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A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
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II. Pedia Sapiens: A Planetary Progeny Comes to Her/His Own Actual Factual Knowledge

C. Earthica Learns as a Symbiotic Person/Planet, Collaborative Ecosmo Sapience

Clery, Daniel and David Voss. All for One and One for All. Science. 308/809, 2005. An introduction to a special section and update on a worldwide “Distributed Computing.” Typical articles are Service-Oriented Science by Ian Foster and Cyberinfrastructure for e-Science by Tony Hey and Anne Trefethen.

Cobb, Jennifer. Cybergrace. New York: Crown, 1998. An IT professional views the Internet as an embryonic world sensorium with an integrative and spiritual potential to inform, heal and empower a humane earth community.

Combs, Allan and Stanley Krippner. Collective Consciousness and the Social Brain. Journal of Consciousness Studies. 15/10-11, 2008. Wise neuropsychologist elders observe ”similar dynamical patterns” of coherent neural networks to grace both brains and human groups, each capable of a unified sense of awareness, cognition, and knowledge. See also in this issue on Social Approaches to Consciousness a paper by Robert Turner and Charles Whitehead on How Collective Representations Can Change the Structure of the Brain.

Dankulov, Marija, et al. The Dynamics of Meaningful Social Interactions and the Emergence of Collective Knowledge. Nature Scientific Reports. 5/12197, 2015. In a paper that again offers a marriage of physics and peoples, systems mathematicians Dankulov and Bosiljka Tadić, Jozef Stefan Institute, Slovenia, and Roderick Melnik, Wilfred Laurier University, Canada, find condensed matter principles to be similarly exemplified in human sociality where they foster a dynamic, self-organized cooperation. As a result, viable “knowledge building and sharing communities” are achieved.

In modern statistical mechanics, it has been recognized that the collective phenomena arise from interactions among the elementary units via a spontaneous transition to an organized state, which can be identified at a larger scale. Recently, this unifying principle is gaining importance in other natural sciences, for instance for elucidating organization in living systems, emergence of coherent activity in neuronal cultures, and developing computational social science. In social systems, interactions and cooperations among actors can lead to the recognizable collective behavior, for instance, the development of collective knowledge, appearance of common norms or language. The quantitative study of the stochastic processes underlying these social phenomena utilizes the methods of statistical physics supported by analysis of the plethora of online empirical data. Some illustrative examples are the appearance of good and bad conduct in online games and groupings induced by the exchange of emotional messages on social sites. However, a deeper understanding of the mechanisms of collaborative social endeavors remains a serious challenging problem in physics and social dynamics modeling. (1)

Davidson, Cathy and David Goldberg. The Future of Learning Institutions in a Digital Age. http://mitpress.mit.edu/9780262513593. An online MacArthur Foundation report which is also available in paper from MIT Press, and is to be expanded into a 2010 book. Computer revolutions have engendered a world-wide community access to the entire corpus of human knowledge, which then challenges educational endeavors to keep apace.

Davies, John, et al, eds. Semantic Web Technologies. Chichester, UK: Wiley, 2006. The global computer Internet is under revision and reinvention based on a new generation of interactive ontologies and protocols to better foster information accessibility, commerce, and dialogue. The name given is Semantically Enabled Knowledge Technologies whose many dimensions are explored herein from annotation principles to digital libraries.

De Rosnay, Joel. Symbionomic Evolution: From Complexity and Systems Theory to Chaos Theory and Coevolution. World Futures. 67/4-5, 2011. Some three decades after his The Macroscope, the French futurist, author, MIT PhD in biology, continues to envision the imminent appearance of a worldwide “macro-organism,” a planetary person, arising from these universally active self-organizing forces. “Symbionomic” is his composite for the many facets of this scientific dynamical revolution, to designate this globally interrelational “emergence of collective intelligence.”

One of the great challenges of the modern world is the control and management of complexity. After the infinitely large and the infinitely small, we once again find ourselves confronting an unfathomable infinite—the infinitely complex. With its capability for simulation, the computer has become a macroscope. It helps us understand complexity and act on it more effectively to build and manage the large systems of which we are the cells—companies, cities, economies, societies, ecosystems. Thanks to this macroscope, a new vision of the world is emerging, based on a unified approach to the self-organization and evolution of complex systems. On the basis of this comprehensive vision, it becomes possible to describe the origin of a new form of life on Earth, a planetary macro-organism made up of human beings and machines, networks, and nations—a still-embryonic macro-organism that is trying to live in symbiosis with the planetary ecosystem. This new vision of the world brings together two complementary modes of analysis and action: the analytic method and the systemic approach. It can be called the unified theory of the self-organization and dynamics of complex systems.

More concisely, one can propose the term symbionomics to describe the range of phenomena covered by this unified theory. Symbionomics can be defined as the study of the emergence of complex systems through self-organization, self-selection, coevolution, and symbiosis. Symbiotic relationships form through coevolution with other organisms or organizations, and collective properties emerge. This information is transmitted to succeeding generations through the memorization of structures and reproductive and evolutionary mechanisms by means of chemical or electronic coding or by the culture. A complex organization is born. From a symbionomic perspective, it is then possible to trace the essential phases of the emergence of a new form of life on Earth, a macrolife, of which humanity, this time, is not the evolutionary end point, but the starting point and catalyst. (Abstract, 304)

De Wolf, Tom and Tom Holvoet. Emergence versus Self-organization. Brueckner, Sven, et al, eds. Engineering Self-Organizing Systems. Berlin: Springer, 2005. In a volume which seeks a scientific practice more in accord with a dynamically viable nature, Belgian computer scientists advise that this project need avail itself of a synthesis best informed by far-from-equilibrium complex adaptive systems.

del Moral, Raquel, et al. New Times and New Challenges for Information Science: From Cellular Systems to Human Societies. Information. Online February, 2014. With Jorge Navarro and Pedro Marijuán, Bioinformation and Systems Biology Group, Aragon Institute of Health Science, Zaragoza, Spain, researchers (search each) press their project to rethink evolutionary nature and culture by way of a cumulative knowledge gaining and sharing quality. Life’s development from cells to civilizations is then informed and tracked by an increasing factual content as “information flow systems.” To highlight the approach, a use “-omic” terms – genomics, proteomics, transcriptomics, metabolomics, culturomics, scientomics – is emphasized. The latter words are due to Marijuan (2012) by which to perceive human studies as genetic in kind. And in this view, we have a “knowledge crisis” with regard to saving the earth for we seem stuck at an individual level, without seeking or availing a global cognitive collaboration.

The extraordinary scientific-technical, economic, and social transformations related to the widespread use of computers and to the whole information and communication technologies have not been accompanied by the development of a scientific “informational” perspective helping make a coherent sense of the spectacular changes occurring. Like in other industrial revolutions of the past, technical praxis antedates the emergence of theoretical disciplines. Apart from the difficulties in handling new empirical domains and in framing new ways of thinking, the case of information science implies the difficult re-evaluation of important bodies of knowledge already well accommodated in specific disciplines. Herein, we will discuss how a new understanding of the “natural information flows” as they prototypically occur in living beings—even in the simplest cells—could provide a sound basis for reappraising fundamental problems of the new science. The role of a renewed information science, multidisciplinarily conceived and empirically grounded, widely transcends the limited “library” and knowledge-repositories mission into which classical information science was cajoled during past decades. (Abstract)

Rather, our basic proposal is the development of a new conception on information, biologically inspired, so that a new understanding might be gained on some unapproachable social themes of informational nature, such as the mentioned conjecture that the excess of “artificial” information flows could be interfering with the “natural” information flows and the bonding structures of social life. As we will propose herein, a new understanding of the “natural information flows” as they prototypically occur in living beings—even in the simplest cells — could provide a sound basis for discussing the most general problems of the new science. (104)

In terms of education science, something similar would happen, for an abridged recapitulation resembling Haeckel’s law seems to be taking place in the ontogenetic development of an individual’s knowledge, which somehow recapitulates the fundamentals of the social acquisition of knowledge along history. (114)

desJardins, Marie, et al. Introduction to the Special Issue on AI and Networks. AI Magazine. Fall, 2008. Studies over the past years with regard to scale-free, small-world linkages prompt reconsiderations of many AI realms such as Natural Language Processing, Peer-to-Peer Systems, Cooperative Multiagent Systems, the Blogosphere, along with similar gene regulatory, metabolic, neural, and social geometries. Typical papers are The Age of Analogy Networks by Claudio Mattiussi, et al, and The Fractal Nature of the Semantic Web by Tim Berners-Lee and Lalana Kagal (view herein). What one may surmise is a consistent recurrence, a universality, of the same patterns and processes across a wide phenomenal range, which is essentially cerebral and linguistic in kind.

Di Marzo Serugendo, Giovanna, et al, eds. Engineering Self-Organizing Systems. Berlin: Springer, 2004. As global networks become highly complex and interconnected, computer scientists are looking to emulate how nature creates and maintains a dynamic, emergent vitality and order. In this regard, the biological realm is seen as most characterized by multi-agent systems which locally interact to spontaneously form a modular organization.

Di Marzo Serugendo, Giovanna, et al, eds. Self-Organizing Software: From Natural to Artificial Adaptation. Berlin: Springer, 2011. As nonlinear science moves toward a mature synthesis, the ubiquitous presence of complex adaptive systems is seen as an innate guide for more viable, life-like computation. A group of editors and authors across Europe from the UK to Greece here explore “Natural Computing” in four sections: Main Concepts and Background, Self-Organizing Mechanisms, Engineering Artificial Self-Organizing systems, and Applications of Self-Organizing Software. And might we then imagine that a new genesis nature is beginning to consciously create itself by way of its human phenomenon?

In other works it has been found that many existing systems demonstrate self-organization, such as planetary systems, organic cells, living organisms and animal societies. Self-organizing systems are encountered in many scientific areas including biology, chemistry, geology, sociology and information technology, and considerable research has so far been undertaken to study them. (Di Marzo Serugendo, Giovanna, et al “Self-Organizing Systems,”)

Software systems are becoming ever more complex, as the capabilities of the software upon which they are based increase. To develop software that is manageable, we must look for novel sources of inspiration, rather than requiring an increasingly costly level of human support. Self-organising software suggests benefits in this direction, and this chapter focuses on a particularly relevant area of inspiration, that of natural systems. Indeed many natural systems are themselves self-organising, despite being often very complicated. We consider natural systems both in the context of non-living (mathematical, physical and chemical) and living (cellular, invertebrate and vertebrate, not excluding human beings) examples. We review some of the causal mechanisms and conditions that are fundamental to self-organisation in natural systems, such as: complexity, evolution, ecological interactions, animal behaviour, as well as the complexities of human behaviour, which has given us insights into phenomena such as small-world networks, epidemics, trust and gossip. (Paul Marrow and Jean-Pierre Mano “Self-organisation in Natural Systems Inspiring Self-organising Software,”)

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