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Wired Founding Editor Now Challenges 'The Myth of A Superhuman AI' (backchannel.com)
Wired's founding executive editor Kevin Kelly wrote a 5,000-word takedown on "the myth of a superhuman AI," challenging dire warnings from Bill Gates, Stephen Hawking, and Elon Musk about the potential extinction of humanity at the hands of a superintelligent constructs. Slashdot reader mirandakatz calls it an "impeccably argued debunking of this pervasive myth." Kelly writes:
Buried in this scenario of a takeover of superhuman artificial intelligence are five assumptions which, when examined closely, are not based on any evidence...
1.) Artificial intelligence is already getting smarter than us, at an exponential rate.
2.) We'll make AIs into a general purpose intelligence, like our own.
3.) We can make human intelligence in silicon.
4.) Intelligence can be expanded without limit.
5.) Once we have exploding superintelligence it can solve most of our problems...
If the expectation of a superhuman AI takeover is built on five key assumptions that have no basis in evidence, then this idea is more akin to a religious belief -- a myth
Kelly proposes "five heresies" which he says have more evidence to support them -- including the prediction that emulating human intelligence "will be constrained by cost" -- and he likens artificial intelligence to the physical powers of machines. "[W]hile all machines as a class can beat the physical achievements of an individual human...there is no one machine that can beat an average human in everything he or she does."
Kelly proposes "five heresies" which he says have more evidence to support them -- including the prediction that emulating human intelligence "will be constrained by cost" -- and he likens artificial intelligence to the physical powers of machines. "[W]hile all machines as a class can beat the physical achievements of an individual human...there is no one machine that can beat an average human in everything he or she does."
Anything is possible in 10-20 years, just give me all your money!
Given that our knowledge of the computational complexity of a single neuron is growing steadily, I think it's safe to say your FPGA cell estimate for a neuron was significantly too low.
For example, scientists now know that one single neuron (of certain types) is an entire neural network all by itself. Dendrites with multiple localized spikes communicating with each other and with other cells. Ultimately performing non-linear computation prior to forwarding any signal to cell body.
there is no one machine that can beat an average human in everything he or she does
Neither can most humans. There is no such thing as an average human. Every individual human specializes, and increasingly so as they get older (or they do not improve). It is a pervasive strawman to require AIs to "beat" an average human when the same quality isn't used to judge humans.
Those who do not learn from commit history are doomed to regress it.
AlphaGo is not a "general purpose" learning mechanism. It won't ever write sonnets meaningful to humans, or be able to to dance, or even employ symbolic differentiation.
It is a really nice toolset, and it is able to solve a task which is difficult for humans, but so does Google or your high-school calculator when you calculate sin(1.2).
It won't ever go beyond the computational underpinnings of playing Go-like games: evaluating game positions and calculating game trees. It won't ever say 'forget it, I'd rather be drinking beer with my buddies', which is an intelligent thing to do for most of us with respect to playing Go.
There's nothing human-like about AlphaGo, except that it solves a problem relevant to humans; the calculator example comes in mind.
I'd be thrilled to know what kind of specific major human problems you'd consider AI-approachable, because I currently only see a bunch of more or less advanced mechanisms that are fine-tuned to solve very specific computationally well-defined problems, and most human problems are not computationally well defined.
Holy Shit! Donald Trump is a Slashdotter! Don't worry Donnie. They'll be working on bigger hands next!
Guns don't kill people; Physics kills people! - John Lithgow as Dick Solomon on Third Rock From The Sun
This kind of problem will be very visible in healthcare. Human doctors will self censor for fear of contradicting AI and taking the wrong choice, that ends up badly for the patient. Because AI is right most of the time, who will have the courage of saying otherwise? Saying truth to AI could cost a person their job. Many doctors stop giving honest feedback the moment they hear another doctor has given a diagnosis out of solidarity with their colleagues or fear of the consequences of making enemies.
Human (or just vision in general) is the best example. It accounts for 30% of the brain capacity. At one end, you have the human eye with a retina consisting of 100 million rods and cones. Then just in that space of a 5mm disc, there are seven layers of processing used to do contrast detection between colors and intensity along with edge detection. The optic nerve takes the compressed information from a thousand areas then passes it through to the brain into two paths; one to identify where objects are, the other to determine what the objects are and their orientation. Understanding what just a single region or layer of brain cells does leads to dozens of papers being published and advances in digital photography (image stabilization, motion correction).
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Indeed!
And one of the myricals in this is: if an object is about to hit your eyes or comes close by, the reflext to close the eyes and raise your hands etc. is triggered _before_ that information has even reached the brain/visual cortex.
The signal processing in the eye can bypass the visual cortex to trigger protective actions.
Cost free eBook I read (by iBook/Kobo/Amazon/ObookO/Gutenberg etc.): "The Green Odyssey" by Philip Jose Farmer.
1) AlphaGo exploded on the scene by beating world class Go players much faster and much earlier than expected. Exponentially is a loaded word. e^0.0000001 is an exponential growth rate. So let's not quibble about how exponential the growth rate is.
Particularly as we can't really measure intelligence. But "exponential" has a meaning, and it means a steady rate of doubling.
2) AlphaGo is a general purpose learning tool. Just listen to the lectures and articles penned by the DeepMind team.
No, it's a narrow AI. In the end, it's simply doing math. It's not "thinking" in any sense of the term. It's just able to hold many more probabilities in its memory than a human, and play them out much faster.
3) Alphago has displayed human-like intelligence, as claimed by the Go professionals it has played. They have said that AlphaGo plays like a human player.
That is what you call anthropomorphizing. The human players are simply projecting onto the machine.
4) If you take the fourth assumption literally, AI's intelligence is going to expand infinitely. Talking about infinity in human terms is unreasonable. Yes, AI's intelligence will expand.
"Infinite" simply means there's no limit. We don't know whether or not there's a limit to intelligence, but since the universe is finite, there would seem to be a limit to the things one could know. Infinite intelligence is our notion of God. What are the odds that infinite intelligence is also mythological?
-- sudon't
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