Evolution and Complexity (1994)

Sohail Inayatullah

Originally published as a review “Life, the Universe and Emergence,” Futures (August 1994), 683-696.

EVOLUTION AND COMPLEXITY

Biochemist and former deputy editor of New Scientist and Research News Editor of Science Roger Lewin gives a tour of theories of complexity based on interviews with leading exponents of this new theory of everything.  Primarily focused on biological and evolutionary theories, Lewin interviews such leading scientists as theoretical biologist Stuart Kauffman, biologist James Lovelock, Artificial Life expert Chris Langton, sociobiologist Edward O. Wilson, geologist Stephan Jay Gould, biologist Brian Godwin, philosopher Daniel Dennett, physicist Murray Gell-Mann, mathematician Norman Packard, and ecologist Tom Ray.

Complexity theory claims to resolve the classic conflict between vitalists who believe evolution is externally caused by spirit or other vital forces and mechanists who believe evolution is bottom up based with survival of the fittest or adaption as the key variable.  In contrast, complexity theory argues that evolution occurs through emergence. New variables naturally develop over time. Organisms, individuals and societies self-organize, that is, they do not need an outside force to guide their growth.  Thus from simple conditions emerge complex conditions.

Complexity takes a dynamic view of life. Indeed, dynamism comes from life itself.  “Biological systems are dynamical, not easily predicted, and are creative in many ways,” argues Chris Langton.[i] “In the old equilibrium worldview, ideas about change were dominated by the action-reaction formula. It was a clockwork world, ultimately predictable in boring ways,” says Langton.[ii]  While boring, such predictability did allow humans to land on the moon.  If these where non-linear systems, Lewin warns us, we would clearly be still on the Earth unable to leave it since our trajectories could not be predicted.

But this does not mean that complexity throws us in a world where prediction is impossible? Not at all. Rather, since all complex systems are based on simple origins, or all simple systems generate complex patters, we can understand these deep patterns and thus better understand biological, environmental and even social change.  While this is obvious to physicists, it is not so obvious to biologists. The thrust of Complexity is a dialogue with the leaders in the field on how complexity theory is changing our understanding of traditional evolutionary theory.

Up to now, through computer modeling complexity theorists have managed to show that emergence can naturally occur, that from a few simple species, a host of evolutionary possibilities can occur.  But for those biologists less enthused with computer simulation, Darwin still reigns supreme.

While some believe that Complexity theory moves towards a theory of everything, others are rightfully more cautious since within different systems–from cellular automata to Gaia itself–there might be different types of complex relationships.

While Lewin attempts to remain objective, it is clear that the one variable that scientists fear is the mystical–that is, an external source that is fuzzy, that cannot be operationalized.  And this many see is the problem with vitalism, the belief that an elan vital somehow plays a role in our biological and social development. The response to this position has been reductionism, as per the work of ant theorist and sociobiologist Edward O. Wilson, who believe that genetic causes are primary in understanding human behavior.

Complexity theory, however, borrows more from ecological theory and the view of the interrelatedness of life as developed by James Lovelock.  The view, for example, that there are links between tropical forests and climate. “No rain, no trees, but equally, no trees, no rain,” argues Lovelock.[iii]  It is this interrelated view that Norman Packard speaks to.  When asked what the implications of complexity theory would be, he answers: “We would see the world as having more unity.”[iv]

Complexity theory attempts to make links between evolutionary systems and social systems as well, albeit in a simplistic way.  Nonetheless they are instructive.  It primarily supports the view like species, societies rise and fall.  There are periods of stasis and then periods of rapid change, or punctuated equilibrium.  In reference to the fall of the Soviet Union, Chris Langton tells us to expect a period of global instability.  “You can see these two species coexisting in a long period of stability; then on of the them drops out and all hell breaks loose. Tremendous instability.  That’s the Soviet Union.”[v] He adds, “I am no fan of the Cold War, but my bet is that we’re going to see a long of instability in the real world now that it’s over.”[vi]   Moreover, what happened to the Soviet Union will happen to liberal capitalism as well, unless of course, one believes that different organizing principles are at work or that the US and USSR were different species.

Complexity theory’s great contribution is showing that the Second Law of Thermodynamics is only part of the story, since some systems tend toward order, not disorder. Within nature, then, there is a deep order. But this order is not caused by the hand of God, complexity theorists are quick to point out.   For physicists this is quite natural but for biologists self-organization still appears mystical, a return to pre-Darwinian theories.

But even as Complexity theory develops its new science, modern molecular biology might make Complexity theory useless, since they believe that with the ability to manipulate and analyze DNA, the process of evolution will be finally completely understood.  In Lewin’s words: “Simply read the messages in the genes, and all would be revealed. …No nod in the direction of the complexities of development. No indication that population biology may play a role in the fate of a species. No suggestion that species are part of ecosystems, which themselves are components of evolutionary history. And, of course, nothing at all about the immanent creativity of dynamical systems.”[vii] Through genetic research our history will be available to us, the causes of the rise and fall of nations will be obvious, right there in our genetic structure.  But while we wait for these remarkable developments in genetics, complexity theorists believe that it is the science of complexity that will lay bare history and the Mind of God. Physicist Heinz Pagels writes: “I am convinced that the nations and people who master the new science of Complexity will become the economic, cultural and political superpowers of the next century.”[viii] Quite a claim and a clear indication that science is not merely about research but about power and control, about comparative advantage.

These grand claims have been made before by Catastrophe theory, developed by Rene Thom, which is now no longer seriously investigated, and by chaos theorists.  Chaos, for complexity theorists, is focused on order and disorder and merely one dimension of complexity since Chaos theory does not explain the mechanisms of change.  Complexity theory is concerned with systems that produce order. However, it is similar to chaos in that both are concerned with non-linear systems, both focus on interrelatedness, both seek for an underlying pattern to all physical and social phenomena.  But the key to understanding Complexity theory is emergence.  Lewin writes, “For an ecosystem, the interaction of species within the community might confer a degree of stability on it; for instance, a resistance to the ravages of a hurricane, or invasion by an alien species. Stability in this context would be an emergent property.”[ix] That is, it arises naturally from the conditions present.  It is not there in the realm of ideas nor can it be merely understood from a part thereof (the platonic and aristotelian positions), rather it emerges.  This is true for economic systems, biological systems, cultural systems, and so forth.  For example, according to physicist Gell-Mann, “In biological evolution, experience of the past is compressed in the genetic message encoded in DNA … in the case of human societies, the schemata are institutions, customs, traditions, and myths.”[x]  Complex systems thus learn from their environment, coding this information in different ways.

Is there Progress?

Complex systems exhibit organizing factors, structures in which the system is drawn to. In cultural evolution these might be bands, tribes, states, and empires, and now nation-states.  Within this model, structures would move towards these various . Sociality is also an attractor, for humans as well as insects. But for ants, for example, the biological attractor of sociality is not dynamic as it is for humans, which have a range of social structures (tribe to nations).    History then has patterns.  But then is it purposeful, is there progress?

For complexity theorists, more complex, more ordered does not necessarily mean the same thing, however.  A complex system might be more likely to collapse, for example. A watch is more complex than a sun dial but less likely to break down. This then counters the Spencerian and Darwinian of the great chain of being, from the simplist to the most complex with humans at the head.  The problem becomes how to measure complexity, by the number of vertebral column among species, perhaps? By this measure, according to biologist Dan McShea, there has been no change at all.[xi]

Are there then better measures of complexity? There is some agreement in the field that computational ability is a measure of complexity.  “There has been a general increase in information processing over the last 550 million years, and particularly in the last 150 million years.”[xii]  Computational ability, where survival is contested, gives the species an advantage.  But then isn’t this progress? Those societies that have a higher intelligence, more information, are not they higher up on the chain of evolution, one could ask.  Normam Packard sidesteps this return of social Darwinism by arguing that “people don’t believe it for sociological, not scientific, reasons. …I don’t impute a value judgement to computational superiority.”[xiii]

But for others, progress is a noxious idea that is not operationalizable and thus not testable.  Progress is noxious not only in the sense of a hierarchy of societies but also in the sense of a hierarchy of species.  For current biologists, the idea of progress brings back racism, the 19th century Western view of life.  At the same time, Lewin argues that “just because a scientific idea is imported into social values–however improperly used–doesn’t invalidate the original idea.”[xiv]

Thus if computational ability does mean progress than Complexity theory might be returning the idea of progress in Western society and science. Indeed, Spencer is believed to be a proponent of Complexity theory. While Spencer had an internal theory of complexity, that is, emergence, he was missing the external factors, such as natural selection, which provide the external variable.  In this sense, Complexity theory unites both Spencer and Darwin, Lewin argues. “The pure Spencerian view of the world, therefore, is that increased complexity is an inevitable manifestation of the system and is driven by the internal dynamics of complex systems: heterogeneity from homogeneity, order out of chaos.”[xv]   This, of course, is the classical position, that history is linear and rational and progressive. It is Man who has the ability to transform nature.  Lewin continues.  “The pure Darwinian view is that complexity is built solely by natural selection, a blind, non-directional force; and there is no inevitable rise in complexity.”[xvi]  Natural selection removes teleology from the scheme of history. However, while biologists may cling to this perspective, most have adopted a neo-Darwinian view, merging Spencer and Darwin.  Complexity theory takes a third approach, however.  According to Lewin, “the new science of Complexity combines elements of both: internal and external forces apply, and increased complexity is to be exacted as a fundamental property of complex dynamical systems.”[xvii]  Through natural selection, adaption and evolution occur. Computational ability increases as species become more complex.  Consciousness then becomes a bottom-emergent phenomena.

This, of course, should be obvious is good dialectical materialism as well.  As Marx reminded us in his laws of dialectics, the complex arises out of the simple.  Consciousness emerges from the material factors of history. There is no God arranging the world nor does consciousness exist hidden in evolution. It is an emergent property.

But from the perspective of Complexity theory, while derived from matter, Consciousness is not central.  Complexity theory does not argue for a brain-centric view of history.  There are degrees of consciousness, of computational ability. In Norman Packard’s words. “The way I see the science is that it’s concerned with information processing throughout the entire biosphere; information processing is central to the way the biosphere evolves and operates. Consciousness is just one part of that larger puzzle, and it’s important to remember that.  Most studies of consciousness focus just on the phenomenon itself, and that’s solipsistic.”[xviii] What then is the unique contribution of Complexity to the study of Consciousness. Again according to Packard, “it is to place consciousness into the larger puzzle of information processing in the biosphere.”[xix]

Gaia:

But what of the planet itself, isn’t it conscious as some proponents of the Gaian theory argue? According to James Lovelock,  the earth itself is a dynamic, self-regulating complex mechanism.  To attempt to prove this Lovelock invented computer models such as Daisyworld which show that there are homeostatic regulating principles at work in the Earth’s evolution–that is that Life, or the biosphere, regulates or maintains the climate and the atmospheric composition at an optimum for itself.”[xx]  The stability of the system, however, does not emerge from Consciousness or some other teleological principle but from the system itself, from its ability to adapt and survive.

While most believe Gaia to be a stable system, from Complexity theory, we learn that given certain conditions (changes in solar radiation for example) there are periods of rapid change, of punctuated equilibrium.  This is in contrast to conventional evolutionary theory which would predict gradual change. In this sense Gaia while its maintain Life at the global level, at the level of particular species, there is stasis and rapid change.  There is dynamic change.  But most important this change is emergent not based on a goddess but emergent properties which act as though they are moving towards fitness or survival.

But then is emergence always the same or are there an infinite number of species and societal possibilities? Simon Conway Morris asks what if the Cambrian explosion  (the beginning of complexity after three billion years of simplicity in which in a matter of a few millions years life exploded on the scene) was rerun? How would creatures look like this time around. According to Morris, the same development would occur and herbivores, carnivores and insectivores would result.[xxi]  But they would not look anything we have experienced.  In this view, our present world is simply one of an infinite number of possible worlds.  For others such as Brian Godwin, the mechanics of embryological development are constrained.[xxii]  Writes Lewin, ” In the language of complex dynamical systems, the space of morphological possibilities is thinly populated by C.”[xxiii] There are only certain possibilities. There are not an infinite range of C.  In this sense if one reran the Cambrian explosion, the world today would not look that different. In this sense there are not an infinite number of possible pasts or possible futures. These are constrained by C, by structures.

THE GRAND UNIFICATION AND THE SEARCH FOR THE NEW LAW

Stuart Kauffman goes far more into scientific and mathematical detail than Lewin’s story. The Origins of Order: Self-Organization and Selection in Evolution is Stuart Kauffman’s life work; a work he hopes will unify self-organization with Darwinian evolutionary theory.  It is the search for the new second law of thermodynamics, one that takes into account the ability of life to self-organize and now move towards entropy. “It is the search for a general law of pattern formation in non-equilibrium systems throughout the universe.”[xxiv] It is the belief that woven into the very fabric of nature is a deep undeniable creative order.  It is a journey  for Kauffman that is based on love, on the Einsteinian view of science–“that science was a search for the secrets of the Old One.”[xxv]  Indeed, as N. Katherine Hayles her nearly brilliant Chaos Bound: Orderly Disorder in Contemporary Literature and Science argues we cannot separate the metaphysics of scientists from their physics.[xxvi]  In this sense both complexity and chaos continue classical physics as the world remains orderly, even chaos now has deep patterns.  It remains a fundamental classical and religious view of the world, a world where God has given us the secrets, we just need to go explore. And at every step of the way, we are given directions. Yet this God is no longer active, he is the blind watchman. Truth is found through connections, serendipity, but the task remains the same, to discover the beauty and elegance of the universe.

Written very much for the scientist and not for the layman, still Kauffman does his best to be communicable by providing succinct intelligible summaries of chapters. In addition, The Origin of Order does attempt to find links to the social and policy sciences.  His goal is simple. “Simple and complex systems can exhibit powerful self-organization. Such spontaneous order is available to natural selection and random drift for the further selective crafting of well-wrought designs or the stumbling fortuity of historical accident.”[xxvii]  And yet self-organization has not yet been incorporated into evolutionary theory. For Kauffman, self-organization is the flip side of natural selection.

But while Kauffman is ever the rigorous scientist, as the case with other complexity theorists who are constantly on the search for new metaphors, for allies in other fields, for lessons learned from other disciplines, he does not suffer from scientism.  Nor he is afraid of sounding mystical.  Indeed the task for his book is to answer the question, “what are the sources of the overwhelming and beautiful order which graces the living world?” [xxviii] Kauffman believes that if his autocatalytic set story is true then he would have a plausible explanation of life.  Life could have emerged through self-organization, life was not an accident.  But it is the aesthetics of it that is the theoretical clincher. Writes Mitchell Waldrop, “The whole story was just too beautiful, Kauffman felt. It had to be true.”[xxix]

But Kauffman is not here to bury Darwin merely to expand upon him, to include the rise of spontaneous order within biological theory.  To do so Kauffman attempts to delineate the sources of order that evolution has to work with, to show how “self-ordered properties, permit, enable, and limit the efficacy of natural selection.”[xxx]

But while the individual scientist may have a moment of awe, theories that evoke non-material factors governing evolution remain inappropriate ala Rupert Sheldrake[xxxi] who postulates morphogenic fields or P.R. Sarkar[xxxii] who believes that our larger Mind, or Cosmic Mind plays almost a Lamarckian role, as species desire themselves into new forms.  Less Sheldrake, more Sarkar, in either case, these theories are problematic not only because they are extra paradigmatic but because they are not testable, that is, operationalizable.  Moreover these theories imply order and structure, something Darwinists cannot understand.  The rise of Darwin has been the rise of a view of organisms as ultimately accidental and historically contingent. More for Sheldrake than Sarkar, while there is emergence, it is Consciousness that is still the key–It is consciousness that communicates not the social organization of species.

The  way out for traditional scientists has been time.  Anything is possible, that is, in terms of questions of the origin of life, if we have two billion years. In traditional theory, time is then the hero, that allows anything to happen.  This allows the variable Consciousness to be controlled for.    Self-organization, while being holistic, does not sponsor non-material approaches to evolution, but it does search for universal laws.  Complex systems are selected because they harbor behavior which is the most flexible and adaptable.  Poised between the boundary of chaos and order, they can best respond to changes in the environment.  Kauffman puts this in the form of a hypothesis, and hopefully for complexity theorists, a law:  “Living systems exist in the solid regime near the edge of chaos, and natural selection achieves and sustains such a poised state.”[xxxiii]  In contrast, writes Kauffman, “systems deep in either the ordered regime or in the chaotic regime are probably neither capable of complex behavior nor highly evolvable.”[xxxiv]  In the ordered regime, mutations cause only slight changes. Conversely in the chaotic regime, slight changes cause dramatic changes in behavior.  It is on the edge of chaos that evolution then is possible.

But for this to happen, organisms at the edge of chaos, they must “Know their worlds. Whether we consider E. coli swimming upstream in a glucose gradient … or a hawk diving to catch a chick, organisms sense, classify, and act up their worlds.”[xxxv]  But how do they know their worlds.  Here Kauffman takes an expanded definition of the word, classify. “The capacity to know a world requires that sufficiently similar states of that world be able to be classified as ‘the same.'”[xxxvi] It is this definition that allows Kauffman to generalize his argument to Boolean networks and even business firms. E. Coli it knows its world because a wealth of molecular signals pass between a bacterium and its environment.  In this, Kauffman and other complexity theorists are looking at systems and structures, attempting to find similar classification schemes, much as Parsons has done for sociology.  We see this clearly in his jump from bacteria to the economic sphere. Just as

a colony of E. coli integrates its behavior … the organisms of a stable ecosystem for a functional whole.. The niches occupied by each organism jointly add up to a meshwork in which all fundamental requirements for joint persistence are met. Similar features are found in an economic system. The set of goods and services making up an economy form a linked meshwork of transformations. The economic niches occupied by each set allow the producers of that set to earn a living and jointly add to a web in which all mutually defined requirements are jointly met. Both biological and technological evolution consist in the invention of slightly or profoundly novel organisms, goods and services which integrate into the ecological or economic mesh and thereby transform it.  Yet at almost all stages, the web retains a functional coherence.”[xxxvii]

At this point we can be mislead into thinking that this is Spencerian evolutionism or Parsonian structural-functionalism, but as well shall see, it is the ecological metaphor where the individual is nested in the larger environment that provides the framework to Complexity theory.  Self-organization allows for a dynamism that is missing from traditional evolutionary thought.  The metaphors and policy implications of complexity theory are not those that favor equilibrium oriented politics; rather, they favor transformation and change, they favor variety and diversity, they favor interconnectedness not reductionist isolationism.

It can thus be argued that changing one part of the system can radically transform the entire system. While this is used to understand the fall of communism, in Waldrop’s Complexity, the same argument is used to predict that the US system might transform itself as well, since one of the functions of Americanism was to stem the Soviet tide.  With the fear of the enemy gone, either Americanism must transform or find a new enemy. Clearly, however, Iraq and South Korea have functioned as a way to keep the equilibrium of the US going.  But we should expect disequilibrium since the world itself is in chaos.  After chaos then what. Complexity and evolutionary transformation, what else.

The Social and the Biological:

Instead of moving to poststructural thought and the larger framing category of episteme, Kauffman use the term regimes of grammar.   To answer the question, what is a functional whole and how does it transform when its components are altered, Kauffman develops this alternative metaframework. In grammar regimes, “the objects of the theory are strings of symbols which may stand for chemical, goods and services, or roles in a cultural setting.”[xxxviii] Remember, we are searching for an overall language for a theory of everything from the smallest to the largest, from the biological to the societal to the astronomical. Using this model, Kauffman hopes to lay down a theory of that is appropriate for the biological and social sciences.

Among the features we shall find are phase transitions between finite and potentially infinite growth in the diversity  of symbol strings in such systems.  As we have seen, the phase transitions may well underlie the origin of life as a phase transition in sufficiently complex set of catalytic polymers. Similar phase transitions may underlie “takeoff” in economic systems, such as the Industrial revolution, once the systems attain a critical complexity of goods and services that allows the set of new economic niches to explode supracritically, and may provide models for the conceptual explosion wrought by the redevelopment of science three centuries.[xxxix]

The critique should be obvious, and this is not only because of the obsessive search for links between the biological and the social–again we saw this earlier in Spencer–but the problem is obvious.  How to explain the necessary exploitation that was needed for the industrial revolution? How to explain the slave trade, the massive appropriate of wealth from India, the extensive plundering of the colonies; in two words: brutal exploitation.  But while complexity theorists are concerned about the environment, exploitation and of the colonies of the other does not enter their dialogue. But within the evolutionary framework they can explain take-off.  That is England was poised at the edge of chaos while India was either too chaotic or too stable–too many regions vying for power after the weakening of the Delhi Sultanate or too stable after centuries of fatalistic Hinduism.  In either case the conditions that were ripe for self-organization were not there.  But perhaps more accurately, they already lived in ecological communities that were locked into positive cycles.  It was military and cultural power that destroyed them, and thus allowed for the Industrial revolution.  But this is merely survival of the fittest. India deserved to lose because she could not adapt but now not only could she not adapt she could not self-organize and lock into positive cycles of increasing returns.  Again this is the central problem of all evolutionary through that has progress immanent in it. Progress forces one to create a great chain of being from the lowest to the Highest.  While the scientific bases for this great chain of being is no longer valid, the image maintains its mythic influence on us. But instead of species we have nations.  This is what those committed to the Complexity model cannot understand;  That information does not always lead to the best possible result, that there is a qualitative difference between information and wisdom, between knowing what is possible and doing the right thing, that is, ethics.  Fortunately, as we see from Waldrop’s Complexity when one is less focused on evolution, we can make arguments for diversity and not linear progress, not selection and adaption.  Kauffman while brilliant at biology and mathematics, does not consider the politics of his epistemology, and of theory building.

Planning:

However, He does give us some useful insights into planning He shows that since the risk for planning far into future is greater than the risk for short term planning (since there is a greater chance one can be wrong). And yet the planner needs to think into the future, “the further she thinks ahead, the more an optimal plan can take account of the highly valuable goods and services which can be constructed from the renewable resources.”[xl]  Thus, rather than thinking too far into the future, it pays to only plan so far ahead where risks and rewards are met. This is what he calls bounded rationality.

For forecasting what this means is having overly complicated models does not allow for generalization while overly simple models with too few variables and data points overgeneralizes.  Kauffman also includes the idea of self-fulfilling prophecies.  He writes “adaptive agents may persistently alter their models of one another’s behavior. Once an agent adopts a changed model of another agent, then his own decision rules, and hence behavior, will change.” [xli]  Now comes the key: “it follows that such agents much coevolve with one another using changing models of one another’s behavior.” [xlii] What this means is that evolution, research, indeed, all activities are done in an holistic integrated sense. This coevolution can be orderly, chaotic or at the edge of chaos, that is, self-organizing.  The site of emergence is at the edge of chaos.  The edge of chaos is more than a simple boundary become disordered and ordered system, indeed it is  a special region to itself.  It was Chris Langton through his computer simulation programs that convinced Kauffman of this.  This realization allowed Kauffman to say that “living system are not entrenched in order systems but are in the area of phase transition, where things are looser and fluid.”[xliii] Natural selection then pushes systems to the edge of chaos, forcing them to adapt, to emerge, to find new solutions as they move around in their fitness landscape.

But forecasting, adaption, transformation is different at the three phases.  As the amount of data increases of other agents (again: political systems, economic agents, or organisms), models of the behavior of other agents becomes more complex.   In evolutionary language, they live on more rugged fitness landscapes.  These models drive agents into more chaotic regimes. More complex models are better able to predict small alterations in behavior.  But in chaotic regimes, models are less complex because change is prevalent, thus moving agents into more ordered regimes. Thus instead of the invisible hand or rational expectation models of behavior, Kauffman posits a model based on coevolution. Agents coordinate their behavior based on the phase they are in and in turn move to other system phases.  “If correct, [this model] may help us understand that E. coli and corporate executives build optimally complex, boundedly rational, models of the other agents constituting their worlds.”[xliv]  Thus Kauffman’s grammar models allow the study of linked processes, he believes, thus turning biology into a science that is law-like.  In his words: “Coevolving adaptive agents attempting to predict one another’s behavior as well as possible may coordinate their mutual behavior through optimally complex, but persistently shifting models of one another. Again, we suspect, the deluge of chaos will be obtained. we may find that E.coli and IBM do indeed know their world in much the same way.”[xlv]

As it has turned out IBM did not know its world well.  It did not move towards a chaotic phase nor to a complex phase.  New revolutions in technology merely forced IBM into an ordered stable organization, that did not lock into changes in computer technology. Instead of increasing returns as the case with Microsoft, it had diminishing returns. It stayed as the large hierarchical organization that did not lock into the future, it did not know its environment.

But Kauffman is not arrogant in his attempt to create a physics of biology, yet his wanderings into a sociology of biology are often trite and overly burdened by the system paradigm. By removing values and ethics at one level but keeping the linear, progress, equilibrium base values of Spencerian systems theory, Kauffman does not add to discussions in the sociology of knowledge or grand system building. His contribution is his effort to develop grammar regimes, to show how self-organizing systems can mathematically emerge, and to expand the discourse of Darwinian biology.

But Kauffman’s main thrust is to show that one can have self-organization without Creationism. We do not need a divine watchmaker.  His effort is to find the laws of biology, “to suspect with quiet passion that below the particular teeming molecular traffic in each cell lie fundamental principles of order any life would reexpress.”[xlvi] But again this does not mean that Kauffman ia religious. Indeed, once his computer model showed the possibility of emergence, he knew he had come “face to face with the secret of the Old One.[xlvii]  In Kauffman’s words, “I had a holy sense of a knowing universe, a universe unfolding, a universe of which we are privileged to be a part….I felt that God would reveal how the world works to anyone who cared to listen..I knew that God had revealed to me a part of how his universe works.”[xlviii]

INCREASING RETURNS AND SYSTEM DYNAMICS

Unlike Kauffman’s detailed accounts, Waldrop’s narrative is similar to Lewin’s in that it is a story of a group of male scientists (with an occasional female colleague but usually wife) discovering the world.  As with Lewin the story is written like a detective novel, where we see how initial assumptions and expectations change over time. We read about the personal frustrations of these men in their search for legitimacy, fame, and acceptance.

In between long discussions of economics, biology, and computer simulation, Waldrop follows the careers of Brian Arthur, Stuart Kauffman, John Holland and others telling stories of academic life, as for example the case of Warren McCulloch, Kauffman’s mentor.  “Former students who had lived with McCulloch told stories of leaving the house through the upper bedroom window to avoid being trapped. McCulloch would habitually follow Kauffman into the bathroom while he was taking a shower, flip down the toilet seat, and sit there happily discussing networks and logical functions of various kinds while Kauffman was trying to get the soap out of his ear.”[xlix]  A men’s club indeed.  But Waldrop does not a paint a picture of emotionally imbalanced scientists or only of happy times. Waldrop shows Kauffman’s suffering when he loses his daughter through an accident.  He also devotes considerable time to Chris Langton’s accident and how through it he suddenly understood that the universe was alive, that self-organization did exist.

Unlike Gleick’s Chaos [l] where discoveries are made in solitary settings, Complexity is a story of an institute, the Sante Fe Institute.  Waldrop traces how it began as a dream of multidisciplinarian institute with the aim putting complexity on the map, its struggles to obtain funding, to keep its research agenda open from any one person’s  politics. The goal was to create “a kind of 21st Century Renaissance Man … starting in science but able to deal with the real messy world, which is not elegant, which science doesn’t really deal with.”[li]  But as we might expect, the goal was not a universal renaissance–even if founders believed it to be–as we can tell by the fact that they wished to call it a new Athens, or par with the city state that gave the world Socrates, Plato and Aristotle.  The problematic nature of that old Athens (the role of females, slaves, young boys) would be something one would hope a holistic perspective like complexity could account before, but these are, after Western scientists, deeply entrenched in their own mythology even as they attempt to deny it.  Nevertheless, the story is exciting as ideas from economists, geneticists, biologists, information specialists all bounce off each other, and from the simple emerged the complex.

While Lewin, like Kauffman, is more concerned with biology, Waldrop follows more closely the life of the Institute, the lives of George Cowan, the long time president of the Sante Fe Institute, Murray Gell-Mann, and John Holland.  But the central figure in this tale is Brian Arthur, an economist who brings back into economic discourse the idea of increasing returns.  Of course those of us in the social sciences or students of political economy are struck by the idiocy of most economists, especially the ones who have won noble awards. But increasing returns does not make sense if one lives in conservative economistic world where the market does work, where monopolies do not emerge. But if the economist were merely to leave his office, he would see how new firms create new goods and ideas–often inefficient–and how these become locked in structures.  But for Arthur finding colleagues who knew something about the real world, instead of merely about that which could be mathematized was nearly impossible.  It was at the Sante Fe Institute however where he found his home.  It is here that Arthur eventually finds himself moving into philosophy and metaphysics. Indeed, in the final section of Waldrop’s Complexity, Arthur concludes comparing complexity to taoist thought in contrast to traditional science and economics which he compares to Newtonian Christian thought.

But while the end of the book is impressive for its metaphysics, the first hundred pages is stunning for its naivety.  Waldrop describes a major revolution in thought when Arthur and colleagues discover on a trip to Bangladesh that women have many children to increase their life chances, that is, that there are social and cultural reasons to population growth and control. Fortunately, he was not awarded a noble for this miraculous discovery.   He also discovers the politics to his and his field’s approach to modeling, that is, let us make the world less messy and use science and mathematics to run the world more rationally.  “Most people in development economics … believe that they are missionaries of this century. But instead of bringing Christianity to the heathen, they’re trying to bring economic development to the Third World,” says Arthur.[lii]  The trip to Bangladesh confirmed Arthur’s view that neo-classical economics had nothing to say to the real world most women and men live in.  The obvious truth that economics is intertwined with history and culture was not made available to Arthur.  But he is humble enough to say that even though the lesson is obvious, “I had to learn it the hard way.”[liii] Arthur, like futurists, began to understand the importance of models that bring in variables from many perspectives yet have deep underlying patterns.  Indeed after reading the struggles of those within classical disciplines one develops a deep appreciation for futures studies–its temporal focus, its attempt to be multidisciplinarian, to find patterns in social, cultural and evolutionary processes and systems.  But what is so obvious to the futurist is not so for the economist or the systems engineer.  Culture is soft, it cannot be mathematized and is thus not real.  Fortunately for Arthur, he went to Bangladesh to meet real people, who do not live in the computer simulations of scientists or the rational irrationality of economists.

The Economy as a Self-Organizing System:

After reading Prigogine, Arthur understands that the economy is a self-organizing system.  While neo-classical theory assumes that there is a negative feedback, the tendency for small effects to die away, system dynamics theory, Chaos, assumes that small effects get magnified under certain conditions.  Diminishing returns means that no monopoly can result, that market conditions can lead to the ideal system, to equilibrium (and if there are problems the State can always step in and fix things).  But increasing returns is based on the idea that a slight chance, a random occurrence, allows a particular product to get more buyers, which then locks in self-producing cycles, until the product has huge advantages over other products.  The VHS versus Beta for vcrs is one example. This was also the case with the QWERTY typewriter. It was designed to reduce type speed but eventually became the standard. As it was mass produced, more people learned it, and thus more were sold and produced–until the industry became locked in.  Microsoft’s operating system is another example.  New software may not be better but if by chance results, or  a few people see a commercial and buy (clever marketing), soon it becomes the standard.

In Arthur’s vision, the new economics would be based on biology, the system would be constantly unfolding, there would be no externalities since all would be part of the system, and the economy would be constantly dynamic, with structures constantly coalescing, decaying an changing. Individuals in this new economics would be part of the economic ecology, where they were complex.

But this type of economics would not be able to accurately predict the future, since one variable could through the equations off. In this sense the legacy of Chaos theory is that although their are deep patterns, these are in effect unknowable, the world is more unpredictable.  But we can understand the world. Good theory helps us explain how we act, how ideas relate to each other, helping us search for similarities in structures and fields.

But as might expect in the Reagan years, these view were not popular and Arthur was challenged to show examples of technologies that humans are locked into. That the question was even asked is part of the problem.  The example that best showed this is the gasoline engine. In its infancy, gasoline was considered the least promising source of energy, with steam the most likely, it was safer and familiar. But as it turned out, gasoline won largely by accident.  Because of the breakout of hoof-and-mouth disease in North America, which led to the withdrawal of horse troughs, where steam cars could refill, gasoline power became locked in, and we lost the chance to have a world with considerably less pollution, argues Arthur.[liv]  Of course, when Arthur gave talks in Russia, economists there countered that this would be impossible in communist countries.

Where Waldrop is useful to the social scientist–if one can still read on and not be amazed at the simple mindedness of biologists, economists and physicists–it is his policy implications, which are full of insight.  For example, according to standard economics theory,  Japan has been successful because of it low cost of capital, powerful cartels, the need to use technology in the absence of commodities.  However, low cost of capital means a low rate of return, and thus no reason to invent, cartels are inefficient, and most economies are weakened when raw materials are scarce. At the same time theories that look at culture and social structure also do not suffice, collective decisionmaking can slow action down, for example.  Japan has been successful because, “increasing returns make high tech markets  unstable, lucrative and possible to corner, and Japan understood this better and earlier than other nations.”[lv] Unfortunately, for the US high tech industries were treated like low-tech industries and thus no industrial policy was articulated.

The next step for Arthur was to develop computer programs to show dynamical economic systems, to show how different set of historical accidents can cause radically different outcomes to emerge.  However, even with this information increasing returns remained antithetical to the politics of the free market since saying that maximizing individual freedom might not lead to the best possible result but to monopolies and inefficient systems was unacceptable for non-Marxists economists since it made problematic the entire neo-classical framework.

From Arthur, Waldrop moves to many of the themes that Lewin discusses, focusing on proofs of emergence at the level of cellular automata. Initial workshops at the Sante Fe institute were full of excitement and the beginnings of a shared language.

In particular, the founding workshops made it clear that every topic of interest had at its heart a system composed of many, many’ “agents.” These agents might be molecules or neurons or species or consumers or even corporations. But whatever their nature, the agents were constantly organizing and reorganizing themselves into larger structures through the clash of mutual accommodation and mutual rivalry. Thus molecules would form cells, neurons would form brains, species would form eco-systems, consumers and corporations would form economies, and so on. At each level, new emergent structures would form and engage in new emergent behaviors.[lvi]

The challenge, of course, as we see from Kauffman’s The Origin of Order, was to find the fundamental laws of emergence. To do this one could not have just physicists or biologists or economists, one needed experts in many fields. Bringing them together was the purpose of the Sante Fe Institute.  For futures studies the lesson is obvious, we need agreement on some larger project of futures studies. Thus while conferences are wonderfully multidisciplinarian they have no focus, no problem to solve, no vision to make law-like.

But it is this multidisciplinarian perspective that makes the writing of complexity rich. We learn how Kauffman is stunned at how static the neo-classical world is. We see how when physicists and economists meet at the Sante Fe Institute, it is hard for physicists to take the dismal science seriously, how so little of what they do relates to reality.  But we also learn about how similar technological systems are to ecological systems.

Moreover, these technological webs can undergo bursts of evolutionary creativity and massive extinction events, just like biological ecosystems. Say a new technology comes in and replaces and older technology, the horse. Along with the horse go the smithy, the pony express, the watering troughs, the stables, the people who curried horses, and so on. The whole subnetwork of technologies that depended upon the horse suddenly collapse … But along with the car come paved roads, gas stations, fast-food restaurants, motels, traffic courts and traffic cops, and traffic lights. A whole new network of goods and services begins to grow, each one filling a niche opened up by the goods and services that came before it.[lvii]

Unfortunately instead of seeing these as isomorphisms among different metaphorical systems, Complexity theorists often fall into the trap of misplaced concretism and confusing metaphor with objectivity.  They forget to take the language of one theory within its own complex context.  The larger cultural context for each theory, each discipline is inaccessible to them.  As is culture in general.  Complexity theorists do not understand that cultures too are destroyed by new technological systems. And like the horse which become ceremonialized in weddings and coronations or reduced to leisure, cultures become museumized. But some cultures do fight back. Fundamentalism is one cultural form that sees its niche being taken away. Its agents–mullahs and priests–attempt to find ways to battle these new technologies.  National sovereignty too can be seen in this light, as a system which, while on the verge of disappearance is trying to find ways to reassert itself. But this part of the problem, for both physics and neo-classical economics have agents that do not make decisions, do not suffer, one is merely following universal laws, the other rational greed, neither exists in a web of cultural complexity, as complexity theory suggests. It is culture that then that is the variable that remains silent in the language of Complexity theory; and paradoxically, it is Complexity theory that show how culture emerges.  Indeed, emergence is about the creation of culture.  The numerous systems that theorists hope to find a general law–evolution, economy, physics–for are all culturally nested within each other. And as Arthur astutely points, the method of investigation is founded on a cultural metaphysic as well as a psychological type of scientist.

Still there are useful policy implications.  With respect to global economic policy, Complexity theory does not restate liberal economics but it does not throw out the idea of growth either.  Indeed, innovation leads to innovation, and after a certain level of complexity, a new economy emerges that is autocatalytic.  The policy prescription is diversity, manufacturing and not dependent on the selling of raw materials.  Trade then between economies can leader to higher complexity but not if one system is undeveloped and the other developed. In the latter case, the developed or more complex nation will merely feed of the former. The former will go extinct, it will not be able to move up the fitness landscape.  But the problem of exploitation is not one that Waldrop discusses rather the issue for them is transformation. For example, how “injecting one new molecule into the soup could often transform the [system] utterly in much the same way that the economy was transformed  when horse was replaced by the automobile.”[lviii]

But John Holland does have a place for exploitation in his theory of complex adaptive systems. For him, complex adaptive systems–the brain, the economy, the ecology, computer programs, firms, individuals, nations–have more than one niche, which can be exploited by other agents. Thus the economic world has a place for programmers and plumbers and the rain forest has a place for crocodiles and butterflies. “The act of filling up one niche opens up more niches–for new parasites, for new predators and prey, for new symbiotic partners,” writes Holland.[lix]   Each change creates new opportunities and failures.  Complex adaptive systems are always in a state of flux, equilibrium is death.  Agents can never optimize a system, they cannot optimize their utility, their fitness. Finding an optimum is impossible, all one can do is change, and one cannot predict this change since agent is part of a larger ecology, a web of interrelationships.

It is this type of talk that has led Arthur to write that the metaphysics of Complexity theory is based on Taoism. God is not the watchmaker, there is no inherent order–as postmodernists as well argue–what is, is always in a state of flux–as Marxists would tell us.  In Arthur’s words, The world “is like a kaleidoscope: the world is a matter of patterns that change, that partly repeat, but never quite repeat, that are always new and different.”[lx] The neo-classical world view is a world of ordered order, fundamentally Christian.

What results then is a worldview based on accommodation and coadaption. There is no duality between humans and nature since human are part of nature.  We are part of the system, although an arrogant part. Optimization assumes that humans are first, as in the case of environmental cost-benefit studies.  They assume that we are outside nature, and nature is inside a store–the shopping center model.   More productive are institutional-policy analysis, where the actors are interactive and where culture, environment and intrinsic to the system not externalities.   In this sense typically phrases like “the optimization of policy decisions concerning environmental resources” become absurd.  They assume a static hierarchical world.

Amazingly, this type of think leads traditional economist Arthur as well as others of the Sante Fe Institute into the realm of much of what is current in futures studies: the politics of metaphor.   They argue that bad policymaking usually involved a poverty of metaphors, of ways of constituting reality.  For example, it may not be appropriate to think of a drug war, with assaults and guns, since each nation is complicit in drug use, drug production, drug culture, and the definitions of drugs themselves.

For Arthur, while one way to understand the new science of complexity is to look at metaphysics, the other is to look at psychological types. One type of scientist needs order and stasis, the other is comfortable with messiness and process.  The first spend their effort trying to make systems go back to equilibrium, the second are less Platonic and Newtonian and more influenced by Heraclitus who argued that the world is in a constant flux. What complexity adds to Heraclitus, is that this flux can become self-organized, allowing consciousness to emerge.

For biologist and artificial intelligence specialist Chris Langton, the metaphor is not the clock but the growth of a plant form a tiny seed or, more specifically the unfolding of a computer program from a few lines of code (indeed, much of this book is about  the effort to create such a program where life is not deigned in the program but emerges spontaneously).  It is the emergence of lifelike behavior from a simple rules.   This is the realization that reality cannot be captures by simple minded logic, that messiness–or metaphor–is intrinsic to the system, this is what Kurt Godel, Alan Turing in computer programming, chaos theoreticians, and postmodernists with respect to language have managed to suggest, if not show.

Thus instead of optimal solutions or utopias are viable solutions or eutopias, good places.  The task is to focus on robustness in the face of an ill-defined future.  That, believes Arthur, “puts a premium on becoming aware of non-linear relationships and causal pathways the best we can.”[lxi]  It is thus attempting to bring economics from the 18th century of Darwin and Newton to the 20th century.

What is needed then for Holland, is to understand how to adapt in conditions of constant change and unpredictable, conditions at the edge of chaos.  In this the debate about sustainability is a mistake from the view of complexity theory. A sustainable society can become a dystopia where our lives are controlled, with few freedoms, and a loss of cultural diversity. What is needed. believes Murray Gel-Mann, is a “society that is adaptable, robust and resilient to lesser disasters, that can learn from mistakes, that isn’t static, but that allows for growth in the quality of human life instead of just the quantity of it.”[lxii] But this then is the paradox, what is needed are general principles on a world solution to pressing problems, that allows for mistakes and cultural tolerance.  We have to find ways to avoid the large avalanches of change (to use the language of Chaos theory), such as nuclear disaster, world war 111 or environmental or economic disasters.

Specifically, Complexity theory allows us to understand and explain (not predict, and in this sense it is a departure from traditional sciences and social sciences) why the Soviet Union collapsed.  The system was not flexible enough and got locked into negative cycles, not positive lock ins. It was too ordered. Anarchy on the other hand is to chaotic, too fluid. But unlike Alex Argyro’s, A Blessed Rage for Order: Deconstruction, Evolution, and Chaos[lxiii] in which he concludes that the American system of checks and balances, of liberal economics of individualism, is the best of all worlds (since it is self-regulating and self-learning system that combines chaos and order), theorist Farmer argues that laissez faire systems also fail as they are too chaotic.  “Like a living cell, they have to regulate themselves with a dense web of feedbacks and regulation, at the same time they need to leave plenty of room for creativity, change, and response to new conditions.”[lxiv]  Evolution thrives at the edge of chaos, where neither chaos or order are dominant, this allows for gradual controlled change, where flexibility can emerge. It is learning and evolution that pushes a system to the edge of chaos, into complexity.  Perpetual novelty is about moving around at the edge of chaos.  For many this might be too much, what is needed is periods of transformation, and then new levels of organization and order.  Stasis and transformation not just continuous revolution.

Clearly then complexity is a slippery concept with some general agreement but with theorists using it in different ways, some from a Spencerian-Darwinian background, some from a more Taoist perspective, and some from an artificial intelligence background.  They come at from different areas as well: from computer simulation models, through years spent studying a fruit fly, and through economic analysis.  What is missing are perspectives from the humanities, from myth.  Arthur begins to make these connections as he investigates the metaphysics of complexity and the scientific enterprise they are caught in. But in their effort to make the analysis of emergence less focused on the divine hand of God, they forget that their efforts to are part of a political-historical web. That is not an accident that chaos and complexity are central topics in the late 20th century, as modernity has exploded from within and without. Indeed, they too are part of the pattern of evolution, a natural emergence from previous scientific enterprises.

But all said and done, the problem of Consciousness remains.  All self-organization gives us is a free lunch, from nothing, again something arrives. Even Spencer had his absolute principle, the end of evolution.   It is this that perhaps they miss. The attraction of the Great, or the divine, or the idea of paradise, the idea of perfection.  Their contribution of complexity theory is to show that life no longer is in the material nor in the spiritual but in the social organization of organisms. If one posits a prior principal, whether consciousness or an initial programmer, one has not explained anything, merely pushed the analysis elsewhere. “This is Darwin’s …insight, that an agent can improve its internal models without an paranormal guidance whatsoever.”[lxv] Clearly elegant, clearly part of the story, an important part of it. But the key is that complexity does not require a strict theory of progress, new systems are not necessarily better since this definition is problematic. And given the fluid nature of the real, we can go back in past and pick up past forms, and adapt them to novel conditions.  Politically, it gives up to those battling the status quo, those hoping for change. The task for them is to move the system they inhabit to the edge of chaos, where new social structures can emerge.

At the same time, complexity is also about understanding the future of life on the planet. While much of research into emergent systems is based on computer simulations, wherein one can argue that computer virus may indeed be alive (they can reproduce, they can store a representation of themselves onto another computer, “they can command the metabolism of their host to carry out their own functions”[lxvi] (such as real viruses), it is the creation of artificial human life that the new sciences must address.  Chris Langton writes that “Not only the specific kinds of living things that will exist, but the very course of evolution itself will come more and more under our control.”[lxvii]  Of course, since changes in initial conditions may dramatically change outcomes, as Chaos theory would assert, what new life forms might emerge at the edge of Chaos is not clear.  As other Complexity theorists, Langton believes that these issues must be publically, and globally, debated. Yet he remains positive.  “With the advent of artificial life, we may be the first creatures to create our own successors…. It is quite possible that, when the conscious beings of the future look back on this era, we will be most noteworthy not in and of ourselves but rather of what we gave rise to. Artificial life is potentially the most beautiful creation of humanity.”[lxviii] A new type of emergence, a new level of complexity that emerges from the present chaos.

But as we might expect, this new open world where new life is being created is fundamental Western. Even as it approaches integrated Taoist perspective–Arthur’s vision but clearly not Langton’s–it is linear.  The Sante Fe Institute would gain by opening up their definition of science and asking what isomorphic theories might emerge from alternative conceptions of science.  Examine an alternative Indian view which also attempts to reconcile emergence with evolution.  In this view, evolution is cyclical beginning with infinite Consciousness to Cosmic Mind and then to matter. We quote extensively from psychologist and physicist Rudreshananda. “From matter, individual mind emerges, evolves and finally merges back into Cosmic Mind and the Consciousness, completing and “cosmic cycle of creation.”[lxix]

But exactly how is matter formed from Cosmic Mind, and how does individual life and mind emerge from matter? In this perspective, there is an intelligence that links Cosmic intelligence to the world of relativity of time, space, and form.  Microvita are responsible for the creation of matter, life and individual minds in the universe.  They are conscious, living entities, so small that millions of microvita form a single electron, while billions form a carbon atom. Microvita move throughout the universe creating bodies and minds. Microvita are responsible for organizing energy to create matter with mass and its other properties.  Energy requires intelligence to become organized and that intelligence is supplied by microvita. Microvita are responsible for the origin and evolution of life as well. Evolution is not random but guided by desires, the environment and cosmic intelligence, which guides any changes desired collectively by a group of organisms. Microvita provide the genetic information to create species evolution by organizing new genetic chemicals such as DNA and RNA required for evolutionary transformations. The emergence of mind from matter (composed of microvita originated from cosmic intelligence) is also guided by microvita which help organisms express greater physio‑psychic potentialities during their evolutionary development.[lxx]

Merits aside of the truth of these statements, they are clearly contentious and problematic–for example how are created? To assert that the Infinite creates them merely pushes back the problem–is that here is another attempt to rethink evolution that does not lead to simple Creationism, nor does it attempt to maintain a secular view of the world, in fact, one can see how dialectics, emergence, and microvita can combine together.  However, as science it is not acceptable since its hypothesis can not be presently tested.  But what is important is that from an Indian thinker we gain a cyclical view of the universe and evolution.  Metaphysics gives us our physics.  But the task for those involved in microvita research is to develop some type of tests, proofs, arguments that move microvita from mere cosmological speculation to a theory with some agreement among a community of scientists.

Still Waldrop’s Complexity should be lauded even though it is myopic in its inability to understand the cultural and political, and for its naivete in taking seriously the neo-classical economic discourse.  Nonetheless there is an attempt to examine the metaphysics of complexity. There is an attempt to examine the lives of the men who have founded this new field.  And as we see from Kauffman’s The Origins of Order this effort is one based on humility.  Lewin shows us the exactness, the rigor, the grand debates within this area. At the same time, he attempts to tackle the problem of progress, as well as the links between Complexity theory and Gaia theory.  All writers also attempt to develop the policy implications of this new science, they understand that science exists with an policy environment, a policy community.  What makes both Waldrop and Lewin especially interesting is that they tell a story, and succeed in making science a story as well.

Notes

[i].   Roger Lewin, Complexity: Life at the Edge of Chaos (New York, Macmillan, 1992) page 190.

[ii].  Ibid.

[iii]. Ibid, page 118.

[iv].  Ibid, page 192.

[v].   Ibid, page 196.

[vi].  Ibid.

[vii]. Ibid, page 180.

[viii].     Ibid, page 10.

[ix].  Ibid, page 13.

[x].   Ibid, page 15.

[xi].  Ibid, page 135.

[xii]. Ibid, page 138.

[xiii].     Ibid, page 139.

[xiv]. Ibid, page 143.

[xv].  Ibid, page 148.

[xvi]. Ibid, page 148.

[xvii].     Ibid, page 148.

[xviii].    Ibid, page 171.

[xix]. Ibid, page 170.

[xx].  Ibid, page 114.

[xxi]. Ibid, page 72.

[xxii].     Ibid.

[xxiii].    Ibid.

[xxiv].     M. Mitchell Waldrop, Complexity: The Emerging Science at the Edge of Chaos and Order (New York, Simon and Schuster, 1992) page 299.

[xxv]. Ibid, page 103.

[xxvi].     N. Katherine Hayles, Chaos Bound: Orderly Disorder in Contemporary Literature and Science (Ithaca, Cornell University Press, 1990), pages 91-102.

[xxvii].    Stuart A. Kauffman, The Origins of Order: Self-Organization and Selection in Evolution (New York, Oxford University Press, 1993) page v11.

[xxviii].   Ibid, page xiv.

[xxix].     Waldrop, op cit, reference 24, page 125.

[xxx]. Kauffman, op cit, reference 27, page xiv.

[xxxi].     Rupert Sheldrake, The Presence of the Past: Morphic Resonance and the Habits of Nature (New York, Times Book, 1988).

[xxxii].    P.R. Sarkar, Microvita in a Nutshell (Calcutta, Ananda Marga Publications, 1993).

[xxxiii].   Ibid, page 232.

[xxxiv].    Ibid.

[xxxv].     Ibid.

[xxxvi].    Ibid, page 233.

[xxxvii].   Ibid, page 370.

[xxxviii].  Ibid.

[xxxix].    Ibid, page 371.

[xl].  Ibid, page 399.

[xli]. Ibid, page 401.

[xlii].     Ibid.

[xliii].    Waldrop, op cit, reference 24, page, 303.

[xliv].     Kauffman, op cit, reference 27, page 402.

[xlv]. Kauffman, op cit, reference 24, page 404.

[xlvi].     Ibid, page 645.

[xlvii].    Waldrop, op cit, reference 24,  page, 133.

[xlviii].   Ibid, page 133.

[xlix].     Ibid, page 115.

[l].   James Gleick, Chaos: Making a New Science (New York, Viking, 1987).

[li].  Waldrop, op cit, reference 24, page 68.

[lii]. Ibid, page 26.

[liii].     Ibid, page 27.

[liv]. Ibid, pages 40-41.

[lv].  Ibid, page 43.

[lvi]. Waldrop, 88.

[lvii].     Ibid, page 119.

[lviii].    Ibid, page 126.

[lix]. Ibid, page 147.

[lx].  Ibid, page 330.

[lxi]. Ibid, page 334.

[lxii].     Ibid, page 351.

[lxiii].    Alex Argyro, A Blessed Rage for Order: Deconstruction, Evolution, and Chaos (Michigan, University of Michigan Press, 1991).  Also see Sohail Inayatullah, “Chaos in Myth, Science and Politics,” in Mika Mannermaa, Sohail Inayatullah and Rick Slaughter, eds., Chaos and Coherence (Turku, Finland, Finnish Society for Futures Studies, 1994).

[lxiv].     Waldrop, op cit, reference 24, page 294.

[lxv]. Ibid, page 198.

[lxvi].     Ibid, page 283.

[lxvii].    Ibid, page 283.

[lxviii].   Ibid, page 285.

[lxix].     E-mail transmission. Based on Rudreshananda, Ac., Microvita: Cosmic Seeds of Life (Mainz, Germany, Microvita Research Institute, 1988).

[lxx]. Ibid.

Complexity: Life at the Edge of Chaos

by Roger Lewin. New York, Macmillan, 1992, 208 pages.

The Origins of Order: Self-Organization and Selection in Evolution

by Stuart A. Kauffman.  New York, Oxford University Press, 1993. 709.

Complexity: The Emerging Science at the Edge of Order and Chaos by M. Mitchell Waldrop. New York, Simon and Schuster, 1992. 380 pages.