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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. Earth Learns: Interactive Person/Planet, Self-Organizing, Daily Collaboratiions

Noriega-Campero, Alejandro, et al. The Wisdom of the Network: How Adaptive Networks Promote Collective Intelligence. arXiv:1805.04766. As many fields are presently involved in, a six person team from MIT and MPI Human Development including Alex Pentland make a case that an active network interconnectivity need be seen in equal effect along with and amongst group members. This heretofore unnoticed relational dynamic serves to achieve cognitive capacities beyond each individual, however smart. In regard, better group acumen and results can then be enhanced by an awareness and facility of this good vibes quality.

It is widely noted that our social embedding exerts strong influence on what information we receive, and how we form beliefs and make decisions. However, most studies overlook the dynamic nature of social networks, and its role in fostering adaptive collective intelligence. It remains unknown (1) how network structures adapt to the performances of individuals, and (2) whether this adaptation promotes the accuracy of individual and collective decisions. Here, we answer these questions through a series of behavioral experiments and simulations. Our results reveal that groups of people embedded in dynamic social networks can adapt to biased and non-stationary information environments. As a result, individual and collective accuracy is substantially improved over static networks and unconnected groups. Moreover, we show that groups in dynamic networks far outperform their best-performing member. Thereby, our findings substantiate the role of dynamic social networks as adaptive mechanisms for refining individual and collective judgments. (Abstract)

Ogushi, Fumiko, et al. Ecology in the Digital World of Wikipedia. arXiv:2105.10333. Systems scholars with postings in Japan, Austria, Finland, the UK and the USA describe a consistent, page rank metrical analysis which helps explain the build-in, self-corrective mechanisms that underlie the reliable success of this encyclopedic information resource. We again record this global brain-like accumulated knowledge repository, and wonder what by what phenomenal revolution can it be possible to perceive that it could be learning on its (her/his) own.

Wikipedia is a paradigmatic example of an online knowledge space. It is organized in a collaborative, bottom-up way with voluntary contributions, yet maintains a reliability comparable to that of traditional encyclopedias. Here we show that a self-consistent metrics for the network defined by the edit records explains the character of editors' activity and the articles' level of complexity. Using our metrics, one can better identify the high-quality, featured articles and separate them from the popular and controversial entries. We demonstrate that the collective effort of the editors indeed drives to the direction of article improvement. (Abstract excerpt)

After the invention of writing and printing we are witnessing the third communication revolution, which is digitally mediated and results in the omnipresent availability of what mankind has ever intellectually produced. Wikipedia, as the largest online encyclopedia, is a paradigmatic example of suxh a collective knowledge space that is based on “wisdom of crowds”. The successful model of Wikipedia, including the editing and organization of the articles, is based on a bottom-up, self-organized process of world-wide human creativity. Thus it is an appealing field of research due to its size, complex structure and because its full content and history is well documented and publicly accessible. (1)

Okamura, Keisuke. Atlas of Science Collaboration, 1971-2020. arXiv:2308.16810. We begin to post this 127 page contribution by an Institute for Future Initiatives, University of Tokyo scholar so it is available online. The topical Table of Contents goes from Artificial Intelligence, Quantum Science and Biotechnology to Earth Science, Astronomy to Pure Mathematics. Altogether, as the text often notes, the document strongly evinces the 21st century occasions of welling global collaborations.

The evolving landscape of interinstitutional collaborative research across 15 natural science disciplines is explored using the open data sourced from OpenAlex. This extensive exploration spans the years from 1971 to 2020, facilitating a thorough investigation of leading scientific output producers and their collaborative relationships based on coauthorships. The findings are visually presented on world maps and other diagrams, offering a clear and insightful portrayal of notable variations in both national and international collaboration patterns across various fields and time periods. These visual representations serve as valuable resources for science policymakers, diplomats and institutional researchers, providing them with a comprehensive overview of global collaboration and aiding their intuitive grasp of the evolving nature of these partnerships over time

This booklet, entitled ‘Atlas of Science Collaboration’, aims to offer a broad overview of international and interinstitutional research collaboration, shedding light on its present status and evolution on a global scale. It is meant as a valuable resource for those seeking a general understanding of the collaborative relationships that have been established between research institutions in the world of science.

Oliveira, Arlindo. The Digital Mind. Cambridge: MIT Press, 2017. The Instituto Superior Tecnico (IST), Lisbon, professor of computer science and IST president, has a 1994 doctorate from UC Berkeley. Akin to Cesar Hidalgo’s Why Information Grows (2015) and Yuval Hatari’s Homo Deus (2016), the work views life’s evolution to human nature as an emergent cognitive procession. By this track, a next phase may be synthetic intelligences, neuromorphic realities, and so on, aka as a technological singularity. We quotes from the author’s synopsis on his website, click on this book.

Although electronic computers are recent and have been around for only a few decades, they represent just the latest way to process information and create order out of chaos. Before computers, the job of processing information was done by living organisms, which are nothing more than complex information processing devices. Computers execute algorithms, sequences of small steps that, in the end, perform some desired computation. Evolution is, in itself, a complex and long- running algorithm that created all species on Earth. The most advanced of these species, Homo sapiens, was endowed with a brain that is the most complex information processing device ever devised. But brains also enabled humans to develop science and technology to a point where it is possible to design computers with a power comparable to that of the human brain. These digital minds may one day rival our own, become our partners and replace humans in many tasks. They may make humans obsolete and even a threatened species or they make us super-humans or demi-gods. (Edited excerpts)

Olsen, Gary, et al, eds. Scientific Collaboration on the Internet. Cambridge: MIT Press, 2008. Originating from the University of Michigan School of Information, an attempt to scope out science’s shift to such a worldwide electronic domain. Six parts with many authors discuss the 'collaboratory' vision, distributed research, the physical sciences, biological and health sciences, earth and environmental studies, and the developing world.

Omicini, Andrea, et al. The Multidisciplinary Patterns of Interaction from Sciences to Computer Science. Goldin, Dina, et al, eds. Interactive Computation. Berlin: Springer, 2006. A universality of self-organization via entities-in-relation gives rise to a globally informative intelligence. Such a dynamically creative nature can then provide an exemplary model for computational systems.

No matter if we are modeling the behavior of a human organization, the life of an intricate ecosystem, or the dynamics of a huge market-place, we can expect to find some repeated patterns, some shared schemes, some common laws that makes all these systems look similar when observed at the right level of abstraction. (396)

Palermos, S. Orestis. The Dynamics of Group Cognition. Minds & Machines. 26/4, 2016. A University of Edinburgh scholar who works at the intersection of epistemology, philosophy of mind, and cognitive science avails dynamic systems theory, as per the Abstract, to learn how human assemblies can actually take on a mind of their own. By these insights, in support of this website, an evolutionary emergence of local and global communicative groupings seem to initiate a new phase of collective knowledge above and beyond individual opinion, which we desperately need. The author is also a member of the “Extended Knowledge Project” at Edinburgh, see second quote.

The aim of this paper is to demonstrate that the postulation of irreducible, distributed cognitive systems (group minds) is necessary for the successful explanatory practice of cognitive science and sociology. Towards this end, and with an eye specifically on the phenomenon of distributed cognition, the debate over reductionism versus emergence is examined from the perspective of Dynamical Systems Theory (DST). Firstly, DST is particularly popular amongst cognitive scientists who work on modelling collective behaviors. Secondly, DST can deliver two distinct arguments in support of the claim that the presence of mutual interactions between group members necessitates the postulation of the corresponding group entity. Thirdly, DST can also provide a succinct understanding of the way group entities exert downward causation on their individual members. The outcome is a naturalist account of the emergent, and thereby irreducible, nature of distributed cognitive systems that avoids the reductionists’ threat of epiphenomenalism, while being well in line with materialism. (Abstract)

Extended Knowledge is a three-year project within Edinburgh’s department of Philosophy that studies the ramifications of the extended and distributed cognition hypotheses for epistemology: If cognition can extend beyond our brains and bodies to the artefacts we employ or–further–be distributed among several different individuals at the same time, then how (and to what extent) should we reconceive our thinking about knowledge and other related cognitive processes, such as learning and justification, which have traditionally been approached against an ‘intracranial’, individualist background? (Website excerpt)

Park, Kihong and Walter Willinger, eds. The Internet as a Large-Scale Complex System. Oxford: Oxford University Press, 2005. Proceedings of a Santa Fe Institute conference to consider the network properties and power-law connectivities of the worldwide web. For example, Computation in the Wild by Stephanie Forrest, et al and The Bio-Networking Architecture by Tatsuya Suda, et al describe natural evolutionary qualities which can serve as a model for its increasing viability and cognition. However Willinger, et al have recently taken issue with the wholesale apply of 'scale-free networks' in this regard in "Mathematics and the Internet" in Notices of the AMS for May 2009.

The Bio-Networking Architecture is inspired by the observation that the biological world has already developed mechanisms that are necessary for future network requirements such as self-organization, scalability, adaptation and evolution, security, and survivability. (Suda 251)

Pentland, Alex. On the Collective Nature of Human Intelligence. Adaptive Behavior. 15/2, 2007. An MIT Media Lab professor contends that individuals do not exist in lone isolation, but are enmeshed and engaged in myriad fluid social networks. He goes on to detail novel technologies that could enhance such distributed cognition.

Pfeifer, Rolf and John Bongard. How the Body Shapes the Way We Think. Cambridge: MIT Press, 2007. Actually a significant contribution to the field of artificial intelligence with regard to the design of robots based on evolutionary principles of self-organization, variation and selection. Sure, the brain can influence and control its soma but this vehicle will in turn in momentary, ontological and phylogenetic time frames constrain and enable reflective and anticipatory thought. As such complex systems are allowed to evolve, a responsive order can be seen to emerge. As agents thusly interact they serve to generate an emergent modular-based collective intelligence from cells to societies.

Pink, Daniel. The Book Stops Here. Wired. March, 2005. With an engagingly edgy style, the story of Wikipedia, the free self-organizing, repairing, policing, online encyclopedia that anyone can contribute to or edit. Which surely looks like a global cerebral learning enterprise. How can we then imagine all these efforts achieving their own composite, salutary knowledge?

Provencal, Yvon. The Mind of Society. New York: Gordon & Breach, 1998. An innovative study based on the work of Marvin Minsky and Pierre Teilhard de Chardin of human society as a superorganism with its own physiology, cerebration and self-consciousness. In this view, a close agreement is recorded in Piaget’s nomenclature between a child’s cognitive experience and the education of humanity.

The conceptual correspondence between cerebral mechanisms of perception and the collective mechanisms of scientific discovery can be seen in striking detail. (40) The analogical method used here requires that we consider global human society, which is undergoing rapid change, as a self-organizing structure similar to a young child’s brain. (49)

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