remarkable in their structural similarity: graded classes and annual promotions; trained, certified teachers; standard texts for a curriculum based on discrete subjects; and national examinations to certify and select. The shape and feel of the formal school makes it unmistakable, wherever one is in the world.
Universally, schools teach language, mathematics, science, social studies, and cultural/religious studies, with a few periods for 'practical' crafts and physical education. Science and mathematics are almost entirely devoted to pre-twentieth century concepts and models. They are considered the most academically rigorous of subjects, and are given the greatest intellectual prestige, particularly in the third world.
In this chapter we are not so much interested in the details of this history as in the ideological, epistemological framework which has defined the structure and content of formal education in the twentieth century. Schools teach and reinforce by their structure and method a positivist, secular version of reality. Yet, virtually all the positivist assumptions have been transformed by twentieth century scientific ideas: the theory of relativity, quantum mechanics, the Heisenberg uncertainty principle, Godel's theorem, information processing, chaos theory, and most recently the theory of complex adaptive systems.
The schools and universities are as yet little affected by these radical ideas. It is said that education is the most conservative social institution, the last to change in response to a new world of thought and practice. In this chapter we will sketch contemporary scientific theories of nature, reality, and epistemology, examine how these ideas are beginning to influence social practices, and speculate on what they might mean for education in the twenty-first century.
Newton's Science
Within one hundred and fifty years, from 1750 to 1900, capitalism and technology conquered the globe and created a world civilization...This transformation was driven by a radical change in the meaning of knowledge. (Drucker. 1993, p.19)
How has the positivist, Newtonian world view gained such a hold on our thinking, our institutions, our schools? We are so imbued with the mechanical metaphor, it so permeates our language and analysis, that it is hardly noticed.
The power of the positivist world view began with Galileo's challenge to established church authority and epistemology, when he asserted that empiricism and the Copernican displacement of earth from the center of creation should reconstruct our view of nature and reality. With Newton, who believed that the foundations of his laws could be applied to problems in moral philosophy, the metaphor for social and political reality was transformed from the great Chain of Being into mechanics (Zohar and Marshall, 1985, p. 23).
The scope and simplicity of Newton's laws, and their evident power to explain the world and produce technology, provided the dominant metaphor for the most influential social, political, and economic thinkers of the eighteenth and nineteenth centuries. The Newtonian model of the universe was applied to new fields and disseminated successfully, not just because of its scientific power or "rightness," but also because an emergent industrial society provided a particularly receptive environment for it.
Where Newton formulated the fundamental laws of physical reality, philosophers and social thinkers hoped to discover basic principles of social life. Descartes sketched an outline of a mechanistic approach to biology, psychology and medicine. Locke's philosophy was informed by the belief that there was a rational basis for the solution to human problems, "that there were laws of nature governing human society similar to governing the physical universe. As the atoms in a gas would establish a balanced state, so human individuals would settle down in a society in a 'state of nature.' Thus function of government was not to impose its will on the people, but rather to discover and enforce the natural laws that existed before any government was formed." (Capra , 1982, pp. 68-69).
Schwartz and Ogilvy describe the Newtonian world view as 'holding that matter consists of very small particles that are assembled into larger and larger complexes...if we knew the masses, positions, and velocities of all the particles we could predict the future from the laws of physics.' (Lincoln and Guba 1985, p.21). Political thinkers compared the colliding atoms and their interacting forces to the behavior and interactions of individuals and institutions in society, confronting each other in pursuit of their self-interest. (Zohar and Marshall, 1995, pp. 26-27).
The central ideas of the positivist position include:
There is an absolute, unchanging and certain reality. In principle, the universe is fixed, predictable, and law-abiding. Ambiguity or indeterminacy is a reflection of lack of information or lack of good theory.
There is one perspective in explaining reality. In Newtonian physics there is one absolute space-time framework. Reality is hard: a statement is either true or false, a strategy or plan is either good or bad. Nuance, paradox, multiplicity of perspective and meaning is not accommodated.
The universe is a hierarchy, with atoms the ultimate reality, the building blocks of molecules, which define cells and organisms. We structure power and organization in the same ladder of ascending and descending authority.
The universe is composed of isolated, separate, and interchangeable physical parts. The individual atoms and forces acting between them can explain physical reality.
Man's consciousness stands outside the physical world. We get at the secrets of nature through objective investigation undistorted by unique perspectives or values. Nature is perceived to be 'other' than ourselves, to be conquered and used.
Each of these ideas has been found wanting in the theory and practice of nineteenth, and more radically, of twentieth century science. Nonetheless, they continue to provide the ground of our common metaphors and concepts, and are particularly evident in the structure, process and content of schooling.
Electromagnetism, Evolution and Thermodynamics
The major scientific ideas developed in the nineteenth century built on the Newtonian model of the universe, while introducing new discoveries and ways of thinking that led to the radically different concepts of the twentieth century. The discovery of the electro-magnetic force field introduced the concept of fields independent of material bodies. The theory of electrodynamics culminated in the realization that light was a rapidly alternating electromagnetic field traveling through space in the form of waves. (Capra, 1982, p. 70).
Two other theories introduced the concept of irreversible change into scientific thinking, in what appeared to be contradictory interpretations. Geologists saw the universe, and the earth within it, as the outcome of an evolutionary process.
"The discovery of evolution in biology forced scientists to abandon the Cartesian conception of the world as a machine that had emerged fully constructed from the hands of its Creator. Instead, the universe had to be pictured as an evolving and ever changing system in which complex structures developed from simpler forms." (Capra, 1982, p.72).
The theory of evolution was radical in its challenge to religious thought and history, yet it presented an "overwhelming mass of evidence in favor of biological evolution, establishing the phenomenon for scientists beyond doubt" (Capra, 1982, p. 72). Darwin proposed the combination of random mutation and selection of the fittest as the mechanisms by which evolutionary change occurred. Evolution provided a new metaphor to philosophy and social science, and was central in the thinking of Kant, Hegel, Marx, and Spenser.
While in biology evolution showed a historical movement towards increasing order and complexity, the Second Law of Thermodynamics showed that energy within closed systems dissipates, proceeding spontaneously in the direction of ever-increasing disorder. The new concept of entropy quantified the evolution of a closed physical system towards randomness. This result seemed to be at odds with biological evolution, and has led to the analysis of open, ordered systems in the twentieth century; what Prigogene calls dissipative structures (Prigogene, 1986).
Although the three central nineteenth century scientific concepts of electrodynamics, biological evolution and thermodynamics went beyond the simple, timeless mechanical model of Newtonian physics, the basic ideas of the mechanical world view remained firmly in place. The rapid growth of public schools and the secular universities in this century expanded and entrenched the positivist world view first in Europe and America, and later into the colonies. Of the three central scientific concepts of the nineteenth century, biological evolution was the least integrated into the school curriculum. Even today it continues to provoke controversy in American school districts, attacked by religious conservatives. It has been generally neglected in school and university curricula in much of the rest of the world.
Relativity and Quantum Theory
"Today there is a wide measure of agreement...that the stream of knowledge is heading towards a non-mechanical reality: the universe begins to look more like a great thought than a great machine." J. Jeans (The Mysterious Universe. 1930).
During the twentieth century Einstein's Special Theory of Relativity, followed by quantum theory, Heisenberg's uncertainty principle, the decoding of DNA, and the development of Chaos and Complexity theories, have freed science of the convictions that the world is simple, material, predictable, and governed by universal mechanical laws.
Who would have expected that most if not all, elementary particles would prove unstable? Who would have expected that with the experimental confirmation of an expanding universe, arising from a time without time, a place without space, all of the vast cosmos, galaxies, starts, planets and life itself would continue to form?
Relativity theory overturned the classical axiom that science is objective. It required scientific description must be explicitly related to the perspective, and the tools, of an observer who belongs to the reality s/he describes. Relativity also leads to the remarkable conclusion that we cannot define the absolute simultaneity of two distant events: simultaneity can only be defined in terms of a given reference frame.
Quantum mechanics went further to undermine the foundations of the classical scientific view of nature and reality. Like many other developments in modern science, quantum theory responded to specific expert conundrums, and its profound philosophic implications were realized long after it was conceived. In this it followed the Copernican revolution so well described by Kuhn (1970). Einstein, and later Bohr, Heisenberg and others built on the work of Max Planck to create a revolutionary concept: the wave - particle duality of light. Light has no ultimate singular reality, it can be understood to be a wave or a particle, depending on the purpose and tools of the observer.
Quantum theory establishes that there is no final material base on which the world is built: the "stuff" of nature is created through a dance of ever changing particles, described now by the "Standard Model" built from quarks with fanciful named properties such as "charm" and "beauty" (Giancolli, 1991). Rather than fixed, solid particles forming the base of our reality, the new physics sees dynamic patterned movement and energy. The proposition that reality is not material and that mass is a particular form of energy is expressed in the familiar equation which captures the essence of the new science, e=mc2, energy is equivalent to mass times the square of the speed of light.
Quantum theory asserts that subatomic particles are not isolated grains of matter but are probability patterns, interconnections in an inseparable cosmic web that includes the human observer. In modern physics, the image of the universe as a machine has been transcended by a view of it as one indivisible, dynamic whole whose parts are essentially interrelated and can be understood only as patterns of a cosmic process. (Capra, 1982, pp. 91-92). This concept changes our relationship to nature, and our scientific epistemology.
The theoretical and methodological findings of relativity and quantum theory have had enormously important practical applications. The most startling was the atomic bomb and the development of nuclear power. More recently the development of the laser beam and the microchip are redefining our technological environment. While our consciousness of nature and reality remain, for the most part, wedded to the concept of a mechanical universe, the technical applications of the new science are based on radically different notions of reality.
It is remarkable that in the seventy years since relativity and quantum theory created a conceptual revolution within the scientific and intellectual community, these ideas have had little impact on our perception of ourselves, our society or the world around us. Numerous attempts have been made to impress the radical new concepts of science and reality on the public. An early, insightful interpreter was Whitehead (1967) who built a new metaphysics based on a dynamic universe defined by energy fields rather than brute matter. Recently Capra in The Tao of Physics (1975), and Zukav in The Dancing Wu Li Masters (1979) have tried to explain in vivid terms the concepts and implications of relativity and quantum theory to the general public, contrasting them with positivist thought. Zohar and Marshal in Quantum Society (1995) develop a vision of social functioning based on the new view of reality. Yet it is only very recently that these concepts have begun to have an impact on social theory and practice (Capra , 1982. Lincoln & Guba, 1985. Roszak, 1992. Ray & Pinzler, 1993).
The schools in Europe and America have only recently introduced these subjects into the science curriculum. The stated goal of a physics textbook at a prestigious private school in Washington, DC is "to give students a thorough understanding of the basic concepts of physics." (Giancolli, 1991. p. xi). Yet less than 10% of the text is devoted to relativity and quantum mechanics, and there are no references whatsoever to dissipative structures, or complex adaptive systems.
Chaos and Complexity
Relativity and Quantum theory, however radical in relation to the Newtonian world view, have become orthodoxy in the scientific community. Their translation into powerful technology such as nuclear power, the laser and microchip provide society with persuasive evidence however strange, these ideas work.
Complexity theory is a new set of ideas related to order, evolution, social systems and learning emerging in the second half of the twentieth century. Drawing on the tool of computer modeling, and engaging mathematicians, biologists, physicists and economists, complexity is controversial in the scientific community (Horgan, 1995), although already significant technical applications are emerging (Brown, 1995).
Dissipative Structures
The famous law of increase of entropy describes the world as evolving from order to disorder; still, biological or social evolution shows us the complex emerging from the simple. How is this possible? How can structure arise from disorder? (Prigogene, 1986, p. xxix.)
Ilya Prigogene is a physicist who was bothered by the contradiction between the Second Law of thermodynamics - which held that the universe was moving toward entropy, it was running down - and the evidence of evolution, which indicated that at least this part of the universe is marked by increasing order and structure. "While some parts of the universe may operate like machines, these are closed systems, and closed systems form only a small part of the physical universe. Most phenomena of interest to us are, in fact, open systems, exchanging energy or matter [and, one might add, information] with their environment." (Prigogene, 1986). It is clear that biological and social systems are open, which means that the attempt to understand them in mechanistic terms is doomed to failure.
Prigogene argues that systems in disequilibrium can produce new structures spontaneously through a process of "self-organization." Examples of this are the whirlpool, the tornado, and the process of crystallization. These systems draw energy from their environment and in creating order dissipate entropy. Prigogene received the Nobel Prize for Science for his investigation of what he called dissipative structures. A dissipative structure captures energy and exhibits order, a characteristic of systems throughout the universe, but in particular of life forms. Prigogene's insight that open systems evolve and that it is only closed systems that move to entropy reconciles the contradiction between the Second Law and evolution.
The reason that the Second Law of thermodynamics isn't universally applicable is that systems are not isolated, but interact with sources of external energy. Take the simple example of a pot of soup beginning to boil. This is a patterned response to energy - the liquid has acquired structure. These self-organizing structures are ubiquitous in nature. A laser is a self-organizing system where photons spontaneously group themselves into a single beam. Mathematically self-organization is expressed as self-reinforcement and self-iteration in which small effects become magnified when conditions are right. (Waldrop, 1993).
Chaos Theory
By the mid-1970s computers began to provide scientists an investigative tool for exploring a new set of phenomena. Similar in impact, but far more powerful than the telescope or microscope, it has opened new methods and perspectives. What mathematicians and computer-literate scientists began to explore was a remarkable set of interactions built out of electronic signals, dancing patterns of 0s and 1s. A continuing debate about computer simulation is whether it is truly a means to discover "real" patterns in nature, or a kind of mind game of human creators, which bears some similarity to natural phenomena.
The mathematical, computational base of what has come to be called Chaos Theory illustrates the problem. Among other mathematical discoveries in the Theory of Chaos are fractals, bifurcations and strange attractors (Gleik, 1988). Each of these phenomena are described very precisely in mathematical terms and are seen in the now familiar graphics of the Mandelbrot set and its progeny. Chaos provides a framework for understanding irregular or erratic fluctuations in nature. Evidence of chaos occurs in models and experiments describing convection and mixing in fluids, in wave motion, in oscillating chemical reactions, and in electrical currents in semiconductors. It is found in the dynamics of animal populations and of medical disorders such as heart arrhythmias and epileptic seizures.
The mathematics of Chaos can, perhaps, be best entered through the experience of James Yorke, a mathematician studying population dynamics. Ecologists, trying to find a function which would represent the growth of a particular population, needed to build in a limiting term, restraining growth when the population becomes too large. The function selected was X(next) <ÛRX (1-X), where X is the population size (use a figure between 0 and 1 - representing 0 to 1,000), and R is the periodic rate of growth. You can see if x =.5 at the outset (population of 500), and R = 2 [percent growth rate], then X(next), the first generation, Will be 2 * .5 *(1 - .5) = .5, or 500. In other words at a 2 percent growth rate, the population is in equilibrium and static.
At a 1 percent growth rate the population slowly declines, finally fading out altogether after about 100 generations. At 1.5% the population declines until it reaches 333 and stays there. At 2.5% the population grows to 600 by the third generation, and then stays at that level. At about 3% something strange happens: the population doesn't stabilize, it jumps around to different values for about 40 generations, and finally oscillates between 689 and 643 for every subsequent generation. This is called by mathematicians a bifurcation. At 3.5 the pattern bifurcates again, with the population oscillating between four values. At 3.75 the figures swing wildly and unpredictably in a chaotic pattern, and at 4.0, the population swells in one generation to a 1000, and that wipes it out (this is the case where a population grows so fast that it overpowers its supporting environment - too many deer for the forest).
The definition of the onset of Chaos is where the oscillations become unpredictable, where it becomes impossible to predict the next value from a prior pattern. Whatever the starting size of the population, it is the growth rate that is critical in determining the pattern of change. Between a growth rate of 3% and 4% growing complexity turns into chaos. Michael Feigenbaum predicted that at the critical point when an ordered system begins to breakdown into chaos a consistent sequence of period-doubling transitions would be observed. Feigenbaum went on to calculate a numerical constant that governs the doubling process (Feigenbaum's constant) and showed that his results were applicable to a wide range of chaotic systems.
Although it is conceivable that one could do this exercise without a computer, calculating about sixty generations for a single value of R at a time, one would have no way of finding, without endless hours and days of calculations, the kind of pattern Yorke discovered. It is a startling result that the very slightest change in on the order of .0001, can change the result of a sixty generation sequence dramatically. The computer is an essential tool here to provide the kind of detail from which the larger picture represented by the graph is built.
Over the past thirty years scientists in a wide variety of fields simultaneously began to find similar patterns and laws in what are broadly described as nonlinear systems. Lorenz at MIT discovered what came to be called Strange Attractors studying weather patterns. Mandelbrot at IBM developed what has been called - somewhat immodestly - the most complex entity in the universe, the Mandelbrot set, and Barnesley, working in North Carolina, developed an algorithm that replicated organic complexity. The stunning computer graphics produced by this work have begun to be widely available through Internet and in mass publications.
Each of these systems share certain fundamental characteristics:
i) they use a relatively simple basic equation(s) with a critical parameter (such as the growth rate described above),
ii) the outcome of a single calculation feeds back into the equation as the basis of the next iteration: a self-referencing process. One is interested in the pattern of results; decline to 0; reach steady state; bifurcations leading to chaos; and exponential growth to infinity,
iii) one carries out the iterations for each small step across a range of values for the parameter, usually representing results graphically. These characteristics make exploration of chaotic system dynamics accessible on a home computer, and this has quickly popularized the methods and concepts of the new field.
Complex Adaptive Systems
Imagine a situation in which a chemical produces an enzyme whose presence then encourages further production of the same enzyme. This is an example of what computer scientists would call a positive-feedback loop. In chemistry it is called "auto-catalysis. " Such situations are rare in inorganic chemistry. But in recent decades the Molecular Biologist have found that such loops ...are the very stuff of life itself. Such processes help explain how we go from little lumps of DNA to complex living organisms (Kaufman, 1993, p.174).
While Prigogene was exploring the growth of order in what he called dissipative structures in the physical world, Kaufman and others were working to understand the processes of evolutionary change in the organic world, clearly the most obvious dissipative structure in nature. This was the perennial child's question: what is life? how did it happen?. Waldrop (1993) in his popular overview of work in complexity, poses a set of questions:
· How did a primordial soup of amino acids and other simple molecules manage to turn itself into the first living cell four billion years ago?
· What is life? Is a computer virus life?
· Why did individual cells begin to form alliances 600 million years ago, giving rise to jellyfish, insects and eventually humans?
· How can random genetic combinations result in such remarkable structures as the eye, the kidney, or the brain?
· Why do humans, like other creatures, organize themselves into families, tribes, communities, nations, and societies of all types? Why should there be such things as trust or cooperation? and why do they flourish?
· What is a mind? How does the brain give rise to such ineffable qualifies as feeling, thought, purpose, and awareness?
These are the questions that one learns not to ask in school. Science teaches analysis, not how to make a flower - that is science fiction. They are the questions that are the focus of an emerging disciplined inquiry into what are termed complex adaptive systems.
John Holland, a pioneer in mathematical models and computer simulations of neural networks, provided some answers at a conference on the Global Economy given at the Santa Fe Institute in 1987 (Waldrop, 1993).
Holland started his presentation by pointing out that the economy is an example par excellence of what the Institute had come to call "complex adaptive systems." In the natural world such systems include brains, immune systems, ecologies, cells, developing embryos, and ant colonies. In the human world they included cultural and social systems such as political parties or scientific communities. Once you learned how to recognize them, in fact, these systems were everywhere. They all share certain crucial properties:
Each of these systems is a network of many "agents" acting in parallel. If you were looking at business cycles, the agents might be firms. If you were looking at international trade, the agents might be whole nations. Regardless of how you define them, each agent finds itself in an environment produced by its interactions with the other agents in the system It is constantly acting and reacting to what the other agents are doing. And because of that, essentially nothing in its environment is fixed.
The control of a complex adaptive system tends to be highly dispersed. There is no master neuron in the brain, nor is there any master cell within a developing embryo.Coherent behavior in the system arises from competition and cooperation among the agents themselves. (This is, of course, also true of an economy, as the collapse of state control has illustrated).
A complex adaptive system has many levels of organization, with agents at any one level serving as the building blocks for agents at a higher level. In the brain, one group of neurons will form the speech centers, another the motor cortex, and still another the visual cortex. In precisely the same way a group of individual workers will compose a department, a group of departments will compose a division, and so on through companies, economic sectors, national economies, and finally the world economy.
Complex adaptive systems are constantly revising and rearranging their building blocks as they gain experience. Succeeding generations of organisms will modify and rearrange their tissues through the process of evolution. The brain will eventually strengthen or weaken myriad connections between its neurons as an individual learns from her encounters with the world.
At some deep, fundamental level, all these processes of learning, evolution and adaptation are the same. One of the fundamental mechanisms of adaptation in any given system is this revision and recombination of the building blocks.
All complex adaptive systems anticipate the future. The anticipation of an oil shortage can send shock waves of buying and selling through the oil markets - whether or not the shortage ever to pass. From bacteria on up, every living creature has an implicit prediction encoded in its genes. Likewise, every creature with a brain has myriad implicit predictions encoded in what it has learned. These predictions are more than passive blueprints, they are active, and produce behavior in the system: these internal models are the building blocks of behavior. Like any other building blocks they can be tested, refined and rearranged as the system gains experience.
Complex adaptive systems typically have many niches, each one of which can be exploited by an agent adapted to fill that niche. Just as the rain forest has a place for tree sloths and butterflies, the economy has a place for computer programmers, plumbers and pet stores. Every act of filling a niche opens up more niches - for new parasites, for new predators, for new symbiotic partners. So new opportunities are always being created by the system.
That means that it's essentially meaningless to talk about a complex adaptive system being in equilibrium: the system can never get there. It is always unfolding, always in transition. If the system does stop internal transformation, it isn't just stable , its dead. Likewise, there is no point in imagining that the agents can ever "optimize" their fitness, or utility, or whatever. The space of possibilities is too vast; they have no practical way of finding the optimum. The most they can ever do is to change and improve themselves relative to what the other agents are doing. In short, complex adaptive systems are characterized by perpetual novelty.
Each of these principles has been modeled, quantified, and simulated. Biologists and mathematicians have developed the 'genetic algorithm' which is an adaptive computer environment simulating evolutionary change at the genetic level (Kaufman, 1993, Mitchell, 1995). Holland and his students have modeled the processes of neural processing, induction and learning - in one case developing a self-learning system which solved a complex problem diagnosing faults in an extensive pipe network. Wolfram (1994) has defined a field called "cellular automatons," and Langton (1992, 1993) has developed a theory and simulations of what is called 'artificial life.' In economics, Arthur (1995) and colleagues have formally defined and persuasively simulated the operations of the stock market
Impacts on Contemporary Thought
"We believe it is precisely this transition to a new description [of nature] that makes this moment in the history of science so exciting. Perhaps it is not an exaggeration to say this is a period like the time of the Greek Atomists or the Renaissance, periods in which a new view of nature was being born." (Prigogene, p.36)
If the metaphor for framing our understanding of nature for the past two hundred years has been mechanical, in the next century it will almost certainly be organic. This is, in part, because the translation of complexity theory into technology will first arise in biological and social systems. This is more a reality than a prediction. In June 1995 Rose and Srinivasan published an article which showed how proteins, the biochemical molecules that make up cells, tissues and organisms, put themselves together. They used a form of the genetic algorithm in a computer simulation of protein folding, and demonstrated precisely how protein structures evolve, based on a few simple rules. The insight into this process will have will have immediate consequences in medicine, drug development and agriculture. Since proteins are the essential working parts of living matter, and since they are so diverse - the human body makes something like 50,000 different proteins - this work will provide a profound new insight into organic development and functioning. (Brown, 1995).
Complexity theory has already influenced economic and organizational paradigms. Reich's book The Work of Nations (1991), and Drucker's Post Capitalist Society (1993) persuasively argue that national and organizational wealth is now based on the process of knowledge creation, on the capacity for learning. The economics of this process are strikingly different from the economics of the industrial age. They depart from the positivist equilibrium models of Keynsian economics, and draw on non-linear, complex adaptive system models.
One particularly interesting example of this shift is the theory of positive feedbacks and increasing returns, developed by Arthur (1990). Classic economic theory assumes diminishing returns to any new product, any new technology. This is based on a mechanical model which posits that an economy tends toward equilibrium. The reality is that much of the modern economy functions on what is called "positive returns," where a particular innovation introduces a whole cycle of change, in which partial acceptance increases demand and catalyzes further self-similar innovations. The economist's imaginary world of perfect equilibrium is a metaphor for a static, complex machine, not for a complex system. The economy acts more like an organism - in which one small genetic change can be magnified to change everything. The history of computing, software and communications technology illustrates this shift. The counter-productive attempts to introduce sanctions to regulate international trade balances (Reich, 1991, Ch. 1 0), or the costly, unproductive attacks on Microsoft by government antitrust lawyers are examples of the wrong theory at work.
Within the business world, and in organizational development, the shift to a new paradigm has begun. Senge's immensely popular book The Fifth Discipline- the Art and Practice of the Learning Organization (1990) and the work by Savage (1990) have contributed to a revolution taking place in the structuring of industry and organizations. The essence of this shift is, in Drucker's words, 'The basic economic resource - "the means of production" - is no longer capital, nor natural resources...It is and will be knowledge...Value is now created by "productivity" and "innovation," both applications of knowledge to work" (Drucker, 1993, p.8). Wheatley (1992), Ray and Rinzler (1993), and Kelly (1994) have indicated the principles drawn from the scientific work on complex adaptive systems that are likely to define effective business practice.
A dynamic firm is likened to a mature ecosystem, in which the individuals and species are constantly undergoing transformation (death, birth, growth) but the total system is relatively stable in the face of external changes. A fundamental concept is the centrality of information and learning - both seen as essential elements for an adaptive system. Information and the development of new knowledge is the lifeblood for organizational effectiveness and growth. One function of management in a dynamic system is to provide unexpected 'insights' - and to assist towards 'creative disequilibrium.' Organizations should not try to package information with averages, pre-set categories and indicators, but use information to learn what is not expected. Kelly (1994) summarized much of this thinking in a list he immodestly calls the Nine Laws of God. These laws are taken from work underway on complex adaptive systems:
Distribute being: new organizations, ideas, arise from a field of many interacting parts;
Control from the bottom up. Overall governance must arise from the most humble interdependent acts done locally in parallel, not from top control.
Cultivate increasing returns. Each time you use a worthwhile idea or skill, reinforce it, make it more likely to be used again.
Grow by chunking. Begin with a simple system that works and build on that.
Maximize the fringes. Encourage diversity, a healthy fringe speeds new ideas, increases resilience, and is almost always the source of innovations.
Honor your errors. The process of being outside the conventional approach is often indistinguishable from error. Error is an integral part of any process of creation. Evolution can be thought of as systematic error management.
Don't pursue optima, have multiple goals. A complex system can only survive by "satisficing" a multitude of functions.
Seek persistent disequilibrium. Neither constancy nor relentless change Will support a new creation. Persistent disequilibrium is a state on the edge of chaos.
Change changes itself. Large complex systems coordinate change, and develop self-changing rules.
Education and Science in the 21st Century
"It was time to recognize that the standard education of a scientist gave the wrong impression. No matter how elaborate their mathematics could get, it inevitably misled scientists about their overwhelmingly non-linear world... "Not only in research, but also in the everyday world of politics and economics, we would all be better off if more people realized that simple linear systems do not necessarily possess simple dynamical properties." Robert May, quoted in Gleik, 1987. p. 80.
Formal education, schools and universities, have all the characteristics of what in Chaos Theory is called a strange attractor. Their form and substance, built 100 years after Newtonian physics provided the knowledge base for the technology to drive the industrial age, has but little changed when examined in relation to the revolutionary changes in our knowledge, and our ways of knowing briefly sketched in this chapter. There are variations of the schooling model from one country to the next, but these are fluctuations, not fundamental shifts.
Will the organizational form of contemporary schooling transform, recreated in new structures, providing learning environments based on principles of learning now being articulated and demonstrated in the complexity theory (e.g. Holland, 1989, 1995).?
There is a long lag between the development and validation of a scientific theory, its application to new technology, the change in world view that affects organizations, political processes and structures, and finally the content and methods used in schooling. European universities took more than one hundred years after the technology of the heat engine was evident to transform from centers of theological study to organized centers for scientific and engineering training and research. The twentieth century high school and university curriculum in sciences is remarkable by its neglect of relativity, quantum theory, much less chaos and complexity. Indeed, there is still strong dispute in conservative areas of America, on religious grounds, about the inclusion of evolutionary theory into the schools.
The policy decisions about the structure and content of national education systems are extraordinarily conservative, and are finally driven by transformations within the larger society.
Until our daily lives begin to be affected by the application of scientific knowledge and technology -- as has happened in the North with information theory and the personal computer -- national panels and curriculum centers are not pushed to incorporate accepted scientific developments within the public school program.
With that consideration, what impacts on the process of education and schooling might we see in the twenty-first century, as a consequence of modern scientific conceptual developments?
Evolution and Learning
One of the many concepts suggested by the principles of complex adaptive systems is the generality, in evolutionary terms, of the process of learning. By this perspective, the process of individual human learning is the most dynamic process, the most "emergent" reality, in the universe. This concept begins with the image of the matter of the universe organizing itself into galaxies, stars and planets as dissipative structures; then the matter of the planet earth organizing itself into the first life form; and that life form evolving into a cellular organism, the first true complex adaptive system. At each stage matter and energy interact to create a system more complex, more reflective of the principles described above, than the prior state. From the virus and bacteria to plants and animals, and from plants and animals to man, there is an accelerated process of transforming matter, and building blocks into more complex, dynamic and adaptive systems. Throughout biological evolution change occurs through the principles of genetic transformation - first through mutation, and later far more efficiently through the sexual mixing of DNA, itself a slow form of learning, although vastly faster than prior processes. Where biological organisms transform energy into order, human societies and individuals transform information into knowledge, and thereby create learning systems.
With humankind, the development of language, culture, writing, and today computers, has accelerated and enriched the evolutionary process enormously. Less than a century ago, education's function was to pass on the knowledge, skills and wisdom of the past on to the next generation. In the paraphrased words of the philosopher Whitehead, "we are of the first generation in human history where the wisdom of our fathers will be of less practical value to our livelihoods than the knowledge produced during our lifetimes." (Whitehead, 1967). To prepare today's child to cope in the 'learning society' of the 21st century, it is clearly essential to focus on learning how to learn, how to solve problems, how to synthesize the new with the old. There is a strong likelihood that this view of the role of education, which is now more rhetorical than practiced, will become a matter of social survival (Reich, 1991).
Learning theory and teaching itself is likely to be greatly enriched by the emerging science of complexity. A formal description of the principles governing the process of learning is at the core of new thinking about social evolution, organizational change and individual development. The contemporary wisdom for the international economic and political sectors argues for greater autonomy from government controls and for greater participation of all sectors of society in policy formation, so as to develop a freer system of exchange and thereby restore dynamism to stagnant economy. Within the developmental field, those working to improve educational policies and planning have turned from a centrist, state controlled planning model towards community and school-based change (Rondenelli, 1993, Heneveld, 1994). So too, teachers may develop the understanding that the starting point of learning is not so much the formal curriculum, but the rich experience and complexity of the conceptual structures that children bring to the classroom (Gardner, 1983, 1992), and seek to build the process of learning on this base.