Capitalism, Commons, Economy, Ethics, Media, Social intelligence, Society

Why and how should we build a basic income for everybody?

“What would Heaven on Earth mean in reality? It would mean that each and every person on the planet has access to an an abundant supply of healthy food and clean water. That each and every person has access to luxurious housing and clothing. That we are all safe. That we can all communicate with everyone. That we all have free and open access to education and entertainment. That cutting edge health care is available freely to everyone, and the cutting edge is advancing as rapidly as possible, curing more and more diseases and ailments as fast as we can. And so on. We do that in an environmentally sustainable way. Obviously there would be no wars. Obviously we would have to find safe, compassionate ways to resolve our differences. Obviously we would need for Heaven on Earth to be environmentally sustainable – otherwise we poison the planet and destroy ourselves. What if we made Heaven on Earth our world-wide, species-wide goal?”

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AI, Algorithm, Automata, Biological Computation, Code, Cybernetics, Deep Learning, Emergence, Man/Machine, Neural Networks, Robots, Science, Social intelligence, Society

Can a robot be too nice?

“Designing artificial entities perfectly groomed to meet our emotional needs has an obvious appeal, like creating the exact right person for a job from thin air. But it’s also not hard to imagine the problems that might arise in a world where we’re constantly dealing with robots calibrated to treat us, on an interpersonal level, exactly the way we want. We might start to prefer the company of robots to that of other, less perfectly optimized humans. We might react against them, hungry for some of the normal friction of human relations. As Lanier worried, we might start to see the lines blur, and become convinced that machines—which in some ways are vastly inferior to us, and in other ways vastly superior—are actually our equals.”

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Anthropology, Archeology, Biology, History, Media, Science, Social intelligence, Society

Mapping Intel­lec­tual Migra­tion Net­works

“We’re starting out to do some­thing which is called cul­tural sci­ence where we’re in a very sim­ilar tra­jec­tory as sys­tems biology for example,” said Schich, now an asso­ciate pro­fessor in arts and tech­nology at the Uni­ver­sity of Texas at Dallas. “As data sets about birth and death loca­tions grow, the approach will be able to reveal an even more com­plete pic­ture of his­tory. In the next five to 10 years, we’ll have con­sid­er­ably larger amounts of data and then we can do more and better, address more questions.”

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AI, Algorithm, Biometrics, Brain, Capitalism, Cybernetics, Economy, Education, Emergence, Ethics, Man/Machine, Robots, Science, Social intelligence, Society

Will You Lose Your Job To a Robot?

“The biggest exception will be jobs that depend upon empathy as a core capacity — schoolteacher, personal service worker, nurse. These jobs are often those traditionally performed by women. One of the bigger social questions of the mid-late 2020s will be the role of men in this world.” — Jamais Cascio, technology writer and futurist

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Anthropology, Art, Biological Computation, Biology, Biometrics, Brain, Deep Learning, Music, Neural Networks, Psychology, Science, Social intelligence, Society, Sound

The Neuroscience of Improvisation

Charles Limb has been investigating rap. “It’s what kids are doing spontaneously when growing up… and improvisation is a strong theme. It incorporates language and rhythmic music very equally.” Limb has been scanning the brains of rappers the same way he looked at jazz musicians: comparing fMRIs when they recited memorized passages to when they “freestyled,” or improvised in rhyme. Although the study is still in progress, preliminary data suggest “major changes in brain activity when you go from memorized rap to freestyle.” Can studies of improvisation unlock more general secrets of creativity? Limb hopes to do similar investigations of artists as they draw or paint. The moderator ended with an inevitable question about art and science: “It is worth the effort to measure and quantify something abstract and artistic… to demystify what we enjoy the mystery of?” Limb saw nothing “threatening or reductionist” in the work of neuroscientists. “Humans are hardwired to seek art, and there are very few things that engage the brain on the level that music does. To understand the neural basis of creativity teaches us something fundamental about who we are, why we’re here.” Improvisation “shows us what the mind can do,” Marcus added. “The ability of human beings to improvise tells us a lot about the ultimate scope of our capabilities.”

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AI, Algorithm, Automata, Biological Computation, Brain, Code, Cybernetics, Deep Learning, Logic, Man/Machine, Mathematics, Neural Networks, Science, Social intelligence

Neural Networks and Deep Learning

“Will we understand how such intelligent networks work? Perhaps the networks will be opaque to us, with weights and biases we don’t understand, because they’ve been learned automatically. In the early days of AI research people hoped that the effort to build an AI would also help us understand the principles behind intelligence and, maybe, the functioning of the human brain. But perhaps the outcome will be that we end up understanding neither the brain nor how artificial intelligence works!”

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Algorithm, Architecture, Art, Automata, Biological Computation, Chaos, Code, Cybernetics, Drawing machine, History, Interface, Kinetic, Light, Logic, Maker, Man/Machine, Mathematics, Neural Networks, PDF, Social intelligence, Society, Tactical Media

Cybernetic Serendipity the Computer and the Arts – (1968)

Exhibition catalogue. Edited by Jasia Reichardt (Studio International Special Issue, London. 1968)

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Anthropology, Art, Capitalism, Code, Commons, Economy, Ethics, History, Interface, Media, Memory, PDF, philosophy, Social intelligence, Society, Tactical Media

Kittler Friedrich : Gramophone Film Typewriter

“Part technological history of the emergent new media in the late nineteenth century, part theoretical discussion of the responses to these media—including texts by Rilke, Kafka, and Heidegger, as well as elaborations by Edison, Bell, Turing, and other innovators—Gramophone, Film, Typewriter analyzes this momentous shift using insights from the work of Foucault, Lacan, and McLuhan. Fusing discourse analysis, structuralist psychoanalysis, and media theory, the author adds a vital historical dimension to the current debates over the relationship between electronic literacy and poststructuralism, and the extent to which we are constituted by our technologies. The book ties the establishment of new discursive practices to the introduction of new media technologies, and it shows how both determine the ways in which psychoanalysis conceives of the psychic apparatus in terms of information machines.”

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AI, Algorithm, Biological Computation, Brain, Code, Cybernetics, History, Interface, Logic, Man/Machine, Mathematics, Neural Networks, PDF, Science, Social intelligence, Society

Computing Machinery and Intelligence : Turing, A.M. (1950).

The fact that Babbage’s Analytical Engine was to be entirely mechanical will help us to rid ourselves of a superstition. Importance is often attached to the fact that modern digital computers are electrical, and that the nervous system also is electrical. Since Babbage’s machine was not electrical, and since all digital computers are in a sense equivalent, we see that this use of electricity cannot be of theoretical importance. Of course electricity usually comes in where fast signalling is concerned, so that it is not surprising that we find it in both these connections. In the nervous system chemical phenomena are at least as important as electrical. In certain computers the storage system is mainly acoustic. The feature of using electricity is thus seen to be only a very superficial similarity. If we wish to find such similarities we should took rather for mathematical analogies of function.

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Animals, Biology, Biometrics, DNA, Economy, Education, Nature, Neural Networks, Science, Social intelligence, Society

Twittering bacteria: on bacteria… social intelligence

“New research suggests that microbial life can be even richer: highly social, intricately networked, and teeming with interactions [47]. Bassler [3] and other researchers have determined that bacteria communicate using molecules comparable to pheromones. By tapping into this cell-to-cell network, microbes are able to collectively track changes in their environment, conspire with their own species, build mutually beneficial alliances with other types of bacteria, gain advantages over competitors, and communicate with their hosts – the sort of collective strategizing typically ascribed to bees, ants, and people, not to bacteria. Eshel Ben-Jacob [6] indicate that bacteria have developed intricate communication capabilities (e.g. quorum-sensing, chemotactic signalling and plasmid exchange) to cooperatively self-organize into highly structured colonies with elevated environmental adaptability, proposing that they maintain linguistic communication. Meaning-based communication permits colonial identity, intentional behavior (e.g. pheromone-based courtship for mating), purposeful alteration of colony structure (e.g. formation of fruiting bodies), decision-making (e.g. to sporulate) and the recognition and identification of other colonies – features we might begin to associate with a bacterial social intelligence.”

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