II. Planetary Prodigy: A Global Sapiensphere Learns by Her/His Self
C. Mindkind Sapiensphere: WorldWise Collective Intelligence
Mayer-Kress, Gottfried and Cathleen Barczys. The Global Brain as an Emergent Structure from the Worldwide Computing Network. The Information Society. 11/1, 1995. From a neuroscience perspective, the Internet seems to be developing and functioning in a similar way as a human brain.
Invoking concepts from complexity science, we can view both the cognitive abilities of the biological brain and the problem-solving capabilities of the Global Brain as other levels of capability that emerge from this interconnected system once the system is sufficiently complex. (5) Thus a Global Brain derived from a complex information and communications network composed of people and computers would be able to sense and respond to the world outside that network as well as within that network, with abilities that would be analogous to our brain’s abilities but would surpass them. (8)
Menary, Richard, ed. The Extended Mind. Cambridge: MIT Press, 2010. An effort to gather between covers this academic surmise that mental activities somehow draw upon and exist in somatic, environmental and communal realms beyond the cerebral brain.
Indianapolis: Que Publishing,
The welling revolution from desktop PCs to remote, vastly interlinked servers, as if “clouds” of computation, will much change the industry. Here is one of the first volumes to explain the lineaments and values of such peer-to-peer, distributed collaboration.
Michel, Jean-Baptiste, et al. Quantitative Analysis of Culture Using Millions of Digitized Books. Science. 331/176, 2011. An interdisciplinary Harvard University team including Martin Nowak, Erez Liberman Aiden, Steven Pinker, and Yuan Kui Shen scope out a project to read all the books at once, as if a collective corpus of worldwide humankind. And it should be noticed that the authors coin an “-omics” term - does this imply it is all somehow “genetic” in instructive kind?
We constructed a corpus of digitized texts containing about 4% of all books ever printed. Analysis of this corpus enables us to investigate cultural trends quantitatively. We survey the vast terrain of ‘culturomics,’ focusing on linguistic and cultural phenomena that were reflected in the English language between 1800 and 2000. We show how this approach can provide insights about fields as diverse as lexicography, the evolution of grammar, collective memory, the adoption of technology, the pursuit of fame, censorship, and historical epidemiology. Culturomics extends the boundaries of rigorous quantitative inquiry to a wide array of new phenomena spanning the social sciences and the humanities. (Abstract)
Michelucci, Pietro. Human Computation and Convergence. arXiv:1503.05959. A chapter for the forthcoming Handbook of Science and Technology Convergence (Springer, 2016) by the director of the Human Computation Institute (Washington, DC), editor of the Handbook of Human Computation (Springer, 2014), with a doctorate in Cognitive Science from Indiana University. Search Dirk Helbing for a similar European take. These movements are generally meant to enhance person-device, computer plus, capabilities, as if complementary right and left brain, so that their implementation can help solve ultra complex social and environmental problems for a better, safer, sustainable world.
Humans are the most effective integrators and producers of information, directly and through the use of information-processing inventions. As these inventions become increasingly sophisticated, the substantive role of humans in processing information will tend toward capabilities that derive from our most complex cognitive processes, e.g., abstraction, creativity, and applied world knowledge. Through the advancement of human computation - methods that leverage the respective strengths of humans and machines in distributed information-processing systems - formerly discrete processes will combine synergistically into increasingly integrated and complex information processing systems. These new, collective systems will exhibit an unprecedented degree of predictive accuracy in modeling physical and techno-social processes, and may ultimately coalesce into a single unified predictive organism, with the capacity to address societies most wicked problems and achieve planetary homeostasis. (Abstract)
Miorandi, Daniele, et al. Social Collective Intelligence. Berlin: Springer, 2014. The subtitle for this eclectic collection is Combining the Powers of Humans and Machines to Build a Smarter Society. Typical chapters are A Taxonomic Framework for Social Machines, Interface Design in Massive Open Online Courses, Computational Epidemiology, and Social Collective Awareness in Socio-Technical Urban Superorganisms.
The book focuses on Social Collective Intelligence, a term used to denote a class of socio-technical systems that combine, in a coordinated way, the strengths of humans, machines and collectives in terms of competences, knowledge and problem solving capabilities with the communication, computing and storage capabilities of advanced ICT.
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)
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.