III. Ecosmos: A Revolutionary Fertile, Habitable, Solar-Bioplanet, Incubator Lifescape

C. The Information Computation Turn

Marshall, William, et al. Black-Boxing and Cause-Effect Power. arXiv:1608.03461. With Larissa Albantakis and Giulio Tononi, University of Wisconsin psychologists expand upon the Tononi’s popular Integrated Information theories, with many colleagues, to argue that a reductive method to study physical substrates is ever inadequate. Rather by these lights, natural, Earthly evolution seems distinguished by a progressive tendency toward and increase of informational, knowledgeable qualities. A companion paper is Quantifying Causal Emergence Shows that Macro can Beat Micro by Erik Hoel with Albantakis and Tononi (PNAS110/19790, 2014).

McQuillan, Dan. Data Science as Machinic Neoplatonism. Philosophy and Technology. Online August, 2017. As a way to appreciate and avail this late version of an immanate source code, a Goldsmiths, University of London lecturer on creative and social computing reaches across the millennia to its perennial witness, as the quotes cite. An original glimpse came from Greek sages who indeed saw worldly abidance as such a double domain. A deep informative cause and exemplary world continued over the centuries into the Renaissance of Copernicus, Galileo, and Newton (search Margaret Cavendish for a “vitalistic materialism”). The author’s aim is to rescue this algorithmic scheme from a mechanical sterility unto a “machine learning for the People” via “participatory agency.”

Data science is not simply a method but an organising idea. Understanding data science requires an appreciation of what algorithms actually do; in particular, how machine learning learns. But attempts to stem the tide have not grasped the nature of data science as both metaphysical and machinic. Data science strongly echoes the neoplatonism that informed the early science of Copernicus and Galileo. It appears to reveal a hidden mathematical order in the world that is superior to our direct experience. But a counterculture of data science must be material as well as discursive. Karen Barad’s idea of agential realism can reconfigure data science to produce both non-dualistic philosophy and participatory agency. (Abstract excerpts)

What would it mean to say that data science is neoplatonic? The philosophical school of Platonism is committed to a two-world metaphysics. Behind the world of the sensible, that which we experience through our senses, is the world of Form or the Idea. (7-8) As such, the world of the Idea is ontologically superior to the one we actually inhabit. For Plato and the neoplatonists, mathematics is the linimal realm between the imperfect and transitory world of the senses and the perfect and eternal of pure spirit. Mathematical relations concerning triangles and circles, for example, are true independently of any particular triangle or circle. (8)

Mediano, Pedro, et al. Greater than the Parts: A Review of the Information Decomposition Approach to Causal Emergence. arXiv:2111.06518. Eight senior systems theorists from the UK, USA and Canada including Henrik Jensen, Anil Seth and Fernando Rosas expand and deepen our Earthuman frontiers of discovering, quantifying and articulating the presence of a universal, independent, manifestly exemplified generative domain at each and every ecosmic scale and instance. A latest finesse of integrated information theory provides a mathematical measure whence the same form and flow, pattern and process of common node/link, entity/group complements repeats in kind. Key cases are cellular automata, bird flocks, and cerebral cognition, which is then dubbed a “causal emergence.” Albeit a highly technical work, a similar reality with a likeness to genotype and phenotype gains vital credence. See also Beyond Integrated Information: A Taxonomy of Information Dynamics Phenomena by this collegial team at 1909.02297.

Emergence is a profound subject that straddles many scientific disciplines from galaxy formations all the way to how consciousness arises from the collective activity of neurons. Despite perceptions that some kind of intrinsic manifestation is underway, its scientific and conceptual study has suffered from a formalism basis that could guide collaborative discussions. Here we conduct a broad survey so to introduce a formal theory of causal emergence based on an information decomposition feature. As a result, information about a system's temporal evolution beyond its separate parts appears to reveal an ascendant path. This article provides a rigorous framework by which to assess the proposed approach in diverse scenarios. (Abstract excerpt)

Merrell, Floyd. Resemblance: From a Complementary Point of View? Sign Systems Studies. 38/1-4, 2010. In a issue about the title term, this paper can accompany Merrell’s 2010 book Entangling Forms, reviewed next, with its focus on this fluidly creative reciprocity of an emergent natural genesis. In earlier centuries, known as exemplarity, sympathy, emblematic, correlative, this perennial secret reveals a gender-based reflection between every entity, community, and strata. Merrell’s essay is then a postmodern paean to this yin-yang-ness in its constant, organically spiraling florescence toward self-individuation. And for our website, in the translation this begs, might one suggest that we are at last simply reading the presence and activity of nature’s parents to children genetic code?

However, as this essay unfolds, we shall note that everything is ‘multivalently’ and ‘nonlinearly’ interdependently interrelated to, and interactive with, everything else, which is to say that nothing is absolutely incommensurable or incompatible with anything else, but rather, complementarity is the watchword. (94)

Miguel-Tome, Sergio. The Influence of Computational Traits on the Natural Selection of the Nervous System. Natural Computing. Online March, 2018. A University of Salamanca, Spain neurotheorist argues that in retrospect life’s evolution has arrived at robust computational neural networks because they empowered a critical brain function of better predictability across animal kingdoms.

Mitchell, Melanie. Biological Computation. The Computer Journal. 55/7, 2012. In a special issue in honor of the Alan Turing Centenary, a Portland State University systems mathematician and author (Complexity: A Guided Tour) elucidates how this Turing turn is aiding a better appreciation of how living nature is distinguished and sustained by such an incarnate informational essence. See also in this edition “Natural Computation” by Erol Gelenbe and “Computation and Fundamental Physics” by David Bacon.

In this note we argue that biological computation is a process that occurs in nature, not merely in computer simulations of nature. (Abstract) In this article, the term biological computation refers to the proposal that living organisms themselves perform computations, and, more specifically, that the abstract ideas of information and computation may be key to understanding biology in a more unified manner. While there is some overlap among these different meldings of biology and computer science, it is only the study of biological computation that asks, specifically, if, how, and why living systems can be viewed as fundamentally computational in nature. (852)

This widespread interest in biological computation reflects a strong intuition that the notions of information and information processing are building blocks that will shed new light on how living systems operate and the common principles underlying their operation. Biology has long suffered from being a science of specific details rather than abstractions and general laws. The theory of evolution serves as one grand organizing principle, but biology still lacks a general theory of how adaptive functionality emerges from large collections of individual, decentralized components. (852)

How, for example, do insect colonies, composed of thousands to millions of individual insects, collectively make decisions and accomplish complex tasks that seem to require the communication and processing of colony‐wide information? How does the immune system, composed of trillions of cells and molecular components circulating in the body, collectively recognize patterns of infection and other organism-wide conditions, and collectively decide how to mount an appropriate response? How do the hundreds of billions of neurons in the brain work together to continually make sense of and respond to the opportunities and threats of the environment in real‐time? These questions cry out for a unified theory involving information, communication, and computation. (852)

Mora, Thierry, et al. JSP Special Issue on Information Processing in Living Systems. Journal of Statistical Physics. 162/5, 2017. French (Mora and Olivier Rivoire) and American (Luca Peliti) theorists introduce a survey of life’s communicative source as it lately becomes amenable with and rooted in physical phenomena. Some papers are Landauer in the Age of Synthetic Biology, Informations in Models of Evolutionary Dynamics, and Biological Implications of Dynamical Phases in Non-Equilibrium Networks.

Living systems are information-processing systems: they need to copy internal information, e.g., contained in their DNA, for producing their proteins—and regulating their production—or for reproducing. They also need to monitor their environment and their internal state, and to control their activity based on the collected informations. Trying to understand how living systems manage these tasks defines an area of questions at the cross-roads between statistical physics, information theory and biology. The contributions contained in the present Special Issue cover a wide-range of topics from information-dissipation trade-offs to statistical inference and issues of biological noise, hope to shed some light on these questions. (First paragraph)

Moyer, Michael. Is Space Digital? Scientific American. February, 2012. A senior editor describes this persuasion of Craig Hogan, director of the Fermilab Particle Astrophysics Center, that the deepest foundations of physical nature are discrete, grainy, and bitlike in kind. He plans to test this theory by a 21st century version of Michelson-Morley’s 1880’s interferometer, quite a low-cost option to the Large Hadron Collider, to detect and measure such intrinsic properties. It is then implied, as often alluded, that “the universe works like a computer,” whence this natural information operates as software. A technical Fermilab paper “Interferometers as Probes of Planckian Quantum Geometry” by Hogan can be accessed at arXiv:1002.4880. And once again, by a simple shift from machine to organism, might we be able to imagine the presence of an actual genotype and phenotype of a genesis cosmos?

He (Hogan) begins by explaining how the two most successful theories of the 20th century quantum mechanics and general relativity—cannot possibly be reconciled. At the smallest scales, both break down into gibberish. Yet this same scale seems to be special for another reason: it happens to be intimately connected to the science of information – the 0’s and 1’s of the universe. Physicists have, over the past couple of decades, uncovered profound insights into how the universe stores information – even going so far as to suggest that information, not matter and energy, constitutes the most basic unit of existence. Information rides on tiny bits; from these bits comes the cosmos. (32)

Yet the Planck length is much more than the space where quantum mechanics and relativity fall apart. In the past few decades an argument over the nature of black holes revealed a wholly new understanding of the Planck scale. Our best theories may break down there, but in their place something else emerges. The essence of the universe is information, (added) so this line of thinking goes, and the fundamental bits of information that give rise to the universe live on the Planck scale. (34-35)

Nicolis, Gregoire and Vasileios Basios, eds. Chaos, Information Processing and Paradoxical Games. Singapore: World Scientific, 2015. A collection in remembrance of the John Nicolis, a University of Patras professor and pioneer complex systems theorist. Chapters include Fractal Parameter Space of Lorenz-like Attractors (Tingli Xing, et al), Historical Contingency in Controlled Evolution (Peter Schuster), and Long Range Order and Fractality in the Structure and Organization of Eukaryotic Genomes (Dimitris Polychronopoulos, et al).

Nunez, Paul. Brain, Mind, and the Structure of Reality. Oxford: Oxford University Press, 2010. Reviewed more in Current Vistas, a good case for our imminent, imperative revolution to a cognizant and informed genesis cosmos.

Oller, John. The Antithesis of Entropy: Biosemiotic Communication from Genetics to Human Language with Special Emphasis on the Immune Systems. Entropy. 12/4, 2010. In a journal that actually serves as a venue for progressive vistas, the University of Louisiana medical linguist expounds at length on waxing perceptions of an innate, informational organization that which works to wind the universe up, as opposed to an inevitable wearing out.

Overman, Dean. A Case for the Existence of God. Lanham, MD: Rowman & Littlefield, 2009. I realize this is not “science,” the author is a scholarly lawyer, but it does provide a heuristic exercise. After dipping into quantum physics, a proposal is made that information indeed ought to be seen as foundational as a way to counter a materialist atheism.

The standard interpretation of the quantum world is based in information as the irreducible seed of the universe and all physical existence; such an interpretation is inconsistent with a strict reductionist materialism. (85)

Previous   1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10  Next  [More Pages]