Over time, machine vision will become harder to fool than the one that was recently tricked into rapid acceleration by a defaced sign. But it will still be true that a fooled human makes a better decision than a fooled machine because the fooled human has common sense, awareness, and a mind that reasons.
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In the book, Baylor professor Marks asks “What if ambitious nations such as China and Iran develop lethal AI military technology but the United States does not?” He argues that “Advanced technology not only wins wars but gives pause to otherwise aggressive adversaries.”
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According to analytical philosopher Richard Johns, we cannot represent ourselves completely mathematically so we cannot generate fundamentally contradictory thoughts about ourselves. Some part of us lies beyond mathematics. An android would not be so lucky, as Captain Kirk realized in an early Star Trek episode.
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Jacob Schatzer identifies three issues in the essay, “The Allure of Transhumanism,” that might prompt some queasy recognitions in all of us, at times.
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A free course at Seattle University addresses the “meaning of ethics in AI.” I’ve signed up for it. One concern that I hope will be addressed is: We must not abdicate to machines the very thing that only we can do: Treat other people fairly.
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To see what I mean about centralization, consider a non-digital tool, say, a shovel. The shovel doesn’t keep track of your shoveling, read your biometrics, and store a file on you-as-shoveler somewhere. It’s a thing, an artifact. So you see, the new digital technology is itself the heart of the surveillance problem. No Matrix could be built with artifacts.
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With AI decision-making, a non-trivial explanation can’t be both accurate and understandable but it can be inaccurate and comprehensible. There is a huge difference between understanding something and almost understanding it.
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Researchers at the Allen Institute for Artificial Intelligence (AI2) published a paper recently, deflating claims of rapid progress toward giving computers common sense.
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As a lawyer with medical training reminded us recently, any one image is a snapshot in time, a brief part of the patient’s whole story. And it’s the whole story that matters, not a single image, perhaps taken out of context.
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Not only was Jean-François Bonnefon’s paper rejected by conventional anti-plagiarism software but the rejection didn’t make any sense. Bonnefon, research director at Toulouse School of Economics, was informed of “a high level of textual overlap with previous literature” (plagiarism) when he was citing scientists’ affiliations, standard descriptions, and papers cited by other—information he was obliged to cite accurately, according to a standard format. “It would have taken two [minutes] for a human to realise the bot was acting up,” he wrote on Twitter. “But there is obviously no human in the loop here. We’re letting bots make autonomous decisions to reject scientific papers.” Reaction to the post by Dr Bonnefon, who is currently a visiting scientist at the Massachusetts Institute Read More ›
The official Winograd Schema Challenge, organized by Levesque and friends to see if AI could learn common sense, was retired officially in 2016 for the embarrassing reason that even the well-funded bleeding age Google Brain team performed poorly on a test set of a few hundred questions.
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Historically, the key difference between the international weapons ban agreements that have been honored and the agreements that have not been honored is that the honored ones involved weapons of mass destruction (WMD). An effective ban on malicious AI requires the global community to first agree that such a form (or use) of AI would be a WMD.
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In 2013, Russian Army General Valery Gerasimov published a strategic doctrine (the Gerasimov Doctrine) where he described applying non-military activities, including false or fake stories and publications, trolls, gas-lighting and technology generally as a form of warfare, like combat. The use of audio and video deep-fakes is expanding in Ukraine, the Baltic States, Western nations, and Africa.
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Recent experiments in entanglement of particles in time as well as space show that our entire universe is imbued with final causality within its very fabric. This final causality must come from some source beyond the universe.
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To remain competitive, the U.S. military must respond and adapt to new warfare technology including weapons using AI, sometimes called killer robots. This includes autonomous AI that acts on its own. Chillingly, unlike atomic weapons, the tools to construct lethal AI weapons are cheap and readily available to all.
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Faced with a claim that an AI language tool had given an interview, I took the advice I gave readers yesterday, and followed the links. What a revelation. The Economist story was more dishonest than the examples that Siegel discussed in Scientific American.
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In an op-ed at CNS this morning, Walter Bradley Center director Robert J. Marks summarizes his case, as an artificial intelligence expert, that the United States must remain competitive in military AI or, as it is called, “killer robots,” because hostile nations are forging ahead.
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Media often co-operate with researchers’ inflated claims about machine learning’s powers of discovery. An ingenious “creative” approach to accuracy enables the misrepresentation, says data analyst Eric Siegel.
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Can we afford to let hostile powers develop AI warfare and not do so ourselves? Artificial intelligence expert Robert J. Marks has been discussing the issue in podcasts with various hosts across the country.
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Seeing the Star Trek universe from a different perspective—that is, not from the interior of a starship—was super refreshing and rewarding. It gives viewers a unique look at what day-to-day life is like for other people (much as The Mandalorian did for the Star Wars universe).
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