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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