Can computers talk? Right now, no. Natural Language Processing -- the field of Artificial Intelligence & Linguistics that deals with computer language (computers using language, not C++ or BASIC) -- has made strides in the last decade, but the best programs still frankly suck.
Will computers ever be able to talk? And I don't mean Alex the Parrot talk. I mean speak, listen and understand just as well as humans. Ideally, we'd like something like a formal proof one way or another, such as the proof that it is impossible to write a computer program that will definitively determine whether another computer program has a bug in it (specifically, a type of bug known as an infinite loop). That sort of program has been proven to be impossible. How about a program to emulate human language?
One of the most famous thought experiments to deal with this question is the The Chinese Room, created by John Searle back in 1980. The thought experiment is meant to be a refutation to the idea that a computer program, even in theory, could be intelligent. It goes like this:
Suppose you have a computer in a room. The computer is fed a question in Chinese, and it matches the question against a database in order to find a response. The computer program is very good, and its responses are indistinguishable from that of a human Chinese speaker. Can you say that this computer understands Chinese?
Searle says, "No." To make it even more clear, suppose the computer was replaced by you and a look-up table. Occasionally, sentences in Chinese come in through a slot in the wall. You can't read Chinese, but you were given a rule book for manipulating the Chinese symbols into an output that you push out the "out" slot in the wall. You are so good at using these rules that your responses are as good as those of a native Chinese speaker. Is it reasonable to say that you know Chinese?
The answer is, of course, that you don't know Chinese. Searle believes that this demonstrates that computers cannot understand language and, scaling the argument up, cannot be conscious, have beliefs or do anything else interesting and mentalistic.
One common rebuttal to this argument is that the system which is the room (input, human, look-up table) knows Chinese, even though the parts do not. This is attractive, since in some sense that is true of our brains -- the only systems we know do in fact understand language. The individual parts (neurons, neuron clusters, etc.) do not understand language, but the brain as a whole does.
It's an attractive rebuttal, but I think there is a bigger problem with Searle's argument. The thought experiment rests on the presupposition that the Chinese Room would produce good Chinese. Is that plausible?
If the human in the room only had a dictionary, it's clearly not reasonable. Trying to translate based on dictionaries produces terrible language. Of course, Searle's Chinese Room does not use a dictionary. The computer version of it uses a database. If this is a simple database with two columns, one for input and one or output, it would have to be infinitely large to perform as well as a human Chinese speaker. As Chomsky famously demonstrated long ago, the number of sentences in any language is infinite. (The computer program could be more complicated, it is true. At an AI conference I attended several years ago, template-based language systems were all the rage. These systems try to fit all input into one of many template sentences. Responses, similarly, are created out of templates. These systems work much better than earlier computerized efforts, but they are still very restricted.)
The human version of the Chinese Room Searle gives us is a little bit different. In that one, the human user has a set of rules to apply to the input to achieve an output. In Minds, Brains and Science, which contains the version of this argument that I'm working from, he isn't very explicit as to how this would work, but I'm assuming it is something like a grammar for Chinese. Even supposing using grammar rules without knowledge of the meaning of the words would work, the fact is that after decades of research, linguists still haven't worked out a complete grammatical description of any living language.
The Chinese Room would require a much, much more sophisticated system than what Searle grants. In fact, it requires something so complicated that nobody even knows what it would look like. The only existing algorithm that can handle human language is implemented in the human brain. The only machine currently capable of processing human language as well as a human is the human brain. Searle's conceit was that we could have "dumb" algorithm -- essentially a look-up table -- that processed language. We don't have one. Maybe we never will. Maybe in order to process human language at the same level of sophistication as a human, the "system" must be intelligent, must actually understand what it's talking about.
This brings us to the flip argument to Searle's thought expeirment: Turing's. Turing proposed to test the intelligence of computers this way: once a computer can compete effectively in parlor games, it's reasonable to assume it's as intelligent as a human. The parlor game in question isn't important: what's important is the flexibility it required. Modern versions of the Turing Test focus on the computer being able to carry on a normal human conversation -- essentially, to do what the Chinese Room would be required to do. The Turing assumption is that the simplest possible method of producing human-like language requires cognitive machinery on par with a human.
If anybody wants to watch a dramatization of these arguments, I suggest the current re-imagining of Battlestar Galactica. The story follows a war between humans and intelligent robots. The robots clearly demonstrate emotions, intelligence, pain and suffering, but the humans are largely unwilling to believe any of it is real. "You have software, not feelings," is the usual refrain. Some of the humans begin to realize that the robots are just as "real" to them as the other humans. The truth is that our only evidence that other humans really have feelings, emotions, consciousness, etc., is through their behavior.
Since we don't yet have a mathematical proof one way or another, I'll have to leave it at that. In the meantime, having spent a lot of time struggling with languages myself, the Turing view seems much more plausible than Searle's.
Comments
I would disagree to all these
July 10, 2009 by Anonymous, 17 weeks 2 days ago
Comment id: 37839
I would disagree to all these points. I think its all fake.
talking computers
October 25, 2008 by Anonymous, 1 year 1 week ago
Comment id: 32534
I think computers can be easier programed to recognise emotions in electronised speech and possibly programmed to recognise greater or lesser overall good in a sentence of programmed words made into a question.
Re: the formal disproof
September 23, 2007 by coglanglab, 2 years 6 weeks ago
Comment id: 25093
Anonymous: you have a number of interesting points. I would disagree, however, that "we are no closer to even the faintest understanding of how we do even the simplest of cognitive tasks." I would say that a great deal has been learned about many simple and complex cognitive tasks, though we certainly have a long ways to go. Good thing, too, or I'd be out of a job!
Please try my web-based experiments
the formal disproof
September 23, 2007 by Anonymous, 2 years 6 weeks ago
Comment id: 25083
The disproof of Searle and the Kurtzweil Singularity hypothesis is really dead obvious: We have no acceptable definition of intelligence, so we cannot "create" it any more than we could create "smurtzwaggle zokelin" because the term is nonsensical. how could we set out to get to smurtzwaggle if we don't know what direction to begin or how to tell if we stray?
There is a related proof, and that is repeated underlined and highlinered in all AI experiments since SHRDLU: We ourselves do not understand even the very rudiments of how we ourselves learn, understand or use language. Anyone asserting the contrary is outright lying, filling you with fantasy Sci-Fi. We have studied the psychology of language for some 80 years now, and we have had a natural philosophy of the mind for many thousands of years, yet we are no closer to even the faintest understanding of how we do even the simplest of cognitive tasks. No idea whatsoever. We don't even have any faint understanding of where to look for the answer, all we have are volumes of rulebooks chronicalling medical anecdotes of where the language systems go wrong, and we cannot even simulate those with our programs.
Joseph Wiezenbaum, inventor of the famous prototypical chatbot psychoanalyst was amazed that even his own staff refused to believe that eliza was not understanding their problems; the desire to believe in AI is so strong, even in the face of huge evidence we cannot let go of the dream. Wiezenbaum also pointed out how even with our more stellar AI acheivements, in his day it was SHRDLU and in ours it is Deep Thought, you can blow the whole Mechanical Turk wide open by asking the genius machine only one question: "Will you sell me your bishop?" -- it is a question any two year old human will grasp and answer in an instant, yet will stymie the un-pre-pared machine.
Very interesting discussion.
September 18, 2007 by pathos, 2 years 7 weeks ago
Comment id: 24994
coglanglab,
Your paragraph 6 strikes me as a crutial point. The Searle analogy with a human in the room and a book of rules of Chinese, is acting as a "computer", albeit a slow cpu, taking input, seeking rules from a book, parsing a database, giving an output. True, in this sense, the person does not know Chinese. However, what if the person takes the book (as we humans have a tendancy to do), learns the rules, and derives the basis from which they were developed, and then applies them and further builds on them? It would be a daunting task, but I would say if this was done comprehensively, the person would know Chinese. To me, it is an interesting point to ponder, where does the person step over the line from functioning as a "computer", into the realm of knowing. Can this point be defined, and can in be applied to computers/AI, with respect to speech/language?
My background is in medicine/biomedical sciences and not computers/AI obviously, so I hope my thoughts are relevant.
To Dr. Fred, Interestingly, my son and I have had another discussion on understanding the universe. We talked about AI, and what seems to be limitations on robots/computers ability to generate and analyze new theories on unification/understanding the universe. I am always brought back to the work of Jacob Bronowski, who saw that in all our mathematics, physics, science, there will always be a human element that is required, even if it is just to translate an observation or phenomena, let alone understand it's basis. It seems to me, that this human component, will present in computers/robots also, as long as we have a hand in building them and programming them. To get to a truly new way of thinking of the universe and anything else, there must be a generation of non-human computer/robot evolution, that happens with the robotic system alone, without any human intervention. It would then be possible to have non-human thought, idea generation, etc.,that may include new thought processes that we can't comprehend/concieve with our own limited senses and mind. And maybe that's what's needed to understand it all. I think I need your book.
Best regards,
Pathos
Fort Collins, CO
Note to Pathos in Fort Collins
September 18, 2007 by Fred Bortz, 2 years 7 weeks ago
Comment id: 24997
Thanks. The book includes an extensive interview with AI founders Herb Simon and Alan Newell, both now deceased.
My questions were such that they started speaking directly to my audience, which was kids like your son, I presume.
Newell knew he only had months to live, yet he spoke like he was in mid-career. It was remarkable sitting there with the two of them, knowing how precious Newell's time was, and capturing it all on tape.
Please contact me at DrFredB AT-SIGN worldnet DOT att Dot net. I'd love to put the book in your son's hands.
Fred Bortz -- Science and technology books for young readers (www.fredbortz.com) and Science book reviews (www.scienceshelf.com)
"It's Greek (or Chinese) to me!"
September 18, 2007 by Fred Bortz, 2 years 7 weeks ago
Comment id: 24984
Fifteen years ago, I wrote a young adult book called Mind Tools: The Science of Artificial Intelligence, which is still current in many aspects. I have a few copies left to sell as bargain books at personal appearances for teens who are into AI. (E-mail me using my website link if you want one.
Anyway, the main reason for this posting is that the article reminded me of the opening of chapter 9 in the book, "Expert systems to Understand and Translate 'Natural Language'." It's amusing and relevant to the famous "Chinese room." I am the "American man" in the incident.
--- begin quote
An American man once asked a Greek colleague to translate the English expression "It's Greek to me!" into Greek. She did so, but, not speaking a word of her native language, he couldn't understand what she said.
So he asked her to translate it back into English. "It's Chinese to me," she said.
They laughed and wondered whether their Chinese-speaking friends had similar expressions in their native language.
--- end quote
Fred Bortz -- Science and technology books for young readers (www.fredbortz.com) and Science book reviews (www.scienceshelf.com)