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

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

Wagner, Caroline and Loet Leydesdorff. Network Structure, Self-Organization, and the Growth of International Collaboration in Science. Research Policy. 34/10, 2005. George Washington University and University of Amsterdam scholars achieve a prescient understanding of the sudden shift of our human pursuit of knowledge to an integral global phase by way of these complex systems theories. Worldwide researchers can now be instantly aware of what everyone else is doing, and in this discourse tend to organize themselves into vast, interlaced network topologies. In regard, one might add that this dynamic phenomena indeed appears as a neural-like connectome, quite taking on a life and mind of its own.

Different approaches have been used to analyse international collaboration in science but none can fully explain its rapid growth. Using international co-authorships, we test the hypothesis that international collaboration is a self-organising network. Applying tools from network analysis, the paper shows that the growth of international co-authorships can be explained based on the organising principle of preferential attachment, although the attachment mechanism deviates from an ideal power-law. Several explanations for the deviation are explored, including that of the influence of institutional constraints on the mechanism of self-organisation. (Abstract)

Wallace, Rodrick and Mindy Fullilove. Collective Consciousness and Its Discontents. New York: Springer, 2008. New York State Psychiatric Institute clinical researchers extend Bernard Baars’ Global Workspace Theory of cerebral consciousness to social and institutional domains in the guise of an emergent distributed cognition arising from many individual contributions. With this mathematical qualification in place, the authors demonstrate its application to real world disease pathologies such as HIV virus AIDS epidemics.

Wang, Yingxu, et al. On the Philosophical, Cognitive and Mathematical Foundations of Symbiotic Autonomous Systems. Philosophical Transactions of the Royal Society A. August, 2021. In a special issue on this advance (see Kaynak), 15 multinational researchers (Y. Wang is a senior authority now based in Canada) scan the breadth and depth of this global frontier as multiplex Earthuman computational webworks increasingly form and take on a lively cerebral intelligence and informational content of their own.

Symbiotic Autonomous Systems (SAS) are advanced intelligent and cognitive systems exhibiting a self-organized collective intelligence enabled by coherent symbiosis of human-machine interactions. The emerging field of SAS has developed general AI technologies which function without human intervention and hybrid cognitive synergies between humans and intelligent machines. Here we look at a theoretical framework for SASs based on the latest advances in intelligence, cognition, computer, and system sciences which adopt bio-brain-social-inspired and autonomous behaviors. (Abstract abstract)

Symbiosis is a widely observable phenomenon in biological, mental, and social systems where mutual dependences exist among plants, animals, and human societies as a necessary condition for them to co-evolve. Symbiosis is particularly important to human societies because of the fundamental need for extending individuals’ physical, intellectual, and/or resource limits. Therefore, it becomes a fundamental principle of system science and the universal context of modern sciences and engineering. (3)

Watson, Richard and Michael Levin. : The Collective Intelligence of Evolution and Development. Collective Intelligence. May, 2023. The University of Southampton computer scientist and the Tufts University polybiologist (search each) join a decade of their innovative studies so to span life’s newly appreciated scalar, processional emergence with an especial emphasis on a cerebral advance via proactive behavior. See the Intelligence Evolution and Vital Knowledge Gain section in Chap. VI for prior studies in support of this 2023 integral panorama. As a consequence, a steady, nested recurrence from a minimum cognition all the way to our global sapience (as this new journal and section records) can now sketch a universal, invariant sequence of group size collectivity of better neural net brains, enhanced cognizance and accumulated knowledge.

In significant regard, some twenty years since this annotated anthology by way of a novel worldwise personsphere can receive its whole scale evident veracity. See also Bioelectric Netwoks: The Cognitive Glue Enabling Evolutionary Scaling from Physiology to Mind by Michael Levin in Animal Cognition (May 2023) for a companion essay.

Collective and individual intelligence are usually considered to be fundamentally different. An individual mode occurs in organisms with certain neural faculties evolved by natural selection to enable cerebral experience that benefit fitness. Collective intelligence, in contrast, has often been an ambiguous debate. Here, we use examples from a consistent evolutionary and developmental morphogenesis to argue for and expand existing models of individual cognition and learning as a framework for collective intelligence, such as connectionist aspects by way of neural networks. We discuss how specific features of these models inform the necessary and sufficient conditions for collective intelligence, and identify current knowledge gaps as opportunities for future research. (Abstract excerpt)

All individuals are collective: They are made of parts that used to be individuals themselves. This is true not only for multicellular organisms derived from unicellular ancestors but also for eukaryotic cells with multiple organelles arising from bacterial ancestors, and for simpler cells that contain the first chromosomes arising from the union of previously free-living self-replicating molecules.(2)

All intelligences are collectives: Individual intelligence, in the familiar guise of a central nervous system or a brain, arises from the interaction of many unintelligent components (neurons) arranged in the right organisation with the right connections. This is the foundation of connectionism; that intelligence resides not in the individual parts but in the arrangement of the connections between them. (2)

Organisms as collective intelligences: All organisms by way of development and basal cognition are collectives at multiple levels: from active molecules in a cell, to cells in a multicellular tissue, to a whole soma self. What makes these anatomy and physiology assemblies become a multicellularity is their intelligence – their degree of competency in solving novel problems. The processes of development are the substrate of this intelligence – the “glue” that makes the whole more than the sum of the parts. (4)

Commonalities between cognitive and evolutionary processes and those that shape growth and form have been hinted at in the past. We argue that conceptual advances in the links between machine learning and evolution now provide quantitative formalisms with which to begin to develop testable models of collective intelligence across life’s scalar stages. From subcellular processes to cellular swarms during morphogenesis to ecological dynamics on evolutionary timescales – all these processes are driven by a sequence of reward dynamics that bind subunits into higher wholes that better navigate, survive and learn. (15)

Wegner, Daniel and Adrian Ward. How Google is Changing Your Brain. Scientific American. December, 2013. A senior Harvard University psychologist and postdoc student now at the University of Colorado wonder and worry over the sudden epochal shift from “for millennia humans have relied on one another” to “now we rely on the cloud.” See also a commentary by Ward on “Social Cognition in the Internet Age” in a special issue of Psychological Inquiry (24/4, 2013). But the further implied dimension of this capacity of a true worldwise Brain learning on her/his Own still eludes.

Yet perhaps as we become parts of the “Intermind,” we will also develop a new intelligence, one that is no longer anchored in the local memories that are housed only in our own brains. As we are freed from the necessity of remembering facts, we may be able as individuals to use our newly available mental resources for ambitious undertakings. And perhaps the evolving Intermind can bring together the creativity of the individual human mind with the Internet’s breadth of knowledge to create a better world – and for the set of messes we have made so far. (61)

Wehner, Stephanie, et al. Quantum Internet: A Vision for the Road Ahead. Science. 362/eaam9288, 2018. QuTech, Delft University of Technology computer physicist provides a technical review and update on the highway to this supercharged noosphere. See also an interview To Invent a Quantum Internet by Natalie Wolchover in Quanta (September 25, 2019), and Towards Large-Scale Quantum Networks by SW and Wojiech Kozlowski at arXiv:1909.08396.

The internet—a vast network that enables simultaneous long-range classical communication—has had a revolutionary impact on our world. The vision of a quantum internet is to fundamentally enhance internet technology by enabling quantum communication between any two points on Earth. Such a quantum internet may operate in parallel to the internet that we have today and connect quantum processors in order to achieve capabilities that are provably impossible by using only classical means. Here, we propose stages of development toward a full-blown quantum internet and highlight experimental and theoretical progress needed to attain them. (Abstract)

Weiss, Aaron. The Power of Collective Intelligence. netWorker. September, 2005. A survey of the evolving Internet as its density of interconnections and upgraded protocols portend a global cognitive noosphere.

With ever more sophisticated APIs (Application Programming Interface) and Web services being shared, attracting a critical mass of developers to build tools on these services, and a critical mass of users contributing to the services’ value by aggregating shared knowledge and content, we have the makings of a truly collaborative, self-organizing platform. (23)

Woolley, Anita, et al. Evidence for a Collective Intelligence Factor in the Performance of Human Groups. Science. September 30, 2010. Carnegie Mellon, Union College, and MIT organizational scientists are able to identify the reality of group-wide cognitive abilities, long predicted but here finally quantified. As picked up by the media, a vital feature proved to be feminine, cooperative, empathic members. Thus is achieved, one might add, a “bicameral” balance. Otherwise, all men would just argue and attain, say, a collective stupidity.

Psychologists have repeatedly shown that a single statistical factor—often called "general intelligence"—emerges from the correlations among people's performance on a wide variety of cognitive tasks. But no one has systematically examined whether a similar kind of "collective intelligence" exists for groups of people. In two studies with 699 individuals, working in groups of two to five, we find converging evidence of a general collective intelligence factor that explains a group's performance on a wide variety of tasks. This "c factor" is not strongly correlated with the average or maximum individual intelligence of group members but is correlated with the average social sensitivity of group members, the equality in distribution of conversational turn-taking, and the proportion of females in the group.

Wurtz, Rolp, ed. Organic Computing. Berlin: Springer, 2008. As a genesis nature sequentially emerges, as computer technology evolves from incipient PCs to their global integration, our planet earth appears to be gaining a true super-organic cerebral faculty, a brain. Various chapters here explore efforts to intentionally recreate the worldwide web into a biological viability by way of essential self-organizing, nonlinear principles. Typical papers are Organic Computing and Complex Dynamical Systems by Klaus Mainzer, Evolutionary Design of Emergent Behavior by Jurgen Branke and Hartmut Schmeck, and Organically Grown Architectures by Rene Doursat.

Organic computer systems with life-like structure are advocated as a way to handle the increasingly complex adaptive systems created by engineer and computer scientists. Consisting of a large number of dynamically interacting components, these systems exhibit emergent global behavior, which is not deducible from the local actions of a single component. (Branke, Schmeck 136)

Yang, Vicky and Anders Sandberg. Collective Intelligence as Infrastructure for Reducing Global Catastrophic Risks. arXiv:2205.03300. Santa Fe Institute and Oxford University, Future of Humanity Institute scholars open this posting by noting how all manner of groupings from cerebral function, fish schools, wildebeest herds, onto political elections can be seen as a natural propensity to form viable associations. By extension, it would be to our advantage if this process could be intentionally availed to serve our own survivability. See also Adaptive Social Networks Promote the Wisdom of Crowds by Almaatouq, A., et al in PNAS (117/21, 2020).

Academic and philanthropic endeavors have grown concerned with global catastrophic risks (GCRs) such as artificial intelligence safety, pandemics, biosecurity, and nuclear war. Study and resolution efforts often depend on the performance of human meetings, which can be seen to involve Collective Intelligence (CI) agendas. CI is a transdisciplinary perspective, whose application involves animal groups, economic markets, collections of neurons, and other distributed systems. Here we argue that better CI methods can improve general resilience against a wide variety of risks. GCR researchers can benefit from engaging more with behavioral researchers to impact critical social issues by engaging and enhancing these transdisciplinary efforts. (Abstract excerpt)

Yassini, Rouzbeh. Planet Broadband. Indianapolis: Cisco Press, 2003. Yes, a book from Cisco Systems which along with some hype shows how a “high-speed, always-on connectivity to an interactive digital network” is facilitating a global sphere of ubiquitous communication, information and accessible knowledge.

Yong, Tao and Didier Sornette. Emerging Social Brain: A Collective Self-Motivated Boltzmann Machine. Chaos, Solitons and Fractals. 143/February, 2021. A Southwest University, Chongqing, China scholar and the veteran ETH Zurich systems economist consider ways that cerebral and cognitive qualities could be seen as presently forming out of a range of human activities. See also Life as a Self-Referential Deep Learning System by Yong Tao also in Biosystems (February 2021).

Boltzmann machines are unsupervised-learning neural networks, which have contributed to deep learning architectures. Theoretically, we show that the emergence of a Boltzmann-like income distribution in a society of optimizing agents reflects the spontaneous organization of a human society wherein each person plays a role analogous to that of a neuron within a brain-like architecture. Empirically, we investigate the household income data from free-market countries and find that the income structure for low and middle classes holds to a Boltzmann-like distribution. We thus suggest that social networks are going through a critical evolution to a kind of brain-like structure. (Abstract excerpt)

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