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

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

Mones, Enys, et al. Universal Hierarchical Behavior of Citation Networks. Journal of Statistical Mechanics. P05023, 2014. Budapest systems biophysicists with Tamas Vicsek describe how this “accumulation of knowledge” is another exemplar of nature’s ubiquitous dynamic structuring into complex, nested, invariant nets. One might imagine, by an affinity with cerebral connectomes, that a similar worldwide brain, a noosphere, is in formation. And compare with Modeling Leadership Hierarchy in Multilevel Animal Societies by Ozogany (search) and Vicsek for a similar instance.

Many of the essential features of the evolution of scientific research are imprinted in the structure of citation networks. Connections in these networks imply information about the transfer of knowledge among papers, or in other words, edges describe the impact of papers on other publications. This inherent meaning of the edges infers that citation networks can exhibit hierarchical features, that is typical of networks based on decision-making. In this paper, we investigate the hierarchical structure of citation networks consisting of papers in the same field. We find that the majority of the networks follow a universal trend towards a highly hierarchical state, and i) the various fields display differences only concerning their phase in life (distance from the "birth" of a field) or ii) the characteristic time according to which they are approaching the stationary state. (Abstract)

Morales, Alfredo, et al. Global Patterns of Synchronization in Human Communications. Journal of the Royal Society Interface. Online March, 2017. New England Complex Systems Institute (Morales, Vaibhav Vavilala, Yaneer Bar-Yam) and Universidad Politecnica de Madrid (Rosa Benito) systems scientists use the latest cyber-analysis techniques to distill intrinsic complex coordinations by way of pervasive social media. The second quote is from a NECSI email about a talk in Boston with cites this work.

Social media are transforming global communication and coordination and provide unprecedented opportunities for studying socio-technical domains. Here we study global dynamical patterns of communication on Twitter across many scales. Underlying the observed patterns is both the diurnal rotation of the earth, day and night, and the synchrony required for contingency of actions between individuals. We find that urban areas show a cyclic contraction and expansion that resembles heartbeats linked to social rather than natural cycles. Different urban areas have characteristic signatures of daily collective activities. We show that the differences detected are consistent with a new emergent global synchrony that couples behavior in distant regions across the world. Although local synchrony is the major force that shapes the collective behavior in cities, a larger-scale synchronization is beginning to occur. (Abstract)

On March 30, 2017 there will be a special presentation by senior postdoctoral researcher Alfredo J. Morales. Titled "The Science of Human Collective Behavior Using Twitter," it will cover structural and dynamical patterns of social systems revealed through the analysis of data from social media like Twitter. Morales uses complex systems science to retrieve important information from Big Data produced by a globally-tweeting civilization. Tweets can reveal unstructured patterns of social behavior across multiple scales, ranging from the daily routines of individuals up to the collective pulse of activities within cities and global networks of communication and synchronicities that can span hemispheres. (NECSI)

Muller-Scholer, Christian, et al, eds. Organic and Pervasive Computing. Berlin: Springer, 2004. Computer and system architectures are becoming more animate in kind as they gain capabilities of adaptive self-organization.

Organic Computing investigates the design and implementation of self-managing systems that are self-configuring, self-optimizing, self-healing, self-protecting, context aware and anticipatory. (Preface)

Muthukrishna, Michael and Joseph Henrich. Innovation in the Collective Brain. Philosophical Transactions of the Royal Society B. Vol.371/Iss.1690, 2016. Harvard University, Human Evolutionary Biology scholars (MM now at London School of Economics) advance a strong argument that human small and larger assemblies and collaborations could actually attain their own intelligent, information processing creativity. While this ought to be obvious (search David Christian and Matt Ridley, e.g.), our cultural mindset of no abiding, procreative reality by itself blocks this view. This sourcebook website quite simply based on this premise that a nascent humankinder is now learning and discovering on her/his sapiensphere own. See also Henrich’s 2016 work The Secret of Our Success for much more.

Innovation is often assumed to be the work of a talented few, whose products are passed on to the masses. Here, we argue that innovations are instead an emergent property of our species' cultural learning abilities, applied within our societies and social networks. Our societies and social networks act as collective brains. We outline how many human brains, which evolved primarily for the acquisition of culture, together beget a collective brain. Within these collective brains, the three main sources of innovation are serendipity, recombination and incremental improvement. We argue that rates of innovation are heavily influenced by (i) sociality, (ii) transmission fidelity, and (iii) cultural variance. For example, we provide preliminary evidence that transmission efficiency is affected by sociality—languages with more speakers are more efficient. (Abstract)

Newman, Harvey, et al. The UltraLight Project: The Network as an Integrated and Managed Resource for Data-Intensive Science. Computing in Science & Engineering. November/December, 2005. The international high energy physics community is assembling an interlinked computational grid to process and share vast data-sets. With similar efforts in other fields such as climate change, as Albert Barabasi, et al (Science. 308/639, 2005) observes, the human scientific endeavor is in transition to a new global cerebral capacity.

Nolte, David. Mind at Light Speed: A New Kind of Intelligence. New York: The Free Press, 2001. The future of optical, holographic, and quantum computers and worldwide communications presage an immense expansion of human mental abilities.

Norgaard, Richard. Learning and Knowing Collectively. Ecological Economics. 49/2, 2004. The University of California at Berkeley environmental scientist contends that the challenges of climate change and many other systemic issues will require a new mode of intentional, global collaboration. The many disciplines and specialties can no longer proceed in isolation. A common epistemology, language and modeling approach is vital so we can learn and act in effective concert.

Norgaard, Richard and Paul Baer. Collectively Seeing Complex Systems. BioScience. 55/11, 2005. In a Special Roundtable Section with several articles, Norgaard, University of California at Berkeley and Baer, Stanford University, continue their efforts, in collaboration with the Millennium Ecosystem Assessment team, to implement a new understanding of science and policy as a collective seeing, learning, and judgment, a distributed cognitive network. Only by such interdisciplinary social syntheses can ultra complex issues as global climate change be addressed.

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)

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