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The White House will be holding four public discussions in order to evaluate the potential benefits and risks of artificial intelligence:
The Obama administration says it wants everyone to take a closer look at artificial intelligence with a series of public discussions.
The workshops will examine if AI will suck jobs out of the economy or add to it, how such systems can be controlled legally and technically, and whether or not such smarter computers can be used as a social good. Deputy Chief Technology Officer Ed Felton announced on Tuesday that the White House will be creating an artificial intelligence and machine learning subcomittee at the National Science and Technology Council (NSTC) and setting up a series of four events designed to consider both artificial intelligence and machine learning.
[...] The special events will be held between May 24 and July 7, will take place in Seattle, Pittsburgh, Washington DC, and New York.
The events come as tech industry leaders have grown increasingly alarmist about the future of AI development. Get ready for bans and FBI surveillance.
(Score: 2) by maxwell demon on Thursday May 05 2016, @12:30PM
Well, that would mean endless work for physicists trying to explain why the formula works, in addition to the still continuing search for a simpler working formula. After all, you cannot prove that it is impossible to explain a given formula. So what again should the physicists be afraid of? Having more work to do?
The Tao of math: The numbers you can count are not the real numbers.
(Score: 2) by RamiK on Thursday May 05 2016, @04:31PM
After all, you cannot prove that it is impossible to explain a given formula.
Just between you and me, you can. Humans learn math using single and two dimensional table assist algorithms that can defiantly be quantified for compute complexity in relation to each other to circumvent the fact they're not done with binary operations.
Already, you can say stuff like "People can't play these moves in chess since they can't visually recognizing patterns of such and so complexity". Children's development psychology is filled with similar facts. "Children of so and so ages can't remember or can understand these specific things".
Adults are tricker but since we're talking about a select range of algorithms and patterns, a targeted level test would be trivial once we actually know what to look for.
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(Score: 2) by maxwell demon on Thursday May 05 2016, @08:42PM
Nobody learns math using tables. You may learn arithmetics using tables, but that's not what math is about. Indeed, the important questions are not of the form "what is 3*5", but of the form "is a*b always the same as b*a".
And understanding a physical formula is not the same as being able to calculate it. To understand a formula means you can tell what it means. That's something very different than being able to calculate it.
And about the complexity of formulas: If you look at the formulas needed to calculate processes in quantum field theories, you'd find them extremely complex. But then, you can write the same formula as Feynman graph (yes, Feynman graphs are pictorial representations of mathematical formulas), and then it suddenly becomes intuitive enough that you can explain its physical essence even to a non-physicist, even if that non-physicist doesn't even know anything about the mathematical operations needed to calculate it.
The Tao of math: The numbers you can count are not the real numbers.
(Score: 2) by RamiK on Friday May 06 2016, @12:07AM
Everything learned is memorization. And everything is learned through memorization. What we call comprehension is the ability to hold enough layers of abstractions in our heads to be able to intuitively account for a single variable changing. It's all neuron making connections. No magic involved.
For a child, it's multiplication tables. For us it might be advance calculus or set theory. For a musicians, it's decades worth of memorizing scales and keys. Regardless, comprehension is memory. Explanation is memory. And it's entirely possible humans just can't make enough connections to work through certain equations. It's definitely the case in math. And it's very likely to be the case in many of the hard sciences.
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