II. Pedia Sapiens: A Planetary Progeny Comes to Her/His Own Actual Factual Twintelligent Knowledge

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

Babaoglu, Ozalp, et al, eds. Self-star Properties in Complex Information Systems. Berlin: Springer, 2005. Intricate computer networks such as the world wide web gain enhanced utility and responsiveness if they are founded on innate abilities to continually configure, organize, manage, and repair themselves, thus the term Self-star. Such features are seen to reflect widespread natural phenomena, which further includes cooperation, a self-awareness vector, emergent thinkers, evolutionary games, and so on.

Bak-Coleman, Joseph, et al. Stewardship of Global Collective Behavior.. Proceedings of the National Academy of Sciences. 118/27, 2021. Eighteen international authorities including Mirta Galesic, Iain Cousin, Carl Bergstrom and Jonathan Donges call attention to the 2020s intense worldwide infosphere which so influences what people may know and think. But at present there is little or no managerial guidance as to relative truth or consequences. An approach is scoped out so to respectfully factor in, and better coordinate. On the TV last night, news items raced from a Vancouver heat dome, Mozambique drought, Chinese communism, Belarus protests, and so on, which brings much despair and dread. This resource site tries to document and foster to such a common cooperation, purpose and ecovillage to ecoworld response.

Collective behavior provides a framework for understanding how the actions and properties of groups emerge from the way individuals generate and share information. In humans, information flows were initially shaped by natural selection yet are increasingly structured by emerging communication technologies. Our larger, more complex social networks now transfer high-fidelity information over vast distances. The rise of digital social media has accelerated changes to our social systems, with poorly understood consequences. This gap in our knowledge presents a challenge to scientific progress, democracy, and actions to address global crises. We argue that the study of collective behavior must rise to a “crisis discipline” just as medicine, conservation, and climate science. (Abstract)

Baker, Stephen. Google and the Wisdom of Clouds. Business Week. December 24, 2007. Making money is a side effect of this socially responsible company which wants to vastly increase the computer power and utility accessible to any user. ‘Cloud’ is their term for great numbers of interlinked, low cost servers, which can crunch much more data than a single PC. See also later BW articles by Steve Hamm: "Cloud Computing" for April 24, 2008, and "How Cloud Computing is Changing the World" by Rachael King on August 4, 2008. But one wonders when, by what imagination, it will take to realize the correct metaphor is actually ‘brain.’

Barabasi, Albert-Laszlo. Network Theory – the Emergence of the Creative Enterprise. Science. 308/639, 2005. A commentary on a detailed study in the same issue (Roger Guimera, et al. 697-702) finds that science has now moved from lone investigators (Newton, Darwin) to international consortiums involving a great many researchers. Their dynamic interrelation can then be modeled by the same principles that occur from protein webs to the Internet. What is going on, I add, seems an historic shift and ascent to a worldwide cognitive capacity beginning to attain its own knowledge. Such an integral evolutionary transition promises to join many contributions and fields into a salutary discovery, which is the working basis of this website.

Traditionally, the achievements of individuals such as Darwin and Einstein have dominated the public’s image of science, yet today some of the most groundbreaking work is collaborative in nature. (639) Indeed, the size of collaborative teams is increasing, turning the scientific enterprise into a densely interconnected network whose evolution is driven by simple universal laws. (640) By demonstrating that the Web, the cell, or society is driven by similar organizing principles, network theory offers a successful conceptual framework to approach the structure of many complex systems. (641)

Barabasi, Albert-Laszlo. The Architecture of Complexity: The Structure and the Dynamics of Networks, from the Web to the Cell. Grossman, Robert, et al, eds. Proceedings of the Eleventh SIGKDD International Conference on Knowledge Discovery and Data Mining. Boston: ACM Press, 2005. A typical example of the many professional meetings each year on every continent as part of intense efforts to develop the full capacity of a global cerebral realm. Physicist Barabasi again notes the deep affinities amongst all realms of an awakening natural genesis.

Networks with complex topology describe systems as diverse as the cell, the World Wide Web or the society. The emergence of most networks is driven by self-organizing processes that are governed by simple but generic laws. The analysis of the cellular network of various organisms shows that cells and complex man-made networks, such as the Internet…and many social and collaboration networks share the same large-scale topology. (3)

Barlow, Horace. The Nested Network of Brains and Minds. Gregory Bock and Jamie Goode, eds. The Limits of Reductionism in Biology. New York: Wiley, 1998. A complex systems view reveals similarities between cognitive architecture and human societies.

Bentley, Alexander and Herbert Maschner. Avalanche of Ideas. Bentley, Alexander and Herbert Maschner, eds. Complex Systems and Archaeology. Salt Lake City: University of Utah Press, 2003. A preamble contends that while most scale-free network studies look for spatial patterns, an important temporal factor can also be observed. An application is then made to cultural concepts or ideas, which are seen to spread by the same self-similar, branching fractal growth as branching rivers or neural networks.

Bentley, R. Alexander, and Michael O’Brien. Cultural Evolutionary Tipping Points in the Storage and Transmission of Information. Frontiers in Psychology. December, 2012. University of Bristol, UK, and University of Missouri anthropologists move from archaeologist Gordon Childe’s 1950s civilizational scale and Malcolm Gladwell’s popular societal transitions to view an episodic rise, repository, and consolidation of collective human knowledge capacity and its effective avail. An increasing rate of shared communication and conveyance is a significant aspect.

Human culture has evolved through a series of major tipping points in information storage and communication. The first was the appearance of language, which enabled communication between brains and allowed humans to specialize in what they do and to participate in complex mating games. The second was information storage outside the brain, most obviously expressed in the “Upper Paleolithic Revolution” – the sudden proliferation of cave art, personal adornment, and ritual in Europe some 35,000–45,000 years ago. More recently, this storage has taken the form of writing, mass media, and now the Internet, which is arguably overwhelming humans’ ability to discern relevant information. The third tipping point was the appearance of technology capable of accumulating and manipulating vast amounts of information outside humans, thus removing them as bottlenecks to a seemingly self-perpetuating process of knowledge explosion. Important components of any discussion of cultural evolutionary tipping points are tempo and mode, given that the rate of change, as well as the kind of change, in information storage and transmission has not been constant over the previous million years. (Abstract)

Bentley, Sarah. Knowing you know nothing in the age of generative AI.. Humanities & Social Sciences Communications. March 10, 2025. In this Nature journal, a psychologist at the University of Queensland, Commonwealth Scientific and Industrial Research Organization and a Responsible and Inclusive AI Women Winner 2024, posts an expansive survey that first reviews an historical context of learning methods from Greece to paper text to the digital internet. With this in place, the article carefully considers ways that a practical reciprocity of human persons and algorithmic agents, once again, might be achieved going forward. Our interest then extends to such a properly arranged global presence whom can gain salutary discovers on her/his own.

Generative AI is a revolutionary new technology whose impact promises to democratize knowledge. And yet, unlike the printing press, which served to amplify one voice to many, Gen AI reduces many voices to one. My Comment situates this novel resource within the evolutionary context of human information dissemination and knowledge production. Whilst noting its extraordinary potential, I propose that since factual cognitive content is such a valuable asset we should be applying it to better understand the impact of AI-mediated informational inputs on both personal and planetary welfare. (Abstract)

Not wishing to negate the enormous potential of generative AI, nor dampen its enthusiastic uptake, it would seem wise at this early point to evaluate the trending tendency to farm out our knowledge practices to this latest wave of technological hyperactivity. Given the value that we peoples place on relative know-how and the role it plays in education, innovation, societal ambience, an understanding of the impact of these new worldwide tools on—both quantitative and qualitative—would seem in order. (5)

Berman, Fran, et al, eds. Grid Computing – Making the Global Infrastructure a Reality. Chichester, UK: Wiley, 2003. A large volume on the many aspects of an enveloping worldwide computer network as if a planetary nervous system. By this novel capacity, an immense flow of information coming from many areas such as bioinformatics, earth systems, climate, astronomy can handled, organized and made accessible to everyone. A typical paper in this regard is “The Data Deluge: an e-Science Perspective.” by Tony Hey and Anne Trefethen.

Berners-Lee, Tim. Weaving the Web. San Francisco: HarperSanFrancisco, 1999. The inventor of the Internet finds it to express a fractal self-similarity as exponentially growing networks take on the emergent properties of a global brain.

Berners-Lee, Tim and Lalana Kagal. The Fractal Nature of the Semantic Web. AI Magazine. Fall, 2008. MIT computer scientists (Berners-Lee is the founder of the worldwide web) contend that since the rest of natural and indeed social reality exemplifies a nested, recurrent, self-similarity, so also should the global Internet. Indeed it already can be seen to be so structured to a good extent. The endeavor to design and facilitate better operating ontologies should then further embrace this effective, organic geometry.

The semantic web is a set of standards for knowledge representation and exchange that is aimed at providing interoperability across applications and organizations. We believe that the gathering success of this technology is not derived from the particular choice of syntax or of logic. Its main contribution is in recognizing and supporting the fractal patterns of scalable web systems. (29) In this article we discuss why fractal patterns are an appropriate model for web systems and how semantic web technologies can be used to design scalable and interoperable systems. (29) The inherent fractal nature of language and culture in human societies leads us to expect the semantic web to demonstrate the self-similar patterns of fractals. (29)

Human society is made up of a fractal tangle of overlapping communities and cultures. We expect the same fractal patterns to appear in scalable web systems within which information will be composed of terms from different ontologies – global, community specific, and local. (34)

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