Artificial Intelligence

From Beth Singler of the Faraday Institute at Aeon: The most avid believers in artificial intelligence are aggressively secular – yet their language is eerily religious. Why? Taking a blind stab in the dark: Both grasp the significance of death? The odd thing about the anti-clericalism in the AI community is that religious language runs wild in its ranks, and in how the media reports on it. There are AI ‘oracles’ and technology ‘evangelists’ of a future that’s yet to come, plus plenty of loose talk about angels, gods and the apocalypse. Ray Kurzweil, an executive at Google, is regularly anointed a ‘prophet’ by the media – sometimes as a prophet of a coming wave of ‘superintelligence’ (a sapience surpassing Read More ›

From Garry Kasparov at TED: Advanced Chess found its home on the internet, and in 2005, a so-called freestyle chess tournament produced a revelation. A team of grandmasters and top machines participated, but the winners were not grandmasters, not a supercomputer. The winners were a pair of amateur American chess players operating three ordinary PCs at the same time. Their skill of coaching their machines effectively counteracted the superior chess knowledge of their grandmaster opponents and much greater computational power of others. And I reached this formulation. A weak human player plus a machine plus a better process is superior to a very powerful machine alone, but more remarkably, is superior to a strong human player plus machine and an inferior Read More ›

From Jesse Emspak at LiveScience: What Is Intelligence? 20 Years After Deep Blue, AI Still Can’t Think Like Humans “Good as they are, [computers] are quite poor at other kinds of decision making,” said Murray Campbell, a research scientist at IBM Research. “Some doubted that a computer would ever play as well as a top human. “The more interesting thing we showed was that there’s more than one way to look at a complex problem,” Campbell told Live Science. “You can look at it the human way, using experience and intuition, or in a more computer-like way.” Those methods complement each other, he said. Although Deep Blue’s win proved that humans could build a machine that’s a great chess player, Read More ›

From Nguyen A, Yosinski J, and Clune J (2015) at Evolving Artificial Intelligence Laboratory: Deep neural networks (DNNs) have recently been achieving state-of-the-art performance on a variety of pattern-recognition tasks, most notably visual classification problems. Given that DNNs are now able to classify objects in images with near-human-level performance, questions naturally arise as to what differences remain between computer and human vision. A recent study revealed that changing an image (e.g. of a lion) in a way imperceptible to humans can cause a DNN to label the image as something else entirely (e.g. mislabeling a lion a library). Here we show a related result: it is easy to produce images that are completely unrecognizable to humans, but that state-of-the-art DNNs believe Read More ›

From Meghan O’Gieblyn at the Guardian: After losing her faith, a former evangelical Christian felt adrift in the world. She then found solace in a radical technological philosophy – but its promises of immortality and spiritual transcendence soon seemed unsettlingly familiar … Transhumanism offered a vision of redemption without the thorny problems of divine justice. It was an evolutionary approach to eschatology, one in which humanity took it upon itself to bring about the final glorification of the body and could not be blamed if the path to redemption was messy or inefficient. Tip: As soon as they mention “evolutionary,” find your keys. Encounters with God are not “evolutionary.” Within months of encountering Kurzweil, I became totally immersed in transhumanist Read More ›

From molecular cancer biologist Ahmed Alkhateeb at Aeon: Science is in the midst of a data crisis. Last year, there were more than 1.2 million new papers published in the biomedical sciences alone, bringing the total number of peer-reviewed biomedical papers to over 26 million. However, the average scientist reads only about 250 papers a year. Meanwhile, the quality of the scientific literature has been in decline. Some recent studies found that the majority of biomedical papers were irreproducible. The twin challenges of too much quantity and too little quality are rooted in the finite neurological capacity of the human mind. Scientists are deriving hypotheses from a smaller and smaller fraction of our collective knowledge and consequently, more and more, Read More ›

It’s always a pleasure to host Dr Selensky’s thoughtful contributions. Here, he tackles the subject of artificial life simulations and the implications of modelling environments, assumptions, algorithms etc: ____________________________ On Modelling Spontaneous Emergence of Programs and Their Evolutionary Self-Improvement Evgeny Selensky Some time ago, I left a comment on Jeffrey Shallit’s blog. We exchanged a couple of phrases. In particular, I referred Jeffrey to the requirement for computational halting in models of artificial life. I praised David Abel’s work, which put him off. In response, Jeffrey recommended that I should “read and understand” the following article. I have done my homework now. However I’d like to post here at UD rather than visit Jeffrey’s blog again. Jeffrey of course is Read More ›

From Bill Dembski at the Best Schools: The White House paper on automation rightly draws our attention to the challenges society faces from the coming disruptions to the job market on account of AI, and machine learning in particular. A real and imminent threat exists here, in which the middle-class could get severely hurt. But this threat can be averted if we rise to the occasion, demanding more of ourselves and of our educational system, focusing on those areas where human intelligence has primacy. Simply put, we’re smarter than machines, and we need to play to our strengths where the superiority of human over machine intelligence is palpable. More. Dembski also talks about the self-driving car. I (O’Leary for News) Read More ›

In Pittsburgh, including 12:00 PM Nik Melchior. “Machine Emulation of Human Thought” Artificial intelligence promises the development of computers with the same capabilities of cognition, perception, and problem-solving as their human inventors. Recent applications include self-driving cars, robots that work in factories, and computers able to best humans in games like Jeopardy, Chess, and Go. This talk will present an accessible introduction to common techniques and paradigms in the study of artificial intelligence and machine learning. The significance of newsworthy AI systems will be examined, as well as the perceived threat of superhuman intelligence that does not share our morality. Bio: Nik Melchior received his masters in computer science from Washington University in St. Louis and his Ph.D. in robotics Read More ›

From Jerry Kaplan at Technology Review: Artificial intelligence, it seems, has a PR problem. While it’s true that today’s machines can credibly perform many tasks (playing chess, driving cars) that were once reserved for humans, that doesn’t mean that the machines are growing more intelligent and ambitious. It just means they’re doing what we built them to do. The robots may be coming, but they are not coming for us—because there is no “they.” Machines are not people, and there’s no persuasive evidence that they are on a path toward sentience. We’ve been replacing skilled and knowledgeable workers for centuries, but the machines don’t aspire to better jobs and higher employment. Jacquard looms replaced expert needleworkers in the 19th century, Read More ›

From Michael Byrne at Motherboard: It’s not that computer scientists haven’t argued against AI hype, but an academic you’ve never heard of (all of them?) pitching the headline “AI is hard” is at a disadvantage to the famous person whose job description largely centers around making big public pronouncements. This month that academic is Alan Bundy, a professor of automated reasoning at the University of Edinburgh in Scotland, who argues in the Communications of the ACM that there is a real AI threat, but it’s not human-like machine intelligence gone amok. Quite the opposite: the danger is instead shitty AI. Incompetent, bumbling machines. Bundy notes that most all of our big-deal AI successes in recent years are extremely narrow in Read More ›

From Ross Pomeroy’s ultimate list of Top Ten science stories at RealClearScience: Artificial Intelligence Defeats Go World Champion This year we witnessed artificial intelligence master a new game: Go. Lee Sedol, the reigning world champion predicted victory at the outset, but by the end of the five-game series he had won only a single bout against Google’s AlphaGo computer program. Google technicians trained AlphaGo using 30 million positions from 160,000 games of Go played by human experts. They later made the program play games against itself to grow in skill even further. Programs like AlphaGo with an enormous potential to learn could one day be harnessed to solve real-world problems.More. Physicist Rob Sheldon offers a different take: There have been Read More ›

From Toby Walsh at New Scientist: In December 2014, Stephen Hawking told the BBC that “the development of full artificial intelligence could spell the end of the human race… It would take off on its own, and redesign itself at an ever increasing rate. Humans, who are limited by slow biological evolution, couldn’t compete, and would be superseded.” Last year, he followed that up by saying that AI is likely “either the best or worst thing ever to happen to humanity”.More. You’d have to pay to find out why Walsh thinks it won’t happen (paywall) . Some of us think it won’t happen because other things will happen first. It’s one thing to want a robotic snow shovel but consider, Read More ›

From Russell Brandom at Verge: While some predict mass unemployment or all-out war between humans and artificial intelligence, others foresee a less bleak future. Professor Manuela Veloso, head of the machine learning department at Carnegie Mellon University, envisions a future in which humans and intelligent systems are inseparable, bound together in a continual exchange of information and goals that she calls “symbiotic autonomy.” In Veloso’s future, it will be hard to distinguish human agency from automated assistance — but neither people nor software will be much use without the other. Veloso is already testing out the idea on the CMU campus, building roving, segway-shaped robots called “cobots” to autonomously escort guests from building to building and ask for human help Read More ›

From Bruce Sterling, reviewing The Singularity from Journal of Consciousness Studies, at New Scientist: Creating superintellingence may be inevitable, unless we are already living in a simulation. A collection of AI essays grapples with this weighty issue … While the book is a tremendous flight over the craggy AI landscape, it settles no disputes and has little or nothing in the way of practical counsel. Kant, Hume and Descartes are major intellectual presences here, apparently because explosively proliferating future AI singularities are going to be plenty worried about these three dead European guys. (paywall) More. Introduction by editor Uziel Awret free here. More contents here. This all comes of not knowing or caring to know what information even is, or Read More ›