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Artificial Intelligence Overview
spiderfarmer writes: "Well, it feels slightly odd to suggest one of my own articles, but here goes. I've recently completed a brief overview of the current state of AI. The article concept was focused on Cyc, but scope creep being what it is, I ended up doing an overview of the entire field. Some of the Slashdot gang were fairly helpful in pointing me towards experts who would talk to me and towards white papers and books I might not have otherwise found. So, I thought they might be interested in how I put all the information together."
Dr. Lenat and others in the field of AI research should know better than to make claims about consciousnes and morality in a public forum. Cognitive scientists don't even begin to agree on what consciousness is, let alone what it would take for a machine to replicate it. Some very respected individuals do not even think that human consciousness can be replicated within the forseeable future (e.g. Roger Penrose's The Emperor's New Mind). Like any other scientific discipline, these sorts of claims should be left to peer review. Claiming to have invented a conscious machine would be akin to a physicist claiming to have unified quantum with relativity, but without having submitted their findings to any publication.
The scientist's explanation took one paragraph, and even sounded like it had a goal - allow a machine to use an encyclopedia to gain new information in a useful manner. This is an important step to an A.I. that can interact with people - you can then train it on reference materials, and have it "understand" them at a certain level.
This scientist is NOT mistaken - he would have to know that "common sense" does not equal "the human brain's inate ability to make sense of the culture it grows in". If I had to draw a distinction, "common sense", as you are describing, is static, tuned to one culture, while the "common ability" is semi-dynamic, able to learn, but (maybe) unable to unlearn.
You could try to fake common sense, by programming your own cultural assumptions into the program, subjecting it to cultural stimulus, and fine-tuning the program. Or you could attempt to program "common ability", train it on cultural materials for a few years, and try to tune the program to build it's own "common sense" in a way that is more like a human. I think these scientists are trying to do the latter.
I'm not sure what your tangent about post-modernism and 1984 have to do with A.I. - are you just making a rant about scientists who didn't get the memo that we are in post-modern times?
An interesting question is if human intellegence can be removed from the human - does it take eyes to understand the phrase "I've got the blues"? Does it take a parent to understand why many grade school teachers are women and most world leaders men? Does it take walking upright, starting at a tiny height and getting bigger, to understand skyscrapers? Or does that just take a penis?
Now, I'm using the "white-space" sense of understand - to be sympathetic to the person who has the blues, to feel an unexplained shame when the president is caught sleeping with a women not his wife, to feel an exhiliration driving into a new city. Can these be simulated in a computer without a body and a human's lifetime? Can these things be removed, still leaving a "human" intellegence? If we interacted with this intellegence, would we say it passed the Turing test? Would we want to interact with it?
Perhaps that's one level of A.I. above where this guy is aiming. It would be extremely useful just to have an intellence with a little of the human ability. You could train it on, for instance, medical journals. A doctor could then descibe symptoms, research, or an interest, and get summaries or references to the library. Once you trained it in the basics, you could burn it to a CD, send it to a doctor, who could then train it for his specific interests. Think of it as a very limited secretary, who requires some training and aclimation, but is still smarter than a PC.
This is probably the best A.I. can do for a few years - get to the point where you can train an A.I. for a particular subject, then meaningfully interact with those interested in the subject - like a very bad librarian. It's only when the clones come out in force that you can hook a computer up to a fetus, and do some real human A.I. training.
"If you look at an encyclopedia, you'll see a great deal of knowledge of the world represented in the form of articles. Common sense is exactly not this knowledge. Common sense is the complement of this knowledge. It is the white space behind the words. It is all of the knowledge that the article writer assumed all of his/her readers would already have prior to reading the article -- knowledge that could be put to use in order to understand the article. Cyc is about representing and automating the white space." (I love that answer.)
Common sense is about representing and automating the white space?
I think these AI researchers need to talk to a few more sociologists. Human common sense is extremely culturally divergent and goes far beyond the simple, textbook logic cases that certain engineers in this field would probably cite. "Reading between the lines" involves not some native common sense that is wedded to intelligence, but a collectively evolved cultural contextualization. When we read an article in an encyclopedia, a lot of other stuff other than intelligence comes into play: x years of public school education, idiomatic constructs, varying by geographic location, that may or may not enhance or obscure meaning, and, of course, the double meanings and entendres inserted by bored or biased encyclopedia writers.
The entire postmodern project of literary criticism has been aimed at proving this point- at proving that there is no such thing as a standardized set of meanings, and that every meaning is contextualized. The Modernists wanted to rationalize and bureacratize speech, to restrict the number of meanings, and to leave what is unsaid in a narrow, predictable whitespace of a unified "common sense."
Of course, there is a language like this, developed in the first half of this century. It takes away as many English words as possible to restrict the meanings that we are able to THINK, let alone say. Of course, this language is called Newspeak.
Goat sex free since 2001
I used to work in AI Alley in Cambridge during the 80s. The industry got hyped to death by claims and demands on performance that wasn't possible. Lots of interesting things were done and lost during that timeframe. The thing is, we hadn't even reached artificial stupidity at that point. I'm not sure we have yet but we're closer in some domains. Until people unlink visions of Cherry 2000 and C3PO from the AI moniker, it's going to be tough getting people to set realistic goals. Just like the Lisp environment back then, I see the research and technology backdooring into products every day. More and more of the stuff that we did back then is making it out as "new technology" under Microsoft when we had it 20 year ago, but hyped it into obscurity. The industry seems to be coming out of it's own dark ages lately and I hope the media doesn't get back on the bandwagon to beat it back down. I thought the article was very good and you did a LOT of good research and didn't just edit together all the buzzwords you found. The response has been good in the community I still keep in touch with and you better watch out or you'll be changing people's minds about talking to journalists. Many of us wish you had been given more access to Cyc and their underlying knowledge engineering techniques to do that topic/aspect justice as well.
Good Job!
Me : Can u imagine a Beowulf cluster of yourself?
Cyc : -1 Troll.
I would recommend re-thinking your division of AI into subfields. You are indescriminately mixing technologies and application areas.
For example, neural networks are a technology and NLP is an application area. I know people working in NLP that use Lisp, and I know others that use neural networks. In AI, technologies and application areas are (mostly) orthogonal.
Granted, there probably isn't a perfect breakdown of AI into subfields, but making the distinction above will help you and your readers get a grip on what AI is all about faster.
Sheesh, evil *and* a jerk. -- Jade