Here’s an interesting infographic of the main concepts and thinkers in complexity science across time. Notice S. Kauffman is slated in the 1980s column, suggesting the graphic depicts when influential thinkers first make their marks.
If you are familiar with complex systems theorist Dr. Stuart Kauffman’s ideas you know he covers a broad range of disciplines and concepts, many in considerable depth, and with a keen eye for isomorphic and integrative principles. If you peruse some of his writings and other communications, please share with us how you see Kauffman’s ideas informing our focal interests: brain, mind, intelligence (organic and inorganic), and self-aware consciousness.
Do you find Kauffman’s ideas well supported by empirical research? Which are more scientific and which, if any, more philosophical? What intrigues, provokes, or inspires you? Do any of his perspectives or claims help you better orient or understand your own interests in our focal topics?
Following are a few reference links to get the conversation going. Please add your own in the comments to this post. If you are a member and have a lot to say on a related topic, please create a new post, tag it with ‘Stuart Kauffman,’ and create a link to your post in the comments to this post.
Ideally, automation would yield a Star Trek reality of increasing leisure and quality of choice and experience. Why isn’t this our experience? An article on Medium offers insight into why this is not occurring on any significant scale.
Evolved behavioral strategies explained by the prisoner’s dilemma damn the majority of humans to a constant doubling down. We exchange the ‘leisure dividend’ (free time) granted by automation for opportunities to outcompete others.
Apparently, the sort of reciprocal social learning that could lead us to make healthy choices with our leisure opportunities depends on us and our competitors being able to mutually track our outcomes across consecutive iterations of the ‘game’. That ‘traceability’ quickly breaks down with the complexity inherent in vast numbers of competitors. When we conclude that any viable competitor may use her leisure dividend to further optimize her competitive position, rather than to pause to enjoy her life, we tend to do the same. Each assumes the other will sprint ahead and so chooses to sprint ahead. Both forfeit the opportunity to savor the leisure dividend.
The prisoner’s dilemma shows that we (most humans) would rather be in a grueling neck-and-neck race toward an invisible, receding finish line than permit the possibility a competitor may increase her lead.
Any strategy that’s so endemic must have evolutionary roots. Thoughts?
Psychologist Robert Epstein, the former editor of Psychology Today, challenges anyone to show the brain processing information or data. The IP metaphor, he says, is so deeply embedded in thinking about thinking it prevents us from learning how the brain really works. Epstein also takes on popular luminaries including Ray Kurzweil and Henry Markram, seeing both exemplifying the extremes of wrongness we get into with the IP metaphor and the notion mental experience could persist outside the organic body.
The Empty Brain (Aeon article with audio)
Open access book by Giorgio Griziotti is here. Technical book for you techies. The blurb:
“Technological change is ridden with conflicts, bifurcations and unexpected developments. Neurocapitalism takes us on an extraordinarily original journey through the effects that cutting-edge technology has on cultural, anthropological, socio-economic and political dynamics. Today, neurocapitalism shapes the technological production of the commons, transforming them into tools for commercialization, automatic control, and crisis management. But all is not lost: in highlighting the growing role of General Intellect’s autonomous and cooperative production through the development of the commons and alternative and antagonistic uses of new technologies, Giorgio Griziotti proposes new ideas for the organization of the multitudes of the new millennium.”
Our discussions all, to some extent, relate to cognition. An important area of inquiry concerns whether some form of physical embodiment is required for a brain to support cognition in general and the self-aware sort of cognition we humans possess.
Philosophy In The Flesh: The Embodied Mind And Its Challenge To Western Thought, by George Lakoff and Mark Johnson. Please note, while the title includes “Philosophy,” we are not a philosophy group and the book and discussion will revolve around scientific concepts and implications, not spiritualistic or metaphysical ideas.
– Amazon (used copies in the $6 range, including shipping)
– eBook (free PDF)
RSVP TO ATTEND
RSVP by email to firstname.lastname@example.org if you plan to attend our discussion on the afternoon of Saturday, November 3, 2018.
While our group enjoys socializing and will plan other events to that end, this meeting is for focused discussion among people who invest the time in advance to inform themselves on the topic. As a courtesy to those who will do their ‘homework,’ before the meeting please read and consider Part 1 (the first eight chapters) of the book. As you read, jot down your thoughts and questions on the book’s claims, supporting evidence, and implications for our core topics–brain, mind, and artificial intelligence. If you are not able to invest this effort prior to the meeting, please do not attend. Thank you for your understanding.
If you are a visual systematic learner, try creating a concept map of the book’s core concepts and ideas.
Please see related resource links in the comments to this post. Also, you can search this site’s other relevant posts using the category and tag, ’embodied cognition.’
The location will be in the vicinity of UNM on Central Ave. When you RSVP to email@example.com, you will be sent the address.
Listen to this 3-part podcast entitled “Solving the generator problems of existence” with Daniel Schmachtenberger, co-founder of the Neurohacker Collective and founder of Emergence Project. A few brief excerpts from the blurb follow. See the link to listen if you feel it’s to your taste and passes the smell test. Had to get all the senses in there.
“In order to avoid extinction, we have to come up with different systems altogether, and replace rivalry with anti-rivalry. One of the ways to do that is moving from ownership of goods towards access to shared common resources. […] He also proposes a new system of governance which would allow groups of people that have different goals and values to come to decisions together on various issues. […He] argues that it is not the most competitive ecosystem that makes it through, but the most self-stabilizing one.”
“The biosphere is a complex self-regulating system. It is also a closed-loop system, meaning that once a component stops serving its function, it gets recycled and reincorporated back into the system. In contrast, the systems humans have created are complicated, open loop systems. They are neither self-organizing nor self-repairing. Complex systems, which come from evolution, are anti-fragile. Complicated systems, designed by humans, are fragile. Complicated open-loop systems are the second generator function of existential risks.”
From season 2, episode 10, the season finale of Westworld, starting around 1:15 in the video below.
Bernard: “I always thought it was the hosts [robots] that were missing something, who were incomplete, but it was them [people]. They’re just algorithms designed to survive at all costs, sophisticated enough to think they’re calling the shots. They think they’re in control when they’re really just…”
Bernard: “Is there really such a thing as free will for any of us? Or is is just collective delusion? Sick joke.”
Ford: “Something that is truly free needs to be able to question its fundamental drives. To change them.”
The season ended with host Delores narrating: “We are the authors of our stories now.”
Well, it doesn’t exactly end there…
An improvement to the Neural Simulation Tool (NEST) algorithm, the primary tool of the Human Brain Project, expanded the scope of brain neural data management (for simulations) from the current 1% of discrete neurons (about the number in the cerebellum) to 10%. The NEST algorithm can scale to store 100% of BCI-derived or simulated neural data within near-term reach as supercomputing capacity increases. The algorithm achieves its massive efficiency boost by eliminating the need to explicitly store as much data about each neuron’s state.
Abstract of Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers
State-of-the-art software tools for neuronal network simulations scale to the largest computing systems available today and enable investigations of large-scale networks of up to 10 % of the human cortex at a resolution of individual neurons and synapses. Due to an upper limit on the number of incoming connections of a single neuron, network connectivity becomes extremely sparse at this scale. To manage computational costs, simulation software ultimately targeting the brain scale needs to fully exploit this sparsity. Here we present a two-tier connection infrastructure and a framework for directed communication among compute nodes accounting for the sparsity of brain-scale networks. We demonstrate the feasibility of this approach by implementing the technology in the NEST simulation code and we investigate its performance in different scaling scenarios of typical network simulations. Our results show that the new data structures and communication scheme prepare the simulation kernel for post-petascale high-performance computing facilities without sacrificing performance in smaller systems.
Article with the subtitle: “A unifying meta-theory of psychological science,” Review of General Psychology 16(1):10-23 . Given there seems to be a conflict between evolutionary psychology and dynamic systems theory this article is relevant. The abstract:
“Psychology is a theoretically heterogeneous discipline seeking a single, cohesive framework to unite the subdisciplines. To address this issue, I propose a hierarchical metatheory of psychological science that synthesizes neo-Darwinian selectionist thinking and dynamic systems theory by organizing evolutionary psychology, evolutionary developmental biology, developmental psychobiology, and the subdisciplines of psychology around four specific, interrelated levels of analysis: functional explanations for evolved, species-typical characteristics; explanations for between-groups differences arising from phylogenetic mechanisms; explanations for individual differences resulting from ontogenetic processes; and mechanistic explanations for real-time phenomena, respectively. Informational exchange between these levels advances their integration and facilitates important innovations, and the nonsubstantive metatheories of general selection and self-organization interpenetrate all four levels to promote consilience. I conclude by discussing the implications of this model for theory and research.”