| Discover the Reality of Scientific Mythology The Facts of Self-Animating Networks in Nature and a New, Realistic Role for the Mythic Imagination
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Quotations from Relevant Books
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Quotes from some of the authors listed on the References Page are provided below. These relate to concerns discussed on this website such as the following: > Beyond Mechanism: Our need for a new dynamical, network oriented worldview 'beyond reductionsim' > Emergence: The confounding ways new order emerges from chaotic and complex dynamics in complex adaptive systems > Cultural Transformation: Contronting a new reality arising from a new science > Network Autonomy: The dynamics and unpredictably purposeful, adaptively self-asserting behaviors of self-organizing networks, thus self-animating systems: > Spiritual Science: The emergence of creative network agency that constitutes a new, factual basis for a naturalistic spirituality and a 'new sene of the sacred.' |
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"Beyond Mechanism: Putting Life Back into Biology" edited by Brian G. Henning and Adam C. Scarfe Phillip Clayton “Why Emergence Matters” p. 75 Early modem science sought to reduce all natural phenomena to matter and the laws of physics. But a shift of emphasis has taken place in the last decades. Scientists now recognize nature’s tendency to produce more and more complex forms of organization, not all reducible to fundamental laws. This new “non-Reductionist” picture of the world gives rise to some rather different assessments of the goals and methods of the biological sciences. Jesper Hoffmeyer “Why Do We Need a Semiotic Understanding of Lite?” p.152 Biosemiotics is based on an understanding of agency as a real property of organic life, a property that is ultimately rooted in the capacity of cells and organisms to interpret (whether consciously or unconsciously) events or states as referring to something other than themselves or, in other words, the capacity to interpret signs. p. 162 A semiotic understanding of animate nature will potentially influence science and culture in important ways. Above all, it will strengthen our human feeling of relatedness to the other creatures of this world and our belonging in the biosphere. The image of animals and plants as stupidly obedient slaves of simple survival schemes will dwindle and be replaced by an understanding of, and an admiration for, the marvelous semiotic interaction loops through which organisms pursue their interests. Living beings are not the senseless and ignorant machines that science has taught us they are, and in the long run this can well have profound implications for how we treat natural systems. "Networkologies: A Philosophy of Networks for a Hyperconnected Age—A Manifesto" Christopher Vitale, Zero Books, 2014 p. 11 The project to develop an entire worldview based on networks luckily does not have to start from scratch. During the second half of the twentieth century, the science and mathematics of networks, a major component of what is often called “complex systems science,’ began to revolutionize a variety of fields of study in a manner which continues today, and which can provide a starting point for this project.. . . Complex systems science is a relational and network-oriented approach to scientific thinking. Opposed to various forms of “reductionism,” complex systems research shows how modes of interaction between relatively simple parts can give rise to highly complex behaviors. p. 16 What could it mean, then, for something to be networked, whether as an aspect of the world being diagrammed, or as a diagram itself? At its simplest a network is any whole, composed of parts. Distinguished from a background, and composed of other parts and wholes, layered into each other at multiple levels of scale. Anything which can be thought of in this way can be seen as a network, which is a general way of thinking about how things intertwine, interact, and hold together. 20 Everything in the world can be seen as a network, and in this sense, to call anything in the world a network simple means to see it relationaly: as a network composed of networks, linked to others, layered in levels, against a ground, and as an aspect of various processes and reifications. Networks are then, more than anything, a way of looking at the world, a shift in perspective, a lens which makes everything appear networked. 22 According to complex systems science, self-organization is promoted by a particular set of conditions, which include: diverse components, distributed organization, meta stability, and feedback between aspects and environment in a manner which is itself diverse, distributed, and meta-stable. Thereby potentiating sync between aspects, the emerging whole, and environment. When all these conditions are met, not only will a system spontaneously self-organize to greater complexity it will generally continue to do so, at least until one of these factors begins to fall out of sync with the others. p. 24 When complex systems self-organize in ways which increase their complexity, whether in quantity or quality, this is what complex systems science calls emergences. Emergence itself comes in many degrees and forms. A whirlpool is an example of the emergence of a simple physical complex adaptive system, if one which is relatively short-lived. Living organisms are more developed forms of emergence, and they can give rise to new forms of emergence in turn, such as learning and evolution, none of which could be predicted by an examination of the structure of any particular part of the organism or its brain, but only by the relational intertwining between these in particular sets of circumstances. Beyond physical and biological emergences, cultural advancements can also be seen as forms of emergence, from flocking of birds to the development of language in humans, and all of these feed back into physical and biological emergences to potentiate them further. p. 25 While all systems ultimately steal energy and materials from their environment, such as the manner in which all life on Earth feeds off the sun, robust systems are those which are able to grow and develop in relation to their environment in the least destructive and maximally creative ways, establishing feedback relations with their environment so that they do not destroy the conditions for the emergence of themselves or their environments in the present or future. p. 30 What the new science of networks has shown then, and artificial neural networks in particular, is that the types of experience given rise to by the human brain can be produced from the networking of the stuff of the world with itself. What matters isn’t what is networked, but how. Nothing less, and nothing more. This could possibly change the way we see almost everything. p. 32-33 Rather than mere materialism, the perspective opened up by these developments allows us to see the world and everything in it as the result of complex networking. For if the potential for mind is simply the result of the networking of neurons, essentially living wires, and these are themselves the result of the dynamic networking of matter and energy, which are themselves networks of quantum events, then this means that the potential for human experience, and all we have ever felt or even dreamed lies not in what things are, but in how they are intertwined. That is, what something is and what it can do is determined by how it networks, from molecule to emotion and thought and everything in between. If the human mind can be seen as produced by the networkings of matter, then so can anything else we have ever known. From such a perspective, every aspect of our world can then be seen as having infinite potential for emergence in and from itself, even if this can only ever be unleashed by means complex robust networkings "The Web of Life: A New Scientific Understanding of Living Systems" Fritjof Capra, First Anchor Book, 1996 Fritjof Capra p. 82 Having appreciated the importance of pattern for the understanding of life, we can now ask: Is there a common pattern of organization that can be identified in all living systems? We shall see that this is indeed the case. This pattern of organization, common to all living systems, will be discussed in detail below. Its most important property is that it is a network pattern. Whenever we encounter living systems-organisms, parts of organisms, or communities of organisms-we can observe that their components are ranged in network fashion. Whenever we look at life, we look at networks. . . . The first and most obvious property of any network is its non-linearity-it goes in all directions. Thus the relationships in a network pattern are nonlinear relationships. In particular, an influence, or message, may travel along a cyclical path, which may become a feedback loop. The concept of feedback is intimately connected with the network pattern. I6 Because networks of communication may generate feedback loops, they may acquire the ability to regulate themselves, for example, a community that maintains an active network of communication will learn from its mistakes, because the consequences of a mistake will spread through the network and return to the source along feedback loops. p. 83 Thus the community can correct its mistakes, regulate itself, and organize itself. Indeed, self-organization has emerged as perhaps the central concept in the systems view of life, and like the concepts of feedback and self-regulation, it is linked closely to networks. The pattern of life, we might say> is a network pattern capable of self-organization. This is a simple definition, yet it is based on recent discoveries at the very forefront of science. "A Third Window: Natural Life beyond Newton and Darwin" Robert E. Ulanowicz, Templeton Foundation Press, 2009 p. 8 If we wish to avoid a bad end, then maybe, just maybe, we should pause and reconsider our directions. The foregoing considerations suggest that we may harbor an inadequate or inaccurate image of reality, and so we might begin by scrutinizing our (mostly unspoken) assumptions concerning how nature acts. Although a legion of books is available describing the scientific method, works that elaborate and critique the underlying postulates (metaphysics) of conventional science remain scarce by comparison . p. 11 I argue that we need to shift emphasis away from objects and focus rather upon configurations of processes p. 25 To the best of my experiencIt is no exaggeration to say that the Newtonian worldview is in tatters. Unfortunately, surprisingly few of us seem willing to admit this condition. It is poignant to ask, therefore, what has arisen that can take the place of the Newtonian framework. As we shall see, there have been a number of thinkers who have suggested fertile new directions, but none has been accorded widespread attention. Rather, what one encounters among the scientific community is that most of us by and large cling to some dangling threads of the Newto nian worldview. Its just that there remains no widespread consensus about how much weight, if any, should be given to each assumption "Networks: A Very Short Introduction" Guido Caldarelli, Michele Catanzaro, Oxford UP, 2012 4 Many emergent phenomena rely crucially on the structure of the underlying networks. The network approach focuses all the attention on the global structure of the interactions within a system. The detailed properties of each element on its own are simply ignored. Consequently, systems as different as a computer network, an ecosystem, or a social group are all described by the same tool: a graph, that, is, a bare architecture of nodes bounded by connections. . . . P. 65 All these examples share with networks one basic feature: they are the outcome of a complex, largely unsupervised process. Heterogeneity is not equivalent to randomness. On the contrary, it can be the signature of a hidden order, not imposed by a top-down project, but generated by the elements of the system. The presence of this feature in widely different networks suggests that some common underlying mechanism may be at work in many of them’ Understanding the origin of this self-organized order is one of the central challenges of the science of networks. "Complexity: Avery Short Introduction" John H. Holland, Oxford UP,. 2014 p. 2 Each of these complex systems exhibits a distinctive property called emergence, roughly described by the common phrase ‘the action of the whole is more than the sum of the actions of the parts . p. 5-6 The behaviors of complex systems: Complex systems exhibit several kinds of telltale behavior. I will describe some of these behaviors briefly here; they will be examined in more detail in later chapters. -Self-organization -- into patterns, as occurs with flocks of birds or schools of* fish -chaotic behavior -- where small changes in initial conditions (‘the flapping of a butterfly’s wings in Argentina’) produce large later changes (‘a hurricane in the Caribbean’) --‘fat-tailed’ behavior, v/here rare events (e.g. mass extinctions and market crashes) occur much more often than would be predicted by a normal (bell-curve) distribution --adaptive interaction -- where interacting agents (as in markets or the Prisoner’s Dilemma) modify their strategies in diverse ways as experience accumulates. In addition, as already mentioned, emergent behavior is essential requirement for calling a system ‘complex’. "Reinventing The Sacred: A New View of Science, Reason, and Religion" Stuart A. Kauffman, Basic Books, 2008 Ix The title of this book, Reinventing the Sacred, states its aim. I will present a new view of a fully natural God and of the sacred, based on a new, emerging scientific worldview. This new worldview reaches further than science itself and invites a new view of God, the sacred, and ourselves ultimately including our science, art, ethics, politics, and spirituality. My field of research, complexity theory, is leading toward the reintegration of science with the ancient Greek ideal of the good life, well lived. It is not some tortured interpretation of fundamentally lifeless facts that prompts me to say this; the science itself compels it. This is not the outlook science has presented up to now. Our current scientific worldview, derived from Galileo, Newton, and their followers, is the foundation of modem secular society, itself the child of the Enlightenment. At base, our contemporary perspective is reductionist: all phenomena are ultimately to be explained in terms of the interactions of fundamental particles. X Reductionist worldview led the existentialists in the mid-twentieth century to try to find value in an absurd, meaningless universe, in our human choices. But to the reductionist, the existentialists’ arguments are as void as the space-time in which their particles move. Our human choices, made by ourselves as human agents, are still, when the full science shall have been done, mere happenings, ultimately to be explained by physics. In this book I will demonstrate the inadequacy of reductionism. Even major physicists now doubt its full legitimacy. 1 shall show that biology and its evolution cannot be reduced to physics alone but stand in their own right. Life, and with it agency, came naturally to exist in the universe. With agency came values, meaning, and doing, all of which are as real in the universe as particles in motion. ‘Real” here has a particular meaning: while life, agency, value, and doing presumably have physical explanations in any specific organism, the evolutionary emergence of these cannot be derived from or reduced to physics alone. Thus, life, agency, value, and doing are real in the universe. This stance is called emergence. ,. . . Emergence is therefore a major part of the new scientific worldview, Emergence says that, while no laws of physics are violated, life in the biosphere, the evolution of the biosphere, the fullness of our human historicity, and our practical everyday worlds are also real, are not reducible to physics nor explicable from it, and are central to our lives. Emergence, already both contentious and transformative, is but one part of the new scientific worldview I shall discuss.... p. 60 Self-organization may require that we rethink all of evolutionary theory, for the order seen in evolution may not be the sole result of natural selection but of some new marriage of contingency, selection, and self-organization. New biological laws may hide in this union. p. 281-282 \fi/e are beyond reductionism: life, agency, meaning, value, and even consciousness and morality almost certainly arose naturally, and the evolution of the biosphere, economy, and human culture are stunningly creative often in ways that cannot be foretold, indeed in ways that appear to be partially lawless. Hie latter challenge to current science is radical. It runs starkly counter to almost four hundred years of belief that natural laws will be sufficient to explain what is real anywhere in the universe, a view I have called the Galilean spell. The new view of emergence and ceaseless creativity partially beyond natural law is truly a new scientific worldview in h science itself has limits. And science itself has found those very limits. In this partial lawlessness is not an abyss, but unparalleled freedom, unparalleled creativity. Can only understand the biosphere, economic evolution, and culture retroactively, from a historical perspective . Yet we must live our lives forward, into that which is only partly knowable. Then since reason truly is an insufficient guide, we truly must reunite our humanity. And if so, we truly need to reinvent the sacred for ourselves guide our lives, based on the ultimate values we come to choose. At last, we must be fully responsible for ourselves, our lives, our actions, our values, our civilizations, the global civilization. "Signs of Life: How Complexity Pervades Biology" Richard Sole and Brian Goodwin, Basic Books, 2000 p. x The concept of emergence, once regarded by many biologists as a vague and mystical concept with dangerous vitalist connotations, is now the central focus of the sciences of complexity. Here the question is, How can systems made up of components whose properties we understand well give rise to phenomena that are quite unexpected? p. Xi What we are seeing is the beginning of a science of emergent forms. This is a new biological frontier that will leave its mark on the life sciences and then transform into something else. But it is likely to have longer* term consequences on our view of science itself. It will become evident that the new understanding of complex processes takes us beyond the traditional scientific perspective of prediction and control of nature, to a relationship of participation in natural processes that are unpredictable, though still intelligible. p. 18 Self-organizing behavior emerges unpredictably in systems at different levels. We make it intelligible recognizing how it is consistent with lower-level properties and by finding appropriate mathematical descriptors. But in doing this dosen’t reduce a whole to the properties of its parts and their interactions. p. 19 We believe that reductionism is inadequate as the primary explanatory framework of science, progress in understanding natural in interaction. It often involves grasping relevant aspects of whole systems and finding appropriate mathematical descriptors that capture these properties. p. 28 The sciences of complexity show us that we are embedded in a world fundamentally different from that which has previously characterized modem science, with its emphasis on prediction and control of nature. We can clearly exercise what ever control remains possible in complex*/ systems. But there are other options, such as participating rather controlling, that is, recognizing that we an influence complex systems and proceeding- cautiously with such mental unpredictability of our actions no longer be naïve observers who live outside the phenomena we manipuIate. "Complexity : A Guided Tour" Melanie Mitchell, Oxford UP, 2009 p. ix REDUCTIONISM HAS BEEN THE DOMINANT approach to science .since the 1600s. Rene Descartes, one of reductionism $ earliest proponents, described his own scientific method thus: to divide all the difficulties under examination into as many parts as possible, and as many as were required to solve them in the best way and to conduct my thoughts in a given order, beginning with the simplest and most easily understood objects, and gradually ascending, as it were step by step, to the knowledge of the most complex”1 Since the time of Descartes, Newton, and other founders of the modem scientific method until the beginning of the twentieth century, a chief goal of science has been a reductionist explanation of all phenomena in terms of fundamental physics. Many late nineteenth-century scientists agreed with the p. X But, twentieth-century science was also marked by the demise of the reductionist dream. In spite of its great successes explaining the very large and very small, fundamental physics, and more generally, scientific reductionism, have been notably mute in explaining the complex phenomena closest to our human-scale concerns. Many phenomena have stymied the reductionist program: the seemingly irreducible unpredictability of weather and climate; the intricacies and adaptive nature of living organisms and the diseases that threaten them; the economic, political, and cultural behavior of societies; the growth and effects of modem technology and communications networks; and the nature of intelligence and the prospect for creating it in computers. The antireductionist catch-phrase, “the whole is more than the sum of its pans, takes on increasing significance as new sciences such as chaos, systems biology, evolutionary economics, and network theory move beyond reductionism to explain how complex behavior can arise from large collections of simpler components. By the mid-twentieth century, many scientists realized that such phenomena cannot be pigeonholed into any single discipline but require an interdisciplinary understanding based on scientific foundations that have not yet been invented. Several attempts at building those foundations include (among others) the fields of cybernetics, synergetics, systems science, and, more recently, the science of complex systems. p. 12 Common Properties of Complex Systems: When looked at in detail, these various systems are quite different, but viewed at an abstract level they have some intriguing properties in common: 1. Complex collective behavior: All the systems I described above consist of large networks of individual components (ants, B cells, neurons, stock-buyers, Web-site creators), each typically following relatively simple rules with no central control or leader. It is the collective actions of vast numbers of components that give rise to the complex, hard-to-predict, and changing patterns of behavior that fascinate us. 2. Signaling and information processing: All these systems produce and use information and signals from both their internal and external environments 3. Adaptation: All these systems adapt—that is, change their behavior to improve their chances of survival or success—through learning evolutionary processes. Now I can propose a definition of the term complex system: a system in which large networks of components with no central control and simple rules of operation give rise to complex collective behavior, sophisticated information processing, and adaptation via learning or evolution. . . . Systems in which organized behavior arises without an internal or external controller or leader are sometimes called self-organizing. Since simple rules produce complex behavior in hard-to-predict ways, the macroscopic behavior of such systems is sometimes called emergent. Here is an alternative definition of a complex system: a system that exhibits nontrivial emergent and self-organizing behaviors. The central question of the sciences of complexity is how this emergent self-organized behavior comes about. |
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