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Arguing A.I.
In some ways, the author argues, the debate over A.I. is undergoing a profound revolution. What was once a discussion largely confined to tech and academic circles has mushroomed into a more mainstream brawl as a growing number of engineers and lay authors vent on the acceleration of modern technology and the future of humanity. Given the explosive growth of the Net, the near-continuous increases in computing power and much-publicized A.I. breakthroughs like Deep Blue's 1997 victory over chess champion Gary Kasparov, the question is no longer whether artificial intelligence will reach the level of human intelligence: It's when.
As the title suggests, Williams's book is less about A.I. itself than about the increasingly ferocious debates raging through the scientific community about it. The conflicts surrounding A.I., Williams suggests, may be the most significant since the titanic battles over evolution a century ago. In fact, Williams is among those who've argued that the A.I. debate is really an extension of the same fight. Artifically intelligent machines are already changing human evolution, many argue, even evolving inevitably into life-forms and species all their own. A growing number of critics and skeptics also argue that A.I. proponents are moving too quickly, failing to take into account the mind-boggling cultural and philosophical problems being raised by their new, still-imperfect technologies.
Williams traces the contemporary birth of A.I. -- via Hilbert and Turing -- on to the living pioneer credited with coining the term (John McCarthy), and talks to several of the principals guiding the A.I. debate today, like Ray Kurzweil, Jaron Lanier and Bill Joy.
This is a necessary book. It's one you could actually recommend to students, journalists, friends, parents, anybody trying to grasp the issues and implications of A.I., surely one of the most significant technologies human beings will face in the 21st Century. Even if A.I.'s impact on life is being overstated, it's poorly understood by the public. So Williams walks us through inventor Kurzweil's almost radical optimism about A.I. and the future -- especially his claims that human society is rapidly approaching the evolutionary equivalent of a new species, a fusion of humans and intelligent machines. This is the point of no return when it comes to artificial intelligence, Kurzweil claims. "The progress will ultimately become so fast that it will rupture our ability to follow it. It will literally get out of our control. The illusion that we have our hand on the plug will be dispelled."
But Williams also introduces some of the people that don't see this as a good thing -- or even a likely development. Bill Joy is more pessimistic, as he made clear in his now famous article in the April 2000 issue of Wired, "Why The Future Doesn't Need Us." The piece thrilled technophobic intellectuals and journalists because it came from a software entrepeneur and reaffirmed something they desperately wanted to believe: technology -- especially genetics, bio-tech and robotics -- is out of control and likely to generate as much evil as good in the future. Joy sees little in the modern history of software development to suggest the emergence of sentient machines. His experience has led him to believe that it's difficult to build things that are reliable.
Jaron Lanier, whom Williams also interviews, coined the term virtual reality and once likened A.I. research to alchemy. Lanier accuses many in the A.I. firmament of choosing faith and hyperbole over science and reality. He likens the current tech obsession with A.I. to medieval scholars' attempts to prove the existence of God through Aristotelian logic. In their rush to endorse the concept of thinking machines, warns Lanier, many authors are putting scientific faith before scientific skepticism.
Williams does a skillful job of presenting these different points of view without intruding on them. It might have been nice to hear more of Williams's own thoughts and perspective, since he's one of the few journalists with this much understanding an access to so many principals in the A.I. discussion. On the other hand, he might not have been wise not to wade in amongst these A.I. heavyweights and their raging debate. "Arguing A.I." is as timely a book about technology as you're likely to come across, and, perhaps more surprisingly, highly readable.
One thing that's always bothered me about the AI debate is that the thinking for a long time has centered around how to model intelligence on silicon. To me the true marvel of the mind is the holographic quality of intelligence and the way in which the physical form of the brain influences, and is shaped by, the quality and nature of one's thoughts. It will be exciting to see what part the new polymers can play in this research.
- Within 50 years, there will be a computer that will pass the Turing Test. For those of you who don't know (and I hope nobody is in this category on Slashdot
:-) the Turing Test is basically making a computer indistinguishable from a human being. A tester will ask the computer questions, and will be unable to determine whether a computer is answering the questions or whether a human is mimicing a computer.
- Within 50 years after that (100 years total), computers will be able to parse speech flawlessly, so voice recognition will finally end up being plausible. Computers will understand the nuances of speech and will be able to change homonyms (here and hear) based on the context of the sentence.
- Within 50 years of that (150 years total) we'll have computers that can respond to voice commands like in Star Trek. The computer will not only understand the syntax of language, but it will be able to determine, on its own, the difference between a question asked in conversation and a question asked to the computer in conversation.
Of course, these are just random guesses on my part, but I really think that they're reasonable. Give me your thoughts, please.The movie DARYL said this even better:-
"A robot becomes human when you can't tell the difference any more".
That one film influenced me more than all the other sci-fi films I ever saw as a kid. It's the only one that really got that concept and went for it. OK, Asimov did it first ("Bicentennial Man") but cinema still hadn't really got there.
Grab.
I no expert, but I think you've got it backwards.
First, computers will recognize voice commands. Well, there are already programs that do this like Dragon, so we're almost there anyway. The point now is that you are still giving keyword commands to a computer, and as it is refined, you'll better recognition of specific commands, and questions that can be filtered from within conversations. Giving commands to a computer is easier than open ended questions to the computer.
Second, we'll solve the natural language problem, or at least enough to provide flawless voice recognition that you speak of. It will be capable mainly of handling accents and bad grammar.
Lastly, a computer will pass the Turing test. Unless a computer can understand the intricassies of the english language, there will be people who will be able to tell by the way the answer is phrased. If you solve the NLP or get far enough for a computer to analyze and spit back poetry, then you got the Turing test licked.
-- If god wanted me to have a sig, he'd have given me a sense of humor.
A thread in useset comp.ai.philosophy today notes the number of logical gates per second in the fastest supercomputers are within a couple magnitudes of the human brain. The brain has 100 million neurons, each connected to thousand others, and runs around 20 Hz. So this is about two quadrillion ops per second.
The fastest supercomputer operates on 64 bit words at a several trillion operations a second, or about a hundred trillion ops per second; a hundred times slower or so.
Instead of quibbling exactly about these numbers, note that Moore's Law implies a factor of ten every five years. So a supercomputer will be as complex as brain somewhere in the 2010 to 2020 time frame. Don't even think about 2050 or 2100!
However, computers aren't programmed as well as a brain in many areas, so the software people have a long way to catch up.
The programmers did nothing once play beganActually that's not true. Part of the controversy surrounding the match was that the programming team, including some grandmasters, were constantly tweaking Big Blue, even during games. In addition, they reserved the right to select from Big Blues top choices. The match was far from the Man vs Machine match that was marketed.
The human brain has 10 to the power of 14 synapses. Each synapse will take around one byte of computer memory. Ignoring motor and low-level sensory functions (but including all brain logic and interpretation functions - yes, scientists have discovered what different areas of the brain do and it is possible to isolate them), an entire human brain's contents could be stored on with a Terabyte or so of computer memory. This storage space exists right now, albeit expensively. It doesn't really matter what level of hardware is used to run a brain, a human brain running 100X slower (as estimated in the post above), would still be able to run - the only limiting factor at the moment is the software used to emulate the brain functions. Like any system, this can be emulated, but it will take a massive programming effort and so far hasn't proven very successful. Of course, this won't really matter in the long run - A.I doesn't neccessarily mean that the computer A.I system must be human-like in intelligence - it could have a whole new type of intelligence which would surpass human intelligence as the rate of hardware improvement increases.
2DUP * ;
This is an excellent point.
The same idea occurred to me recently when reading through Kurzweil's "Spiritual Machines" book. There are a few orders of magnitude to toss around in these calculations : Kurzweil determined that a desktop computer will be comparable to a human by around 2020. It was evident to me that Kurzweil's timescales (and hence the premises which he used to infer them) are quite far off, because current massive parallelization of commodity CPUs puts one a factor of about 4,000 up from a desktop machine, or about 13 years of Moore's Law evolution. In addition, as the number of CPUs per supercomputer is increased, we have effectively grown faster than Moore's law, due to both the chip and parallelization advances.
Since the supercomputers of today effectively place us where a desktop will be in 2015, it should be apparent (by Kurzweil's logic) that an "intelligent" machine should be nearly imminent.
It is quite evident that something is awry in the logic leading to Kurzweil's conclusion. The simplest explanation is one which is quite familiar to scientists and programmers using state-of-the-art software tecnhinques : having the hardware resources is only a bare minimum requirement to solve a problem. For instance, one can have a supercomputer capable of simulating the Earth's climate for centuries, but that won't get you any closer to the results if you don't also possess a great deal of knowledge about atmospheric physics and numerical methods. The same is true for studies of "Thinking Machines" : one can have a machine possibly capable of thinking, but without the knowledge of how to go about doing it, you are no closer to the solution than where you began.
Bob
Science, like Nature, must also be tamed, with a view turned towards its preservation.