Brain Archive

Originally published in print June 18, 2002 in Are We Spiritual Machines? Ray Kurzweil vs. the Critics of Strong AI by the Discovery Institute. Published on KurzweilAI.net on June 18, 2002.

Those Who Build Chinese Rooms are Doomed to Live in Them

John Searle is popular among his followers for what they believe is a staunch defense of the deep mystery of human consciousness against trivialization by strong AI reductionists like Ray Kurzweil. And even though I have always found Searle’s logic in his celebrated Chinese Room Argument to be hopelessly tautological, even I had expected him to articulate an elevating treatise on the paradoxes of consciousness. Thus it is with some surprise that I find Searle writing statements such as:

[H]uman brains cause consciousness by a series of specific neurobiological processes in the brain. The essential thing is to recognize that consciousness is a biological process like digestion, lactation, photosynthesis, or mitosis . . .

The brain is a machine, a biological machine to be sure, but a machine all the same. So the first step is to figure out how the brain does it and then build an artificial machine that has an equally effective mechanism for causing consciousness.

We know that brains cause consciousness with specific biological mechanisms . . .

So who is being the reductionist here? Searle apparently expects that we can measure the subjectivity of another entity as readily as we measure the oxygen output of photosynthesis.

I will return to this central issue, but I also need to point out the disingenuous nature of many of Searle’s quotations and characterizations. For example, he leaves out critical words that dramatically alter the meaning of a statement. For example, Searle writes in his chapter in this book:

[Ray Kurzweil] insists that they [the machines] will claim to be conscious . . . and consequently their claims will be largely accepted. People will eventually just come to accept without question that machines are conscious. But this misses the point. I can already program my computer so that it says that it is conscious—i.e., it prints out “I am conscious”—and a good programmer can even program it so that it will carry on a rudimentary argument to the effect that it is conscious. But that has nothing to do with whether or not it really is conscious.

Searle fails to point out that I make exactly the same point, and further that I refer not to such idle claims that are easily feasible today but rather to the convincing claims of future machines. As one example of many, I write in my book (p. 60) that these claims “won’t seem like a programmed response. The machines will be earnest and convincing.”

Searle writes that I “frequently cite IBM’s Deep Blue as evidence of superior intelligence in the computer.” The opposite is the case: I cite Deep Blue to (p. 289) “examine the human and [contemporary] machine approaches to chess . . . not to belabor the issue of chess, but rather because [they] illustrate a clear contrast.” Human thinking follows a very different paradigm. Solutions emerge in the human brain from the unpredictable interaction of millions of simultaneous self-organizing chaotic processes. There are profound advantages to the human paradigm: we can recognize and respond to extremely subtle patterns. But we can build machines the same way.

Searle states that my book “is an extended reflection of the implications of Moore’s Law.” But the exponential growth of computing power is only a small part of the story. As I repeatedly state, adequate computational power is a necessary but not sufficient condition to achieve human levels of intelligence. Searle essentially doesn’t mention my primary thesis: We are learning how to organize these increasingly formidable resources by reverse engineering the human brain itself. By examining brains in microscopic detail, we will be able to recreate and then vastly extend these processes. As I point out below, we have made substantial progress in this endeavor just in the brief period of time since my book was published.

Searle is best known for his “Chinese Room” analogy and has presented various formulations of it over twenty years (see below). His descriptions illustrate a failure to understand the essence of either brain processes or the nonbiological processes that could replicate them. Searle starts with the assumption that the “man” in the room doesn’t understand anything because, after all, “he is just a computer,” thereby illuminating Searle’s own bias. Searle then concludes—no surprise—that the computer doesn’t understand. Searle combines this tautology with a basic contradiction: The computer doesn’t understand Chinese, yet (according to Searle) can convincingly answer questions in Chinese. But if an entity—biological or otherwise—really doesn’t understand human language, it will quickly be unmasked by a competent interlocutor. In addition, for the program to convincingly respond, it would have to be as complex as a human brain. The observers would long be dead while the man in the room spends millions of years following a program billions of pages long.

Most importantly, the man is acting only as the central processing unit, a small part of a system. While the man may not see it, the understanding is distributed across the entire pattern of the program itself and the billions of notes he would have to make to follow the program. I understand English, but none of my neurons do. My understanding is represented in vast patterns of neurotransmitter strengths, synaptic clefts, and interneuronal connections. Searle appears not to understand the significance of distributed patterns of information and their emergent properties.

Searle writes that I confuse a simulation for a recreation of the real thing. What my book (and chapter in this book) actually talk about is a third category: functionally equivalent recreation. He writes that we could not stuff a pizza into a computer simulation of the stomach and expect it to be digested. But we could indeed accomplish this with a properly designed artificial stomach. I am not talking about a mere “simulation” of the human brain as Searle construes it, but rather functionally equivalent recreations of its causal powers. As I pointed out, we already have functionally equivalent replacements of portions of the brain to overcome such disabilities as deafness and Parkinson’s disease.

Searle writes: “It is out of the question . . . to suppose that . . . the computer is conscious.” Given this assumption, Searle’s conclusions to the same effect are hardly a surprise. Searle would have us believe that you can’t be conscious if you don’t possess some specific (albeit unspecified) biological process. No entities based on functionally equivalent processes need apply. This biology-centric view of consciousness is likely to go the way of other human-centric beliefs. In my view, we cannot penetrate the ultimate reality of subjective experience with objective measurement, which is why many classical methods, including Searle’s materialist approach, quickly hit a wall.

The Intuitive Linear View Revisited

Searle’s slippery and circular arguments aside, nonbiological entities, which today have many narrowly focused skills, are going to vastly expand in the breadth, depth, and subtlety of their intelligence and creativity. Early in his chapter, Searle makes clear his discomfiture with the radical nature of the twenty-first century technologies that I have described and their impact on society. Searle clearly expects the twenty-first century to be much like the twentieth century, and considers any significant deviation from present norms to be absurd on their face. Not once, but twice he expresses incredulity at the notion of virtual sex, for example: “The section on prostitute is a little puzzling to me. . . . But why pay, if it is all an electrically generated fantasy anyway?”

Searle obviously misses the point of virtual reality. Virtual reality is not fantasy; it is a communication medium between two or more people. We already have auditory virtual reality; it’s called the telephone. Indeed, that is exactly how the telephone was viewed when it was introduced in the late nineteenth century. People found it remarkable that you could actually “be with” someone else, at least as far as the auditory sense was concerned, despite the fact that you were geographically disparate. And indeed we have a form of sex over phone lines, not very satisfying to many perhaps, but keep in mind it involves only one sense organ. The paradigm, however, is just this: two people communicating, and in some cases one of those persons may be paid for their services. Technology to provide full immersion visual shared environments is now being developed, and will be ubiquitous by the end of this decade (with images written directly to our retinas by our eyeglasses and contact lenses). Then, in addition to talking, it will really appear like you are with that other person. As for touching one another, the tactile sense will not be full immersion by the end of this decade, but full immersion virtual shared environments incorporating the auditory, visual, and tactile senses will become available by around 2020. The design of such technology can already be described. When nanobot-based virtual reality becomes feasible around 2030, then these shared environments will encompass all of the senses.

Virtual sex and virtual prostitution are among the more straightforward scenarios for applying full immersion communication technologies, so it is puzzling to me that Searle consistently cites these as among the most puzzling to him. Clearly Searle’s thinking about the future is limited by what I referred to in my chapter as the “intuitive linear” view, despite the fact that both he and I have been around long enough to witness the acceleration inherent in the historically accurate exponential view of history and the future.

Twenty-First Century Machine Intelligence Revisited

Beyond Searle’s circular, tautological, and often contradictory reasoning, he essentially fails to even address the key points in my chapter and my book, so it is worthwhile reviewing my primary reasoning in my own words. My message concerns the emergence early in the next century of nonbiological entities with enormously powerful intellectual skills and abilities and the profound impact this will have on human society. The primary themes are:

(1) The power of computer technology per unit cost is growing exponentially. This has been true for the past one hundred years, and will continue well into the next century.

(2) New hardware technologies such as nanotube-based circuits, which allow three-dimensional computer circuits to be constructed, are already working in laboratories. Such three-dimensional circuits will ultimately provide physically small devices that vastly exceed the memory and computational ability of the human brain.

(3) In addition to computation, there is comparable exponential growth in communication, brain scanning, neuron modeling, brain reverse engineering, miniaturization of technology, and many other areas.

(4) Sufficient computational power by itself is not enough. Adequate computational (and communication) resources are a necessary but not sufficient condition to match the breadth, depth, and subtlety of human capabilities. The organization, content, and embedded knowledge of these resources (i.e., the “software” of intelligence) is also critical.

(5) A key resource for understanding and ultimately recreating the software of intelligence is the human brain itself. By probing the human brain, we are already learning its methods. We are already applying these types of insights (e.g., the front-end sound-wave transformations used in automatic speech recognition systems are based on early auditory processing in mammalian brains). The brain is not invisible to us. Our ability to scan and understand human neural functioning both invasively and noninvasively is scaling up exponentially.

(6) We have already created detailed replications of substantial neuron clusters. These replications (not to be confused with the simplified mathematical models used in many contemporary “neural nets”) recreate the highly parallel analog-digital functions of these neuron clusters, and such efforts are also scaling up exponentially. This has nothing to do with manipulating symbols, but is a detailed and realistic recreation of what Searle refers to as the “causal powers” of neuron clusters. Human neurons and neuron clusters are certainly complicated, but their complexity is not beyond our ability to understand and recreate using other mediums. I cite specific recent progress below.

(7) We’ve already shown that the causal powers of substantial neuron clusters cannot only be recreated, but actually placed in the human brain to replace disabled brain portions. These are not mere simulations, but functionally equivalent recreations of the causal powers of neuron clusters.

(8) With continuing exponential advances in computer hardware, neuron modeling, and human brain scanning and understanding, it is a conservative statement to say that we will have detailed models of neurons and complete maps of the human brain within thirty years that enable us to reverse engineer its organization and content. This is no more startling a proposition than was the proposal to scan the entire human genome 14 years ago. Well before that, we will have nonbiological hardware with the requisite capacity to replicate its causal powers. Human brain level computational power, together with an understanding of the organization and content of human intelligence gained through such reverse engineering efforts, will be a formidable combination.

(9) Although contemporary computers can compete with human intelligence in narrow domains (e.g., chess, diagnosing blood cell images, recognizing land terrain images in a cruise missile, making financial investment decisions), their overall intelligence lacks the subtlety and range of human intelligence. Compared to humans, today’s machines appear brittle and formulaic. But contemporary computers are still a million times simpler than the human brain. The depth and breadth of the behavior of nonbiological entities will appear quite different when the million-fold difference in complexity is reversed, and when we can apply powerful models of biological processes.

(10) There are profound advantages to nonbiological intelligence. If I spend years learning French, I can’t transfer that knowledge to you. You have to go through a similar painstaking process. We cannot easily transfer (from one person to another) the vast pattern of neurotransmitter strengths, synaptic clefts, and other neural elements that represents our human knowledge. But we won’t leave out quick downloading ports in our nonbiological recreations of neuron clusters. Machines will be able, therefore, to rapidly share their knowledge.

(11) Virtual personalities can claim to be conscious today, but such claims are not convincing. They lack the subtle and profound behavior that would make such claims compelling. But the claims of nonbiological entities some decades from now—entities that are based on the detailed design of human thinking—will not be so easily dismissed.

(12) The emergence of highly advanced intelligence in our machines will have a profound impact on all aspects of our human-machine civilization.

Recent Progress in Brain Reverse Engineering

Critical to my thesis is the issue of brain reverse engineering, so it is worth commenting on recent progress in this area. Just in the two years since my recent book was published, progress in this area has been remarkably fast. The pace of brain reverse engineering is only slightly behind the availability of the brain scanning and neuron structure information. There are many contemporary examples, but I will cite just one, which is a comprehensive model of a significant portion of the human auditory processing system that Lloyd Watts <www.lloydwatts.com> has developed from both neurobiology studies of specific neuron types and brain interneuronal connection information. Watts’ model includes more than a dozen specific brain modules, five parallel paths and includes the actual intermediate representations of auditory information at each stage of neural processing. Watts has implemented his model as real-time software which can locate and identify sounds with many of the same properties as human hearing. Although a work in progress, the model illustrates the feasibility of converting neurobiological models and brain connection data into working functionally equivalent recreations. Also, as Hans Moravec and others have speculated, these efficient machine implementations require about 1,000 times less computation than the theoretical potential of the biological neurons being recreated.

The brain is not one huge “tabula rasa” (i.e., undifferentiated blank slate), but rather an intricate and intertwined collection of hundreds of specialized regions. The process of “peeling the onion” to understand these interleaved regions is well underway. As the requisite neuron models and brain interconnection data becomes available, detailed and implementable models such as the auditory example above will be developed for all brain regions.

On the Contrast Between Deep Blue and Human Thinking

To return to Searle’s conceptions and misconceptions, he misconstrues my presentation of Deep Blue. As I mentioned above, I discuss Deep Blue because it illustrates a clear contrast between this particular approach to building machines that perform certain structured tasks such as playing chess, and the way that the human brain works. In my book, I use this discussion to present a proposal to build these systems in a different way—a more human way (see below). Searle concentrates entirely on the methods used by Deep Blue, which completely misses the point.

Searle’s chapter is replete with misquotations. For example, Searle states:

So what, according to Kurzweil and Moore’s Law, does the future hold for us? We will very soon have computers that vastly exceed us in intelligence. Why does increase in computing power automatically generate increased intelligence? Because intelligence, according to Kurzweil, is a matter of getting the right formulas in the right combination and then applying them over and over, in his sense “recursively,” until the problem is solved.

This is a completely erroneous reference. I repeatedly state that increases in computing power do not automatically generate increased intelligence. Furthermore, with regard to Searle’s reference to recursion, I present the recursive method as only one technique among many, and as a method suitable only for a narrow class of problems such as playing board games. I never present this simple approach as the way to create human-level intelligence in a machine.

If you read Searle’s chapter and do not read my book, you would get the impression that I present the method used by Deep Blue as the ultimate paradigm for machine intelligence. It makes me wonder if Searle actually read the book, or just selectively picked phrases out of context. I repeatedly contrast the recursive methods of Deep Blue with the pattern recognition based paradigm used by the human brain. The field of pattern recognition represents my own technical area of expertise. Human pattern recognition is based on a paradigm in which solutions emerge from the interplay of many interacting processes (see below). What I clearly describe in the book is moving away from the formulaic approaches used by many contemporary AI systems and moving towards the human paradigm of pattern recognition.

Searle’s explanation of how Deep Blue works is essentially correct (thanks in large measure to my explaining it to him in response to his urgent email messages to me asking me to clarify for him how Deep Blue works). Although the basic recursive method of rapidly expanding move-countermove sequences is simple, the evaluation at the “leaves” of this move-countermove tree (the scoring function) is really the heart of the method. If you have a simple scoring function, then the method is indeed simple and dependent merely on brute force in computational speed. However, the scoring function is not necessarily simple. Deep Blue’s scoring function uses up to 8,000 different features, and is more complex than most.

Deep Blue is able to consider billions of board situations and creates an enormous tree of move-countermove possibilities. Since our human neurons are so slow (at least ten million times slower than electronic circuits), we only have time to consider at most a few hundred board positions. Since we are unable to consider the billions of move-countermove situations that a computer such as Deep Blue evaluates, what we do instead is to “deeply” consider each of these situations. So how do we do that? By using pattern recognition, which is the heart of human intelligence. We have the ability to recognize situations as being similar to ones we have thought about previously. A chess master such as Kasparov will have mastered up to one hundred thousand such board situations. As he plays, he recognizes situations as being similar to ones he has thought about before and then calls upon his memory of those previous thoughts (e.g., “this is just like that situation that I got into three years ago against grandmaster so-and-so when I forgot to protect my trailing pawn . . .”).

I discuss this in my book in order to introduce a proposal to build game-playing machines in a new and hybrid way which would combine the current strength of machines (i.e., the ability to quickly sift through a vast combinatorial explosion of move-countermove sequences) with the more human-like pattern recognition paradigm which represents at least a current superiority of human thinking. Basically, the idea is to use a large (machine-based) neural net to replace the scoring function. Prior to playing, we train that neural net on millions of examples of real-world chess playing (or whatever other game or problem we are addressing). With regard to chess, we have most of the master games of this century on-line, so we can train this extensive neural net on every master game. And then instead of just using an arbitrary set of rules or procedures at the terminal leaves (i.e., the scoring function), we would use this fully trained neural net to make these evaluations. This would combine the combinatorial approach with a pattern recognition approach (which, as I mentioned above, is my area of technical expertise).

I proposed this to Murray Campbell, head of the IBM Deep Blue team, and he was very interested in the idea, and we were going to pursue it, but then IBM cancelled the Deep Blue project. I may yet return to the idea. Recently I brought up the idea again with Campbell.

Searle completely misconstrues this discussion in my book. It is not at all my view that the simple recursive paradigm of Deep Blue is exemplary of how to build flexible intelligence in a machine. The pattern recognition paradigm of the human brain is that solutions emerge from the chaotic and unpredictable interplay of millions of simultaneous processes. And these pattern recognizers are themselves organized in elaborate and shifting hierarchies. In contrast to today’s computers, the human brain is massively parallel, combines digital and analog methods, and represents knowledge as highly distributed patterns encoded in trillions of neurotransmitter strengths.

A failure to understand that computing processes are capable of being—just like the human brain—chaotic, unpredictable, messy, tentative, and emergent is behind much of the criticism of the prospect of intelligent machines that we hear from Searle and other essentially materialist philosophers. Inevitably, Searle comes back to a criticism of “symbolic” computing: that orderly sequential symbolic processes cannot recreate true thinking. I think that’s true.

But that’s not the only way to build machines, or computers.

So-called computers (and part of the problem is the word “computer” because machines can do more than “compute”) are not limited to symbolic processing. Nonbiological entities can also use the emergent self-organizing paradigm, and indeed that will be one great trend over the next couple of decades, a trend well under way. Computers do not have to use only 0 and 1. They don’t have to be all digital. The human brain combines analog and digital techniques. For example, California Institute of Technology Professor Carver Mead and others have shown that machines can be built by combining digital and analog methods. Machines can be massively parallel. And machines can use chaotic emergent techniques just as the brain does.

My own background is in pattern recognition, and the primary computing techniques that I have used are not symbol manipulation, but rather self-organizing methods such as neural nets, Markov models, and evolutionary (sometimes called genetic) algorithms.

A machine that could really do what Searle describes in the Chinese Room would not be merely “manipulating symbols” because that approach doesn’t work. This is at the heart of the philosophical slight of hand underlying the Chinese Room (but more about the Chinese Room below).

It is not the case that the nature of computing is limited to manipulating symbols. Something is going on in the human brain, and there is nothing that prevents these biological processes from being reverse engineered and replicated in nonbiological entities.

Searle writes that “Kurzweil assures us that Deep Blue was actually thinking.” This is one of Searle’s many out-of-context quotations. The full quotation from my book addresses diverse ways of viewing the concept of thinking, and introduces my proposal for building Deep Blue in a different, more human way:

After Kasparov’s 1997 defeat, we read a lot about how Deep Blue was just doing massive number crunching, not really “thinking” the way his human rival was doing. One could say that the opposite is the case, that Deep Blue was indeed thinking through the implications of each move and countermove; and that it was Kasparov who did not have time to really think very much during the tournament. Mostly he was just drawing upon his mental database of situations he had thought about long ago. Of course, this depends on one’s notion of thinking, as I discussed in chapter three. But if the human approach to chess—neural network based pattern recognition used to identify situations from a library of previously analyzed situations—is to be regarded as true thinking, then why not program our machines to work the same way? The third way: And that’s my idea that I alluded to above as the third school of thought in evaluating the terminal leaves in a recursive search. . . .

Finally, a comment on Searle’s view that the “real competition was not between Kasparov and the machine, but between Kasparov and a team of engineers and programmers.” Both Deep Blue and Kasparov obtain input and modification to their knowledge bases and strategies from time to time between games. But both Deep Blue and Kasparov use their internal knowledge bases, strategies, and abilities to play each game without any outside assistance or intervention during the game.

On Searle and his Chinese Rooms

John Searle is probably best known for his Chinese Room Argument, which adherents believe demonstrates that machines (i.e., nonbiological entities) can never truly understand anything of significance (such as Chinese). There are several versions of the Chinese Room, of which I will discuss three.

Chinese Room One: A Person and a Computer in a Room

The first involves a person and a computer in a room. I quote here from Professor Searle’s 1992 book:

I believe the best-known argument against strong AI was my Chinese room argument (Searle 1980a) that showed that a system could instantiate a program so as to give a perfect simulation of some human cognitive capacity, such as the capacity to understand Chinese, even though that system had no understanding of Chinese whatever. Simply imagine that someone who understands no Chinese is locked in a room with a lot of Chinese symbols and a computer program for answering questions in Chinese. The input to the system consists in Chinese symbols in the form of questions; the output of the system consists in Chinese symbols in answer to the questions. We might suppose that the program is so good that the answers to the questions are indistinguishable from those of a native Chinese speaker. But all the same, neither the person inside nor any other part of the system literally understands Chinese; and because the programmed computer has nothing that this system does not have, the programmed computer, qua computer, does not understand Chinese either. Because the program is purely formal or syntactical and because minds have mental or semantic contents, any attempt to produce a mind purely with computer programs leaves out the essential features of the mind.

First of all, it is important to recognize that for this system—the person and the computer—to, as Professor Searle puts it, “give a perfect simulation of some human cognitive capacity, such as the capacity to understand Chinese” and to convincingly answer questions in Chinese, this system is essentially passing a Chinese Turing Test. It is entirely equivalent to a Turing Test. In the Turing Test, a computer answers questions in a natural language such as English, or it could be Chinese, in a way that is convincing to a human judge. That is essentially the premise here in the Chinese Room. Keep in mind that we are not talking about answering questions from a fixed list of stock questions (because that’s a trivial task), but answering any unanticipated question or sequence of questions from a knowledgeable human interrogator, just as in Turing’s eponymous test.

Now, the human in the Chinese Room has little or no significance. He is just feeding things into the computer and mechanically transmitting the output of the computer. And the computer and the human don’t need to be in a room either. Both the human and the room are irrelevant. The only thing that is significant is the computer.

Now for the computer to really perform this “perfect simulation of a human cognitive capacity, such as the capacity to understand Chinese,” it would have to, indeed, understand Chinese. It has, according to the very premise “the capacity to understand Chinese,” so it is then entirely contradictory to say that “the programmed computer . . . does not understand Chinese.” The premise here directly contradicts itself.

A computer and computer program as we know them today could not successfully perform the described task. So if we are to understand the computer to be like today’s computers, then it is not fulfilling the premise. The only way that it could fulfill the premise would be for the computer to have the depth and complexity that a human has. That was Turing’s brilliant insight in proposing the Turing Test, that convincingly answering questions in a human language really probes all of human intelligence. We’re not talking here about answering a question from a canned set of questions, but answering any possible sequence of questions from an intelligent human questioner. A system that could only answer a fixed set of questions would quickly be unmasked by a knowledgeable interlocutor. That requires a human level of intelligence.

A computer that is capable of accomplishing this—a computer that we will run into a few decades from now—will need to be of human complexity or greater, and will indeed understand Chinese in a deep way—because otherwise it would never be convincing in its claim to understand Chinese.

So just stating the computer “does not literally understand Chinese” does not make sense. It contradicts the entire premise.

To claim that the computer is not conscious is not compelling either. To be consistent with some of Searle’s other statements, we have to conclude that we really don’t know if it is conscious or not. With regard to relatively simple machines, including today’s computers, while we can’t state for certain that these entities are not conscious, their behavior, including their inner workings, don’t give us that impression. But that will not be true for a computer that can really do what is needed in the Chinese room. Such a computer will at least seem conscious. Whether it is or not, we really cannot make a definitive statement. But just declaring that it is obvious that the computer (or the entire system of the computer, person and room) is not conscious is far from a compelling argument.

In the quote I read above, Professor Searle is saying that “the program is purely formal or syntactical.” But as I pointed out above, that is a bad assumption based on Searle’s failure to understand the requirements of such a technology. This assumption is behind much of the criticism of AI that we have heard from certain AI critics such as Searle. A program that is purely formal or syntactical will not be able to understand Chinese, and it won’t “give a perfect simulation of some human cognitive capacity.”

But again, we don’t have to build our machines that way. We can build them the same way nature built the human brain: using chaotic emergent methods that are massively parallel. Furthermore, there is nothing preventing machines from mastering semantics. There is nothing inherent in the concept of a machine that restricts its expertise to the level of syntax alone. Indeed if the machine inherent in Searle’s conception of the Chinese Room had not mastered semantics, it would not be able to convincingly answer questions in Chinese and thus would contradict Searle’s own premise.

One approach, as I discuss at length in my book and in my chapter in this book, is to reverse engineer and copy the methods of the human brain (with possible extensions). And if it is a Chinese human brain, the copy will understand Chinese. I am not talking about a simulation per se, but rather a duplication of the causal powers of the massive neuron cluster that constitutes the brain, at least those causal powers salient and relevant to thinking.

Will such a copy be conscious? I don’t think the Chinese Room Argument tells us anything about this question.

Searle’s Chinese Room Argument Can Be Applied to the Human Brain Itself

Although it is clearly not his intent, Searle’s own argument implies that the human brain has no understanding. He writes:

“The computer . . . succeeds by manipulating formal symbols. The symbols themselves are quite meaningless: they have only the meaning we have attached to them. The computer knows nothing of this, it just shuffles the symbols.”

Searle acknowledges that biological neurons are machines, so if we simply substitute the phrase “human brain” for “computer” and “neurotransmitter concentrations and related mechanisms” for “formal symbols,” we get:

The [human brain] . . . succeeds by manipulating [neurotransmitter concentrations and related mechanisms]. The [neurotransmitter concentrations and related mechanisms] themselves are quite meaningless: they have only the meaning we have attached to them. The [human brain] knows nothing of this, it just shuffles the [neurotransmitter concentrations and related mechanisms].

Of course, neurotransmitter concentrations and other neural details (e.g., interneuronal connection patterns) have no meaning in and of themselves. The meaning and understanding that emerges in the human brain is exactly that: an emergent property of its complex patterns of activity. The same is true for machines. Although the “shuffling symbols” do not have meaning in and of themselves, the emergent patterns have the same potential role in nonbiological systems as they do in biological systems such as the brain. As Hans Moravec has written, “Searle is looking for understanding in the wrong places . . . [he] seemingly cannot accept that real meaning can exist in mere patterns.”

Chinese Room Two: People Manipulating Slips of Paper

Okay, now let’s address a second conception of the Chinese Room. In this conception of the Chinese Room Argument, the room does not include a computer but has a room full of people manipulating slips of paper with Chinese symbols on it. The idea is that this system of a room, people, and slips of paper would convincingly answer questions in Chinese, but none of the participants would know Chinese, nor could we say that the whole system really knows Chinese. Not in a conscious way, anyway. Searle then essentially ridicules the idea that this “system” could be conscious. What are we to consider conscious, Searle asks: the slips of paper, the room? Of course the very notion sounds absurd, so the point is made.

One of the problems with this version of the Chinese Room Argument is that this model of the Chinese Room does not come remotely close to really solving the specific problem of answering questions in Chinese. This form of Chinese Room is really a description of a machine-like process that uses the equivalent of a table look-up, with perhaps some straightforward logical manipulations, to answer questions. It would be able to answer some limited number of canned questions. But if it were to answer any arbitrary question that it might be asked, this process would really have to understand Chinese in the same way that a Chinese person does. Again, it is essentially being asked to pass a Chinese Turing Test. And as such, it would need to be as clever, and about as complex, as a human brain, a Chinese human brain. And straightforward table look-up algorithms are simply not going to work.

If we want to recreate a brain that understands Chinese using people as little cogs in the recreation, we would really need a person for each neural connection, so we would need about a hundred trillion people, which means about ten thousand planet Earths with ten billion persons each. This would require a rather large room. And even if extremely efficient organized, this system would run many thousands of times slower than the Chinese brain it is attempting to recreate (by the way, I say thousands, and not millions or trillions because the human brain is very slow compared to electronic circuits—200 calculations per second versus about one billion for machines today).

So Professor Searle is taking an utterly unrealistic solution, one that does not come close to fulfilling its own premise, and then asks us to perform a mental thought experiment that considers whether or not this unrealistic system is conscious, or knows anything about Chinese. The very word “room” is misleading, as it implies a limited number of people with some manageable number of slips of papers. So people think of this so-called “room” and these slips of papers and the rules of manipulating the slips of paper and then are asked to consider if this “system” is conscious. The apparent absurdity of considering this simple system to be conscious is therefore supposed to show that such a recreation of an intelligent process would not really “know” Chinese.

However, if we were to do it right, so that it would actually work, it would take on the order of a hundred trillion people. Now it’s true that none of these hundred trillion people would need to know anything about Chinese, and none of them would necessarily know what is going on in this elaborate system. But that’s equally true of the neural connections in a real human brain. None of the hundred trillion connections in my brain knows anything about this Discovery Institute book chapter I am writing, nor do any of them know English, nor any of the other things that I know. None of them are conscious of this chapter, nor of any of the things I am conscious of. Probably none of them are conscious at all. But the entire system of them, that is Ray Kurzweil, is conscious. At least, I’m claiming that I’m conscious.

So if we scale up Searle’s Chinese Room to be the rather massive “room” it needs to be, who’s to say that the entire system of a hundred trillion people simulating a Chinese Brain that knows Chinese isn’t conscious? Certainly, it would be correct to say that such a system knows Chinese. And we can’t say that it is not conscious anymore than we can say that about any other process. We can’t know the subjective experience of another entity (and in at least some of Searle’s writings, he appears to acknowledge this limitation). And this massive hundred trillion person “room” is an entity. And perhaps it is conscious. Searle is just declaring ipso facto that it isn’t conscious, and that this conclusion is obvious. It may seem that way when you call it a room, and talk about a limited number of people manipulating a limited number of pieces of paper. But as I said, such a system doesn’t remotely work.

A key to the philosophical sleight of hand implicit in the Chinese Room Argument has specifically to do with the complexity and scale of the system. Searle says that whereas he cannot prove that his typewriter or tape recorder are not conscious, he feels it is obvious that they are not. Why is this so obvious? At least one reason is because a typewriter and a tape recorder are relatively simple entities.

But the existence or absence of consciousness is not so obvious in a system that is as complex as the human brain, indeed one that may be a direct copy of the organization and causal powers of a real human brain. If such a “system” acts human and knows Chinese in a human way, is it conscious? Now the answer is no longer so obvious. What Searle is saying in the Chinese Room Argument is that we take a simple “machine”—and the conception of a room of people manipulating slips of paper is indeed a simple machine—and then consider how absurd it is to consider such a simple machine to be conscious.

I would agree that a simple machine appears not to be conscious, and that a room of people manipulating slips of paper does not appear to be conscious. But such a simple machine, whether it be a typewriter, a tape recorder, or a room of people manipulating slips of paper cannot possibly answer questions in Chinese. So the fallacy has everything to do with the scale and complexity of the system. Simple machines do not appear to be conscious (again, this is not a proof, but a reasonable conclusion nonetheless). The possible consciousness of machines that are as complex as the human brain is an entirely different question. Complexity alone does not necessarily give us consciousness, but the Chinese Room tells us nothing about whether or not such a system is conscious. The way Searle describes this Chinese Room makes it sound like a simple system, so it seems reasonable to conclude that it isn’t conscious. What he doesn’t tell you is that the room needs to be much bigger than the solar system, so this apparently simple system isn’t really so simple at all.

Chinese Room Three: A Person with a Rule Book

A third variant of the Chinese Room is that there is only one person manipulating slips of papers according to a “rule book.” Searle then asks what we are we to consider conscious: the slips of paper, the rule book, the room? Again, the humorous absurdity of the situation clearly implies that the system is not conscious, and does not really “know” Chinese.

But again, it would be utterly infeasible for this little system to provide “a perfect simulation of some human cognitive capacity, such as the capacity to understand Chinese” unless the rule book were to be as complex as a human brain that understands Chinese. And then it would take absurdly long for the human to follow the trillions of rules.

Okay, how about if the rule book simply listed every possible question, and then provided the answer? This would be even less feasible, as the number of possible questions is in the trillions of trillions.

Also keep in mind that the answer to a question would need to consider all of the dialogue that came before it.

The term “rule book” implies a book of hundreds or maybe thousands of pages of rules, but not many trillions of pages.

So again we have a simple machine—a person and a “rule book”—and the apparent absurdity of such a simple system “knowing” Chinese or being conscious. But what really is absurd is the notion that such a system, even in theory, could really answer questions in Chinese in a convincing way.

The version of the Chinese Room Searle cites in his chapter in this book is closest to this third conception. One just replaces “rule book” with “computer program.” But as I point out above, the man in the room is acting like the central processing unit (CPU) of the computer carrying out the program. One could indeed say that the CPU of a computer, being only a small part of a larger system, does not understand what the entire system understands. One has to look for understanding from the right perspective. The understanding, in this case, is distributed across the entire system, including a vastly complex program, and the billions of little notes that the man would have to keep and organize in order to actually follow the program. That’s where the understanding lies, not in the CPU (i.e., the man in the room) alone. It is a distributed understanding embedded in a vast pattern, a type of understanding that Searle appears not to recognize.

Ray Kurzweil’s Chinese Room: With Decorations from the Ming Dynasty

Okay, so here is my conception of the Chinese Room. Call it Ray Kurzweil’s Chinese Room:

There is a human in a room. The room has decorations from the Ming Dynasty. There is a pedestal on which sits a mechanical typewriter. The typewriter has been modified so that there are Chinese symbols on the keys instead of English letters. And the mechanical linkages have been cleverly altered so that when the human types in a question in Chinese, the typewriter does not type the question, but instead types the answer to the question.

Now the person receives questions in Chinese characters, and dutifully presses the appropriate keys on the typewriter. The typewriter types out not the question, but the appropriate answer. The human then passes the answer outside the room.

So here we have a room with a man in it that appears to know Chinese, yet clearly the human does not know Chinese. And clearly the typewriter does not know Chinese either. It is just an ordinary typewriter with its mechanical linkages modified. So despite the fact that the man in the room can answer questions in Chinese, who or what can we say truly knows Chinese? The decorations?

Now you might have some objections to my Chinese Room.

You might point out that the decorations don’t seem to have any significance.

Yes, that’s true. Neither does the pedestal. The same can be said for the human, and for the room.

You might also point out that the premise is absurd. Just changing the mechanical linkages in a mechanical typewriter could not possibly enable it to convincingly answer questions in Chinese (not to mention the fact that we can’t fit all the Kanji symbols on the keys).

Yes, that’s a valid objection as well. Now the only difference between my Chinese Room conception, and the several proposed by Professor Searle, is that it is patently obvious in my conception that it couldn’t possibly work. It is obvious that my conception is absurd. That is not quite as apparent to many readers or listeners with regard to the Searle Chinese Rooms. However, it is equally the case.

Now, wait a second. We can make my conception work, just as we can make Searle’s conceptions work. All you have to do is to make the typewriter linkages as complex as a human brain. And that’s theoretically (if not practically) possible. But the phrase “typewriter linkages” does not suggest such vast complexity. The same is true when Searle talks about a person manipulating slips of paper or following a book of rules or a computer program. These are all equally misleading conceptions.

The Chinese Room and Chess

Searle’s application of his Chinese Room to chess is equally misleading. He says the man in the room “looks up in a book what he is supposed to do.” So again, we have a simple look-up procedure. What sort of book is Searle imagining? If it lists all the chess situations that the man might confront, there wouldn’t be enough particles in the Universe to list them all, given the number of possible permutations of chess boards. If, on the other hand, the book contains the program that Deep Blue follows, the man would take thousands of years to make a move, which last time I checked, is not regulation chess.

Searle’s primary point is contained in his statement:

The man understands nothing of chess; he is just a computer. And the point of the parable is this: if the man does not understand chess on the basis of running the chess-playing program, neither does any other computer solely on that basis.

As I pointed out earlier, Searle is simply assuming his conclusion: the man “is just a computer,” so obviously (to Searle) he cannot understand anything. But the entire system which includes the rule book and the man following the rule book does “understand” chess, or else it wouldn’t be able to play the game.

It should also be pointed out that playing good chess, even championship chess, is a lot easier than convincingly answering questions in a natural human language such as Chinese. But then, Searle shifts the task from playing chess to being knowledgeable about chess in a human context: knowing something about the history and role of chess, having knowledge about the roles of kings and queens who do not necessarily stand on chess squares, having reasons to want to win the game, being able to articulate such reasons, and so on. A reasonable test of such knowledge and understanding of context would be answering questions about chess and engaging in a convincing dialogue (in the Turing Test sense) about chess using a human language such as English or Chinese. And now we have a task that is very similar to the original Chinese Room task, to which my comments above pertain.

On the Difference Between Simulation and Re-Creation

This discussion of Searle’s, which he numbers (1), is so hopelessly confused that it is difficult to know where to begin to unravel his tautological and contradictory reasoning.

Let me start with Searle’s stomach analogy. He writes:

What the computer does is a simulation of these processes, a symbolic model of the processes. But the computer simulation of brain processes that produce consciousness stands to real consciousness as the computer simulation of the stomach processes that produce digestion stands to real digestion. You do not cause digestion by doing a computer simulation of digestion. Nobody thinks that if we had the perfect computer simulation running on the computer, we could stuff a pizza into the computer and it would thereby digest it. It is the same mistake to suppose that when a computer simulates the processes of a conscious brain it is thereby conscious.

As I point out in at the beginning of my discussion of Searle’s chapter above, Searle confuses simulation with functionally equivalent recreation. We could indeed stuff a pizza into an artificial stomach. It may have a very different design than an ordinary human stomach, but if properly designed, it would digest the pizza as well, or perhaps even better than, a real stomach (in the case of some people’s stomachs, that probably wouldn’t be so hard to do).

In my chapter and in my book, I discuss the creation of functionally equivalent recreations of individual neurons (which has been done), of substantial clusters of neurons (which has also been done), and, ultimately, of the human brain. I am not talking about conventional neural nets, which involve mathematically simplified neurons, but recreations of the full complexity of the digital-analog behavior and response of human and other mammalian neurons and neuron clusters. And these clusters have been growing rapidly (in accordance with the law of accelerating returns). A few years ago, we could only replicate individual neurons, then we could replicate clusters of tens of neurons, then hundreds, and scientists are now replicating clusters of thousands of neurons. Scaling up to the billions of neurons in the human brain may seem daunting, but so did the human genome scan when first proposed.

I don’t assume that a perfect or near-perfect recreation of a human brain would necessarily be conscious. But we can expect that it would exhibit the same subtle, complex behavior and abilities that we associate with humans. Our wonderful ability to connect chessboard kings to historical kings and to reflect on the meaning of chess, and all of our other endearing abilities to put ideas in a panoply of contexts is the result of the complex swirl of millions of interacting processes that take place in the human system. If we recreate (and ultimately, vastly extend) these processes, we will get comparably rich and subtle behavior. Such entities will at least convincingly seem conscious. But I am the first to agree that this does not prove that they are in fact conscious.

Searle writes:

The computer, as we saw in our discussion of the chess-playing program, succeeds by manipulating formal symbols. The symbols themselves are quite meaningless: they have only the meaning we have attached to them. The computer knows nothing of this; it just shuffles the symbols. And those symbols are not by themselves sufficient to guarantee equivalent causal powers to actual biological machinery like human stomachs and human brains.

Here again, Searle assumes that the methods used by Deep Blue are the only way to build intelligent machines. Searle may assume this, but that is clearly not what my book discusses. There are other methods that do not involve the manipulation of formal symbols in this sense. We have discovered that the behavior and functioning of neurons, while quite complex, are describable in mathematical terms. This should not be surprising, as neurons are constructed of real materials following natural laws. And chips have been created that implement these descriptions, and the chips operate in a very similar manner to biological neurons. We are even putting such chips in human brains to replace disabled portions of those brains, as in the case of neural implants for deafness, Parkinson’s Disease, and a growing list of other conditions.

There is nothing in Searle’s arguments that argues against our ability to scale up these efforts to capture all of human intelligence, and then extend it in nonbiological mediums. As I pointed out above, these efforts are already scaling up very quickly.

Searle writes:

Kurzweil points out that not all computers manipulate symbols. Some recent machines simulate the brain by using networks of parallel processors called “neural nets,” which try to imitate certain features of the brain. But that is no help. We know from the Church-Turing Thesis, a mathematical result, that any computation that can be carried out on a neural net can be carried out on a symbol-manipulating machine. The neural net gives no increase in computational power. And simulation is still not duplication.

It is remarkable that Searle describes the Church-Turing Thesis as a “mathematical result,” but more about that later. Searle here is confusing different results of Church and Turing. Turing and Church independently derived mathematical theorems that show that methods such as a neural net can be carried out, albeit very slowly, on a Turing Machine, which can be considered as a universal symbol-manipulating machine. They also put forth a conjecture, which has become known as the Church-Turing Thesis, which is not mathematical in nature, but rather relates certain abilities of the human brain (in particular its mathematical abilities) to abilities of a Turing Machine.

We know in practical terms that we can precisely replicate neural functioning in electronic devices. No one has demonstrated any practical limits to our ability to do this. In the book, I discuss our efforts to understand the human brain, and the many different schools of thought pursuing the replication of its abilities.

Searle acknowledges that neural nets can be emulated through computation. Well, that only confirms my thesis. Although many contemporary neural nets involve highly simplified models of neurons, a neural net does not necessarily need to be based on such simplified models of biological neurons. They can be built from models of neurons that are just as complex as biological neurons, or even more complex. And doing so would not change the implications of Turing’s and Church’s theorems. So we could still replicate these neural nets through forms of computation. And indeed we have been successfully doing exactly this, and such efforts are rapidly increasing in complexity.

As for simulation not being duplication, as I pointed out above, I am specifically talking about functionally equivalent duplication.

Searle writes:

He [Kurzweil] does not claim to know that machines will be conscious, but he insists that they will claim to be conscious, and will continue to engage in discussions about whether they are conscious, and consequently their claims will be largely accepted. People will eventually just come to accept without question that machines are conscious.

But this misses the point. I can already program my computer so that it says that it is conscious—i.e., it prints out “I am conscious”—and a good programmer can even program it so that it will carry on a rudimentary argument to the effect that it is conscious. But that has nothing to do with whether or not it really is conscious.

As I discussed earlier, Searle frequently changes my statements in critical ways, and in this case has left out the word “convincingly.” Of course one can trivially make a computer claim to be conscious. I make the same point repeatedly. Claims to be conscious neither prove nor even suggest its actual presence, nor does an inability to make such a claim demonstrate a lack of consciousness. What I am asserting, specifically, is that we will meet entities in several decades that convincingly claim to be conscious.

Searle asserts that I assert that people will “just come to accept without question that machines are conscious.” This is a typical distortion of Searle. Many people will accept that machines are conscious precisely because the claims will be convincing. There is a huge difference between idle claims (which are feasible today), and convincing claims (which are not yet feasible). It is the difference between the twentieth and twenty-first centuries, and one of the primary points of my book.

Now what does it mean to be convincing? It means that when a nonbiological entity talks about its feelings, its behavior at that moment and subsequently will be fully consistent with what we would expect of a human who professed such feelings. This requires enormously subtle, deep, and complex behavior. Nonbiological entities today do not have this ability. What I am specifically claiming is that twenty-first century nonbiological entities will.

This development will have enormous implications for the relationship between humans and the technology we will have created, and I talk extensively in the book about these implications.

One of those implications is not that such entities are necessarily conscious, even though their claims (to be conscious) will be convincing. We come back to the inability to penetrate the subjective experience of another entity. We accept that other humans are conscious, but even this is a shared assumption. And humans are not of like mind when it comes to the consciousness of non-human entities such as animals. We can argue about the issue, but there is no definitive consciousness-detector that we can use to settle the argument. The issue of the potential consciousness of nonbiological entities will be even more contentious than the arguments we have today about the potential consciousness of non-human entities. My prediction is more a political prediction than a philosophical one.

As I mentioned earlier, Searle writes: “Actual human brains cause consciousness by a series of specific neurobiological processes in the brain.”

Searle provides (and has provided) no basis for such a startling view. To illuminate where Searle is coming from, I take the liberty of quoting from a letter Searle sent me (dated December 15, 1998), in which he writes

. . . it may turn out that rather simple organisms like termites or snails are conscious. . .The essential thing is to recognize that consciousness is a biological process like digestion, lactation, photosynthesis, or mitosis, and you should look for its specific biology as you look for the specific biology of these other processes.

I wrote Searle back:

Yes, it is true that consciousness emerges from the biological process(es) of the brain and body, but there is at least one difference. If I ask the question, “does a particular entity emit carbon dioxide,” I can answer that question through clear objective measurement. If I ask the question, “is this entity conscious,” I may be able to provide inferential arguments—possibly strong and convincing ones—but not clear objective measurement.

With regard to the snail, I wrote:

Now when you say that a snail may be conscious, I think what you are saying is the following: that we may discover a certain neurophysiological basis for consciousness (call it “x”) in humans such that when this basis was present humans were conscious, and when it was not present humans were not conscious. So we would presumably have an objectively measurable basis for consciousness. And then if we found that in a snail, we could conclude that it was conscious. But this inferential conclusion is just a strong suggestion, it is not a proof of subjective experience on the snail’s part. It may be that humans are conscious because they have “x” as well as some other quality that essentially all humans share, call this “y.” The “y” may have to do with a human’s level of complexity or something having to do with the way we are organized, or with the quantum properties of our tubules (although this may be part of “x”), or something else entirely. The snail has “x” but doesn’t have “y” and so it may not be conscious.

How would one settle such an argument? You obviously can’t ask the snail. You can’t tell from its fairly simple and more-or-less predictable behavior. Pointing out that it has “x” may be a good argument and many people may be convinced by it. But it’s just an argument, it’s not a direct measurement of the snail’s subjective experience. Once again, objective measurement is incompatible with the very concept of subjective experience.

And indeed we have such arguments today. Not about snails so much, but about higher level animals. It is apparent to me that dogs and cats are conscious, and I think you mentioned that you accept this as well. But not all humans accept this. I can imagine scientific ways of strengthening the argument by pointing out many similarities between these animals and humans, but again these are just arguments, not scientific proof.

Searle expects to find some clear biological “cause” of consciousness. And he seems unable to acknowledge that either understanding or consciousness may emerge from an overall pattern of activity. Other philosophers, such as Daniel Dennett, have articulated such “pattern emergent” theories of consciousness. But whether “caused” by a specific biological process or by a pattern of activity, Searle provides no foundation for how we would measure or detect consciousness. Finding a neurological correlate of consciousness in humans does not prove that consciousness is necessarily present in other entities with the same correlate, nor does it prove that the absence of such correlate indicates the absence of consciousness. Such inferential arguments necessarily stop short of direct measurement. In this way, consciousness differs from objectively measurable processes such as lactation and photosynthesis.

Searle writes in his chapter: “It is out of the question, for purely neurobiological reasons, to suppose that the chair or the computer is conscious.”

Just what neurobiological reasons is Searle talking about? I agree that chairs don’t seem to be conscious, but as for computers of the future that have the same complexity, depth, subtlety, and capabilities as humans, I don’t think we can rule out the possibility that they are conscious. Searle just assumes that they are not, and that it is “out of the question” to suppose otherwise. There is really nothing more of a substantive nature to Searle’s “arguments” than this tautology.

Now part of the appeal of Searle’s stance against the possibility of a computer being conscious is that the computers we know today just don’t seem to be conscious. Their behavior is brittle and formulaic, even if they are occasionally unpredictable. But as I pointed out above, computers today are still a million times simpler than the human brain, which is at least one reason they don’t share all of the endearing qualities of human thought. But that disparity is rapidly shrinking, and will ultimately reverse itself in several decades. The twenty-first century machines I am talking about in the book will appear and act very differently than the relatively simple computers of today.

Searle may assert that the level of complexity and capacity is irrelevant, that even if nonbiological entities become trillions of times more complex and capable than humans, they inherently just don’t have this mysterious neurobiological basis of consciousness. I have no problem with his believing that, but he should present it simply as his belief, and not wrap it in tautological arguments that provide no basis for such a belief.

The Chinese Room Argument is based on the idea that it seems ridiculous that a simple machine can be conscious. He then describes a simple machine successfully carrying out deep, extremely complex tasks such as answering unanticipated questions in Chinese. But simple machines would never accomplish such tasks. However, with regard to the extremely complex machines that could accomplish such difficult and subtle tasks, machines that would necessarily match or exceed the complexity of the human brain, the Chinese Room tells us nothing about their consciousness. It may be that consciousness emerges from certain types of very complex self-organizing processes that take place in the human brain. If so, then recreating the essence of these processes would also result in consciousness. It is certainly a plausible conjecture.

Searle writes:

Kurzweil is aware of this objection and tries to meet it with a slippery-slope argument: We already have brain implants, such as cochlear implants in the auditory system, that can duplicate and not merely simulate certain brain functions. What is to prevent us from a gradual replacement of all the brain anatomy that would preserve and not merely simulate our consciousness and the rest of our mental life? In answer to this, I would point out that he is now abandoning the main thesis of the book, which is that what is important for consciousness and other mental functions is entirely a matter of computation. In his words, we will become software, not hardware.

Once again, Searle misrepresents the essence of my argument. As I described in my chapter in this book and in greater detail in my book, I describe this slippery-slope scenario and then provide two strong arguments: one that consciousness is preserved, and a second argument that consciousness is not preserved. I present this specifically to illustrate the contradictions inherent in simplistic explanations of the phenomenon of consciousness. The difficulty of resolving this undeniably important issue, and the paradoxes inherent in our understanding of consciousness, stem, once again, from our inability to penetrate subjective experience with objective measurement. I frequently present the perplexity of the issue of consciousness by showing how reasonable and logical arguments lead us to contradictory conclusions. Searle takes one of these arguments completely out of context and then presents that as my position.

As for “abandoning the main thesis of [my] book, Searle’s assertion is absurd. The primary thesis of the book is exactly this: that we will recreate the processes in our brains, and then extend them, and ultimately merge these enhanced processes into our human-machine civilization. I maintain that these recreated nonbiological systems will be highly intelligent, and use this term to refer to the highly flexible skills that we exhibit as humans.

On the Difference Between Intrinsic (Observer Independent) and Observer-Relative Features of the World

With regard to Searle’s argument that he numbers (2), I will respond briefly as many of the points have already been covered. First of all, I will point out that from a prevalent interpretation of quantum theory, all features of the world are rendered as observer-relative. But let’s consider Searle’s distinction as valid for the world as it appears to us.

Searle writes:

In a psychological, observer-independent sense, I am more intelligent than my dog, because I can have certain sorts of mental processes that he cannot have, and I can use these mental capacities to solve problems that he cannot solve. But in this psychological sense of intelligence, wristwatches, pocket calculators, computers, and cars are not candidates for intelligence, because they have no mental life whatever.

Searle doesn’t define what he means by mental life. But by any reasonable interpretation of the term, I would grant that Searle’s observation is reasonable with respect to pocket calculators, cars, and the like. The statement is also reasonable with regard to today’s computers. But as for the “computers” that we will meet a few decades from now, Searle’s statement just reveals, once again, his bias that computers are inherently incapable of “mental life.” It is an assumption that produces an identical conclusion, one of Searle’s many tautologies.

If by “mental life,” Searle is talking about our human ability to place ideas in a rich array of contexts, to deal with subjects in a fluid and subtle way, to recognize and respond appropriately to human emotions, and all of the other endearing and impressive qualities of our species, then computers (nonbiological entities) will achieve—according to the primary thesis of my book—these abilities and behaviors. If we’re talking about consciousness, then we run into the same objective-subjective barrier.

Searle writes:

In an observer-relative sense, we can indeed say that lots of machines are more intelligent than human beings because we have designed the machines in such a way as to help us solve problems that we cannot solve, or cannot solve as efficiently, in an unaided fashion. Chess-playing machines and pocket calculators are good examples. Is the chess-playing machine really more intelligent at chess than Kasparov? Is my pocket calculator more intelligent than I at arithmetic? Well, in an intrinsic or observer-independent sense, of course not, the machine has no intelligence whatever, it is just an electronic circuit that we have designed, and can ourselves operate, for certain purposes. But in the metaphorical or observer-relative sense, it is perfectly legitimate to say that the chess-playing machine has more intelligence, because it can produce better results. And the same can be said for the pocket calculator.

There is nothing wrong with using the word “intelligence” in both senses, provided you understand the difference between the observer-relative and the observer-independent. The difficulty is that this word has been used as if it were a scientific term, with a scientifically precise meaning. Indeed, many of the exaggerated claims made on behalf of “artificial intelligence” have been based on this systematic confusion between observer-independent, psychologically relevant intelligence and metaphorical, observer-relative, psychologically irrelevant ascriptions of intelligence. There is nothing wrong with the metaphor as such; the only mistake is to think that it is a scientifically precise and unambiguous term. A better term than “artificial intelligence” would have been “simulated cognition.”

Exactly the same confusion comes over the notion of “computation.” There is a literal sense in which human beings are computers because, for example, we can compute 2+2=4. But when we design a piece of machinery to carry out that computation, the computation 2+2=4 exists only relative to our assignment of a computational interpretation to the machine. Intrinsically, the machine is just an electronic circuit with very rapid changes between such things as voltage levels. The machine knows nothing about arithmetic just as it knows nothing about chess. And it knows nothing about computation either, because it knows nothing at all. We use the machinery to compute with, but that does not mean that the computation is intrinsic to the physics of the machinery. The computation is observer-relative, or to put it more traditionally, “in the eye of the beholder.”

This distinction is fatal to Kurzweil’s entire argument, because it rests on the assumption that the main thing humans do in their lives is compute. Hence, on his view, if—thanks to Moore’s Law—we can create machines that can compute better than humans, we have equaled and surpassed humans in all that is distinctively human. But in fact humans do rather little that is literally computing. Very little of our time is spent working out algorithms to figure out answers to questions. Some brain processes can be usefully described as if they were computational, but that is observer-relative. That is like the attribution of computation to commercial machinery, in that it requires an outside observer or interpreter.

There are many confusions in the lengthy quote above, several of which I have already discussed. When I speak of the intelligence that will emerge in twenty-first century machines as a result of reverse engineering the human brain and recreating and extending these extensive processes in extremely powerful new substrates, I am not talking about trivial forms of “intelligence” such as found in calculators and contemporary chess machines. I am not referring to the “narrow” victories of contemporary computers in areas such as chess, diagnosing blood cell images, or tracking land terrain images in a cruise missile. What I am talking about is recreating the processes that take place in the human brain, which, as Searle acknowledges, is a machine that follows natural laws in the physical world. It is disingenuous for Searle to maintain that I confuse the narrow calculations of a calculator or even a game-playing algorithm with the sorts of deep intelligence displayed by the human brain.

I do not maintain that the processes that take place in human brains can be recreated in nonbiological machines because human beings are capable of performing arithmetic. This is typical of Searle’s disingenuous arguments: attributing absurd assertions to my book that in fact it never makes, and then pointing to their absurdity.

Another example is his false statement that I assume that the main thing humans do in their lives is compute. I make the opposite point: very little of our time is spent “computing.” I make it clear that what goes on in the human brain is a pattern recognition paradigm: the complex, chaotic, and unpredictable interplay of millions of intersecting and interacting processes. We have in fact no direct means of performing mental computation (in the sense that Searle refers to in the above quote) at all. When we perform “computations” such as figuring out 2+2, we use very indirect and complex means. There is no direct calculator in our brains.

A nonbiological entity that contains an extended copy of the very extensive processes that take place in the human brain can combine the resulting human-like abilities with the speed, accuracy and sharing ability that constitute a current superiority of machines. As I mentioned above, humans are unable to directly transfer their knowledge to other persons. Computers, however, can share their knowledge very quickly. As we replicate the functionality of human neuron clusters, we are not leaving out quick downloading ports on the neurotransmitter strength patterns. Thus future machines will be able to combine human intellectual and creative strengths with machine strengths. When one machine learns a skill or gains an insight, it will be able to share that knowledge instantly with billions of other machines.

On the Church-Turing Thesis

Searle makes some strange statements about the Church-Turing Thesis, an important philosophical thesis independently presented by Alan Turing and Alonzo Church.

Searle writes:

We know from the Church-Turing Thesis, a mathematical result, that any computation that can be carried out on a neural net can be carried out on a symbol-manipulating machine.

Searle also writes:

[T]he basic idea [of the Church-Turing Thesis] is that any problem that has an algorithmic solution can be solved on a Turing machine, a machine that manipulates only two kinds of symbols, the famous zeroes and ones.

It is remarkable that Searle refers to the Church-Turing Thesis as a “mathematical result.” He must be confusing the Church-Turing Thesis (CTT) with Church and Turing theorems. CTT is not a mathematical theorem at all, but rather a philosophical conjecture which relates to a proposed relationship between what a human brain can do and what a Turing Machine can do. There are a range of versions or interpretations of CTT. A standard version is that any method that a human can use to solve a mathematical problem in a finite amount of time can be expressed as a general recursive function and can therefore be solved in a finite amount of time on a Turing Machine. Searle’s definition only makes sense if we interpret his phrase “algorithmic solution” to mean a method that a human follows, but that is not the common meaning of this phrase (unless we qualify the phrase as in “algorithmic solutions implemented by a human brain”). The phrase “algorithmic solution” usually refers to a method that can be implemented on a Turing Machine. This makes the Searle definition a tautology.

Broader versions of CTT consider problems beyond mathematical problems, which is consistent with the definition I offer in the book’s timeline. The definition I provided is necessarily simplified as it is one brief entry in a lengthy timeline (“1937: Alonzo Church and Alan Turing independently develop the Church-Turing Thesis. This thesis states that all problems that a human being can solve can be reduced to a set of algorithms, supporting the idea that machine intelligence and human intelligence are essentially equivalent”). In this conception of CTT, I relate problems solvable by a human to algorithms, and use the word “algorithms” in its normal sense as referring to methods that can be implemented on a Turing Machine.

There are yet broader conceptions of CTT that relate the processes that take place in the human brain to methods that are computable. This conjecture is based on the following: (i) the constituent components of brains (e.g., neurons, interneuronal connections, synaptic clefts, neurotransmitter concentrations) are made up of matter and energy, therefore: (ii) these constituent components follow physical laws, therefore: (iii) the behavior of these components are describable in mathematical terms (even if including some irreducibly random elements), therefore: (iv) the behavior of such components is machine-computable.

In Conclusion

I believe that the scale of Searle’s misrepresentation of ideas from the AI community stems from a basic lack of understanding of technology. He is stuck in a mindset that nonbiological entities are only capable of manipulating logical symbols, and appears to be unaware of other paradigms. It is true that manipulating symbols is largely how rule-based expert systems and game-playing programs such as Deep Blue work. But the current trend is in a different direction, towards self-organizing chaotic systems that employ biological-inspired methods, including processes derived directly from the reverse engineering of the hundreds of neuron clusters we call the human brain. Searle acknowledges that biological neurons are machines, indeed that the entire brain is a machine. Recent advances that I discussed above have shown that we can recreate in an extremely detailed way the “causal powers” of individual neurons as well as those of substantial neuron clusters. There is no conceptual barrier to scaling these efforts up to the entire human brain.

Searle argues that the Church-Turing Thesis (it’s actually Church and Turing theorems) show that neural nets can be mapped onto algorithms that can be implemented in machines. Searle’s own argument, however, can be applied equally well to biological neural nets, and indeed the experiments I cite above demonstrate this empirically.

Searle is a master of combining tautologies and contradictions in the same argument, but his illogical reasoning to the effect that machines that demonstrate understanding have no understanding does nothing to alter these rapidly accelerating developments.

Copyright ę 2002 by the Discovery Institute. Used with permission.

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		language posted on 06/25/2002 1:30 AM by rtb333@hotmail.com	[Top] [Mind·X] [Reply to this post]
	I am writing in the hopes that someone would give me a straight answer to a straight question: Is it possible or not that we will soon have adequate CAT spoken translation between natural languages? K says that this will be normal between major language pairs by 2009 (haven't the book in front of me at the moment, so correct me if I'm wrong, please). My reason for asking is this: I am an Applied Linguist much involved in the training of teachers of foreign languages (esp. English) and in the training of translators and interpreters. If wire-less interpreting via computers will be commonplace in a few years (I speak English and you hear me in a different language), there seems no future for the learning of foreign languages nor for translating texts or interpreting speech. If this is going to be the case, what do I say to my colleague and their students? I live and work in Malaysia where, since even before Independence nearly 50 years ago, there has been endless debate and shifts in educational policy over the relationship between the national language (Malay) and English (the ex-colonial language)resulting in a generation whose Malay is excellent but whose English is weak. The latest change in policy is to start teaching science and mathematics in English but retain Malay as medium of instruction at all levels for all other subjects. Am I to try to motivate learners of English by telling them that there will always be a need for bilinguals (i.e. K is wrong)or sit down urgently with my colleagues and the educational planners and face the fact that the bilingual is about to become an anachronism (i.e. K is right)? Bests Roger

		Re: language posted on 06/25/2002 3:12 AM by skoobysnkz@attbi.com	[Top] [Mind·X] [Reply to this post]
	I would suggest a much simpler approach. Wait and see but always be prepared for the worst. <I> that way your never disappointed and rarely caught with your pants around your ankles (: </I> Anyways, even after the actual technology is developed there will still be demand for linguists for quite some time. For 1 -- People like talking to people more than they do machines. (At least that is the case now and at least until the majority of my generation dies. And I'm only in my 20's). For 2 -- every program has bugs (not excluding human thought) somebodys gotta know enough to find them. Hey, thats you!! So dont fret too much too soon. ;)

		Re: language posted on 06/25/2002 9:17 PM by rtb333@hotmail.com	[Top] [Mind·X] [Reply to this post]
	Huge sighs of relief. I won't give up my day job and I'll tell my colleagues not to either but: 1. What do we tell the students? If I was a teenager studying a foreign language and told (by some people, though not all) that within 10 (20...50..) years it would all be pointless....? 2. As I understand K, one wouldn't talk to a machine. Isn't the idea that you have a tiny computer buried in your clothes or wherever and just talk? The other person who would be standing/sitting(whatever) right in front of you would have no impression that you weren't just talking in his/her own language. No visible machines at all. Of course the lip movements etc would be out but we're used to dubbed films where that happens all the time and it doesn't bother us much. 3. The excursus on Joyce was fun but not what I was personally after nor would the translation of such WRITTEN texts be of much interest to the Malaysian teenager. My focus is on good old bread and butter, day to day conversational exchanges: Searle's speech acts of asserting, agreeing, promising, warning etc. Can I steer the discussion towards face-to-face interaction. That's where the challenge is, I think. Syntax is pretty easy, semantics (context free, literal, semantic sense) is tougher and pragmatics (context sensitive communicative value) is toughest of all because it demands a thorough understanding of the cultural implications of what is going on i.e. producing utterances which are not only grammatical but acceptable/appropriate. Grammaticality relates to what is possible according to the rules of the code (what CAN be said); acceptability concerns what is appropriate in a particular set of circumstances and that means taking into account who is involved, what their relative statuses is (are!), when, where, why the interaction is taking place and so forth. 'Hi Liz. How's the old man and the kids' is OK as a greeting to my daughter-in-law, who is called Elizabeth, and referring to my son and grandsons but addressed to Her Britannic Majesty Queen Elisabeth II, by the Grace of God.... it would play havoc with my chances of getting a Knighthood, wouldn't it? Children acquire language through their senses and their perception of the whole communicative environment: the order goes (crudely speaking), pragmatics, semantics, syntax. The computers (and long-suffering students of linguistics) go the other way and come to the context (the 'real world') last. 'There's (just to chuck in a literary quote)'the rub'. Bests Roger

		Re: language posted on 06/26/2002 12:50 AM by thp@studiooctopussy.com	[Top] [Mind·X] [Reply to this post]
	>Searle's speech acts of asserting, agreeing, >promising, warning etc. Do not listen to Searle. He is not in touch with what is currently possible and what will be within the next 10 years. If he was he would dismiss his own Chineese room argument.

		Re: language posted on 06/25/2002 3:33 AM by tomaz@techemail.com	[Top] [Mind·X] [Reply to this post]
	K. is right of course. But that will be a small change, compared to others which will come. - Thomas

		Re: language posted on 06/25/2002 12:02 PM by thp@studiooctopussy.com	[Top] [Mind·X] [Reply to this post]
	K. IS right, there is not doubt about it. As tomaz so truthfully have pointed out before, we exist of non living matter that doesen't understand chineese seperately. My neurons don't understand chinesese either, yet through casual feedbackloops, the illusion is kept in "equillibrium"

		Re: language posted on 06/25/2002 12:18 PM by tomaz@techemail.com	[Top] [Mind·X] [Reply to this post]
	> As tomaz so truthfully have pointed out before, we exist of non living matter that doesen't understand chineese seperately. I don't rember, that I have. Somebody else was faster. I just agree. ;) - Thomas

		Re: language posted on 06/25/2002 12:24 PM by Thp@studiooctopussy.com	[Top] [Mind·X] [Reply to this post]
	Well actually I pointed out that neurons didn't understand Chineese but you made the really good point of us consisting of none-alive matter (atoms)

		Re: language posted on 06/25/2002 10:07 AM by grantc4@hotmail.com	[Top] [Mind·X] [Reply to this post]
	If you want to see how far they have to go to put you out of business, take the best translation program you can find and feed it a page of James Joyce's Ulyses. Then tell it to translate that back into English. When a machine can handle that task with any fidelity, it's time to get a new job. I figure you're good for maybe 50 to 100 years.

		Re: language posted on 06/25/2002 11:34 AM by tomaz@techemail.com	[Top] [Mind·X] [Reply to this post]
	Grant! This is the result of your procedure, applied to your text, with the altavista's translator. If you wish to see how they must go far to put to him of business, she takes the best program from the translation that you can find and feed a page to him on Ulyses de James Joyce. Then dÝgalo to translate that within English again. When a machine can handle that task with any fidelity, it is hour to find a a new job. I calculate to him I am good by perhaps 50 to 100 years. - Thomas

		Re: language posted on 06/25/2002 4:36 PM by grantc4@hotmail.com	[Top] [Mind·X] [Reply to this post]
	Like I said, Roger shouldn't give up his day job yet. And that wasn't even Joyce. ;-)>

		Re: language posted on 06/25/2002 5:05 PM by thp@studiooctopussy.com	[Top] [Mind·X] [Reply to this post]
	You will have to give up your day job very soon. Within the next 5 years we are going to have a pretty useful babelfish, withing 10 years almost perfect translation. I have some friends who are working on a new technology that will revolutionise error correction for written and spoken words. That technology will be ready within the next 2 years. Kind Regards Thomas P

		Re: language posted on 07/01/2002 10:10 PM by rtb333@hotmail.com	[Top] [Mind·X] [Reply to this post]
	The Babel Fish: where can I read about it (other than the Hitch-hikers Guide, of course!? Whose working on it? How do I get in touch with them? Thanks. Roger

		Re: language posted on 11/15/2004 6:13 PM by Cyprian	[Top] [Mind·X] [Reply to this post]
	I have some friends who are working on a new technology that will revolutionise error correction for written and spoken words. That technology will be ready within the next 2 years. It's almost 2005. Did this technology ever see the light of day?

		Re: language (Ulysses) posted on 06/25/2002 5:10 PM by grantc4@hotmail.com	[Top] [Mind·X] [Reply to this post]
	Here's a look at the kinds of problems the machine will have to cope with in the process: Language -- September 1995 "Ulysses" in Chinese The story of an elderly pair of translators and their unusual bestseller by Cait Murphy XIAO Qian, a Chinese war correspondent and a literature student, stood over the grave of James Joyce in 1946 in Zurich and mourned, "Here lies the corpse of someone who wasted his great talents writing something very unreadable." Forty-nine years later Xiao still thinks that Joyce carried his virtuosity too far. He has earned the right to his reservations: he and his wife, Wen Jieruo, have just finished a labor that might have humbled Hercules--translating Ulysses into Chinese. "In old age one should do something monumental," says Xiao, who is eighty-five. "This translation is quite monumental." As the name implies ("Ulysses" is a Romanization of "Odysseus"), Ulysses is organized around the Greek myth known as the Odyssey. Homer's saga tells the story of Odysseus, the king of Ithaca, who sails with his army to sack the city of Troy. Odysseus has some difficulty getting back home. Only after ten years, and a goodly number of Boy's Own adventures, is he restored to his faithful wife, Penelope, and his stalwart son, Telemachus. Joyce masticates Homer's Odyssey and spits it out in his saga of a day (June 16, 1904) in the life of two Dubliners, Leopold Bloom (Ulysses) and Stephen Dedalus (Telemachus). Penelope is represented by Bloom's not-so-faithful wife, Molly. Ulysses does not slavishly follow the Odyssey, though each episode in the ancient tale has a counterpart in the modern one. For example, in one Homeric episode Odysseus descends to Hades, the world of the dead; in Joyce's version Leopold Bloom--a Jew and therefore, like Odysseus, an outsider--goes to a funeral. If Homer marks the beginning of Western literature, Joyce suggested, Ulysses was its culmination. "The task I set myself technically in writing a book from eighteen different points of view and in as many styles," he wrote to his benefactress, Harriet Shaw Weaver, "all apparently unknown or undiscovered by my fellow tradesmen, that and the nature of the legend chosen would be enough to upset anyone's mental balance." Xiao and Wen don't need to read Joyce's paean to his own genius to appreciate the mental upsets that Ulysses can produce. "There are places," Xiao says, "where I think he made it unnecessarily difficult." His fellow translators can only agree. Ulysses has been translated into more than twenty languages, including Icelandic, Arabic, Malayalam, and, fittingly, Irish. Perhaps the surprising thing is not that it has now been translated into Chinese but that the translation is only now available. Much of the delay can be attributed to the antipathy of the Chinese Communists toward bourgeois liberal Western culture. Joyce's work became caught in the Chinese government's straitened view of literature's role--that it should extol the morally upright deeds of workers, peasants, and soldiers. Ulysses--bawdy, irreverent, and anti-heroic--hardly suits. Nor did the Maoist cultural commissars appreciate the literary merits of Ulysses, considering it too pessimistic, subjective, and personal. And perhaps worst of all, it was not concerned nearly enough with the great theme of class struggle. Even with the end, in 1976, of the Cultural Revolution, in which China tried to purge all foreign influences (except Marxism) from the land, Xiao and Wen were confined to translating only what was deemed to be safe material, such as the work of Henry Fielding, Charles Lamb, and Arthur Schlesinger Jr. So when the two were just about ready to publish their translation, Xiao took the precaution of writing a series of articles for the Chinese press describing the American trial in 1933 that established that Ulysses was not a dirty book. China would look backward, he argued, if it were to ban or censor the book six decades later. Xiao also pointed out the book's "progressive" stance: it was anti-anti-Semitic and anti-imperialistic. The strategy worked. Published last year, with no interference, the first edition of the three-volume translation sold out its 85,000 copies; a second and a third edition were rushed into print. "We publishers had to be brave to take this kind of risk," says Li Jingduan, the editor of Yilin Publishing House, in Nanjing. "I never imagined this book would be so welcomed by the Chinese reader." Considering the price--about $15, or roughly a week's wages for a high school teacher in China--the sales are phenomenal, and the couple have become modest celebrities. They keep clippings about their work in two thick albums in their book-cluttered four-room apartment near Tiananmen Square, and clearly enjoy the fuss. Wen positively purrs as she recalls a book-signing in Shanghai that attracted a thousand readers. "Five police officers had to come to keep order," she says. "Very excellent." The story made the front pages of Shanghai's newspapers. Xiao and Wen both have traumatic personal memories of times when China was not nearly so accommodating, and see their translation as a major advance for China's cultural life. "I feel that this translation of Ulysses signifies that China at last has opened herself not only in technology and science but also in literature," Xiao says. Translating Joyce is no party game in any language, of course. Even a simple sentence like "And going forth, he met Butterly" presents dangers. In fact in the book Buck Mulligan and Stephen Dedalus meet no one named Butterly. Mulligan, Stephen's roommate, is just tossing off a clever remark as he and Stephen leave their residence south of Dublin. He is referring, crudely, as is his wont, to the biblical description of Peter after his betrayal of Jesus: "and going forth, he wept bitterly." In English the allusion is obvious enough. In German, though, after much cogitation, the thought has been put this way: they went forth "und weinte Buttermilch"--or "and wept buttermilk." In Chinese it is translated for sound: they "went out and met Ba Teli," meaning "to hope earnestly-special-inside," but in context signaling a group of foreign sounds. Well, okay: the reader is clued in that the phrase is more than it seems. But a lot is lost in translation. Another example: Stephen recalls that he has borrowed a pound from the poet and writer George Russell, who styles himself "A.E." Thinking of his debt, Stephen puns "A.E.I.O.U." In the German, Italian, Czech, and Latvian translations, the expression is simply left as it is, which must be rather baffling to readers. Most others include a native-language gloss. In the 1929 French translation the passage reads "A.E. Je vous dois. I.O.U." In Spanish it is "A.E. Te debo. I.O.U." In Hungarian the vowels are changed, killing the joke: "A.E.K.P." The same is true in Croatian, where an explanation is also added: "A.E.J.V.D (Ja vam dugujem)." "You can only do your best," says Fritz Senn, of the ZŘrich James Joyce Foundation. Senn is an authority on Joyce translation. "But of course, if a joke is explained, it is no longer funny." Right. Is there any way to translate Stephen's witticism about Shakespeare's wife: "If others have their will, Ann hath a way"? Many languages at least share the Roman alphabet, and therefore, to varying degrees, a common corpus of sounds. The name Leopold Bloom looks and sounds much the same from Dublin to Detroit, from Harare to Hanoi. Enter China and the rules change. To begin with, there are only 404 possible phonetic combinations in Mandarin, far fewer than in English. Wordplay is inevitably distorted. And Chinese is ideographic, not alphabetic; "home," for example, is represented by a stylized picture that has traditionally been interpreted to be a pig beneath a roof. Ulysses is not pictorial but aural, and comes alive most vividly when read aloud. To make things more difficult, Chinese is a tonal language. In Mandarin, the official national tongue, there are four possible tones to each sound: high level, rising, falling rising, and falling. The tones make a difference. For a crude example of the sounds, consider using the word "Ma" in these different contexts: "Oh, Ma!" in surprised anger at seeing your mother where she shouldn't be, "Oh, Ma!" in exasperation, "Ma" in sober conversation, and "Oh, it's Maaa" in warning at an unexpected phone call from the matriarch. In Chinese, tones change the meaning of a word, not just the emphasis. The four tones for "ma" mean, respectively, "mother," "hemp," "horse," and "to curse." (A fifth tone for "ma," which is actually atonal, turns a sentence into a question.) Proper names are not always translated syllable for syllable. If "America" were to be written sound for sound--that is, one Chinese character for each syllable--it could be construed as "inferior beautiful beneficial addition." That's not a bad metaphor for Chinese ambivalence toward our country, but the standard term for America is actually mei guo, which sounds like "America" said with a mouthful of marbles. At least the name translates well: "Beautiful Country." Sometimes names are assigned with reference not to sound at all but to the way China understands the world. This magazine, for example, named after a great body of water, is translated as "The Great Western Ocean Monthly." And finally, normal Chinese discourse is sometimes best translated loosely. When Americans see each other on the street, they ask, "How are you?" But when two Chinese acquaintances meet, they greet each other this way: "Chi le ma?"--literally, "Have you eaten yet?" That does not call for a recitation of the day's diet any more than "How are you?" is an invitation to describe one's fitness program. Therefore, in translating Chinese into English, "Chi le ma?" becomes "How are you?" So it's no wonder that Xiao was not altogether thrilled when a Chinese publisher suggested in 1990 that he undertake a translation of Ulysses. Pity the poor soul who has to deal with a fairly typical scrap of Ulysses like this one: [Try running it through your machine translator.] Unsheathe your dagger definitions. Horseness is the whatness of allhorse. Streams of tendency and eons they worship. God: noise in the street: very peripatetic. Space: what you damn well have to see. Through spaces smaller than red globules of man's blood they creepy-crawl after Blake's buttocks into eternity of which this vegetable world is but a shadow. Hold to the now, the here, through which all future plunges to the past. I asked Judy Arase, a translator, to find this passage in the Chinese translation and then, without reference to Ulysses, translate it from the Chinese back into English. Here's the result: How about laying bare your dagger-like definitions? That which is the nature of a horse is the essence of all horses. They revere the up-down flow and surging-beginning. God: cries in the street. Downright leisure school of thought. Space: the thing you are bound to see. They slowly crawl towards eternity, boring through spaces smaller than man's red blood cells, chasing after Blake's buttocks. This vegetable world is only but its shadow. Hold tightly to the here and now; all of the future shall surge into the past through it. The translation is inventive and carries something of the texture of Joyce's prose. Still, it's not quite the same: for one thing, it's far too intelligible. Wen was undaunted by the complexities; indeed, she was positively eager to take a crack at Joyce. Then sixty-two, and recently retired from a career as a translator of Japanese and the editor of other people's English translations, she felt it was time to put her skills to the test. "In Chinese there is an expression, `Only the head, not the tail'"--meaning that a work has been started but not completed. "For forty years I only polished the translations of others. I never had a chance to translate a famous book, a classic. Why not Ulysses?" Eventually she persuaded her husband that they could crack it together. The project has been an act of teamwork from the beginning, with Wen doing the first draft, Xiao applying the polish, and the two of them arguing over the final version. Beginning in October of 1990 they set the following schedule: Rise at 5:00 each morning (Wen often had to rouse her less committed husband), work until 8:00, and pause for breakfast. Then work until lunch, and again into the late afternoon. Wen worked nights and weekends as well, putting in, she figures, fifteen hours a day just about every day. She even gave up television and newspapers. For two years her sister took over the household, doing the shopping, cooking, and cleaning, so that the couple could work. The sister died in 1992; the translation is dedicated to her memory. The couple leaned heavily on published sources to untangle Joycean knots; they cite Don Gifford's annotated Ulysses as a particular help. They consulted the Chinese Catholic Church, foreign-language specialists, geologists, doctors, and others for specialized knowledge. The Irish Embassy helped with specifically Irish references. What's "blarney"? Wen asked. The answer, as translated: "flattery as usual." And "on the shaughraun"? A drifting state of mind. The embassy also provided reference books, maps of Dublin, and a videotape of the movie version of Ulysses, which was invaluable because Wen and Xiao have never been to Ireland. A Canadian resident in Beijing helped research linguistic oddities like "smutty moll for a mattress jig" --Joycespeak for "prostitute." Xiao and Wen were also able to refer to a work in progress by a man named Jin Di, a Chinese literary scholar now living in the United States, who began his own Chinese translation of Ulysses in 1978 but has not yet seen all of it into print. Bits of Jin's work had been published by the time Xiao and Wen began theirs, and they acknowledge that they saw these, though not the twelve chapters that had appeared in Taiwan by 1993. Jin is somewhat chagrined that he has been working longer and yet is finishing later. But there is room for more than one Chinese translation. The Japanese, after all, are on their fourth. Xiao and Wen do not claim that their work is flawless; they are, however, delighted to have published first. "A gold medal is better than the silver one," Wen says. The work is not, in fact, flawless. A sharp-eyed Chinese reader has pointed out a few mistaken translations from the Latin. More important, sometimes things are just missed. Molly and her lover, Blazes Boylan, eat Plumtree's Potted Meat during their assignation; the term is translated as "plum tree trademark canned meat." Good enough, but it misses the pun: "potted meat" was Dublin argot for sex. When Leopold recalls Molly's description of the plump Ben Dollard, that his fine singing voice was a "bass barreltone," the translation does not embody the play on words. His voice and shape, she is saying, are derived from barrels of Bass beer. Joyce experimented with different ways of expressing cat sounds: "mkgnao," "mrkgnao," "mrkrgnao," and, prosaically, "miaow." In Chinese, which does not have the array of sounds English has, the characters don't change. Still, Xiao and Wen don't miss much. First, they adapted Chinese-language tools to the challenge. Most Chinese names have three syllables (Deng Xiaoping, Mao Zedong, Zhou Enlai); the Chinese transliterations of Leopold Bloom and Stephen Dedalus have seven each. Stephen's is rendered phonetically--"Si di fen . Di da le si." The unusual number of characters, the midline period between them, and the use of a few classical (rather than simplified) Chinese characters are all unmistakable signals to the Chinese reader to ignore the meaning and just note that it signifies a name. (A literal translation would be "This-base of a fruit-fragrant. Enlighten-extend-coerce-this.") The practice is similar to using "#%*&!" to indicate a curse in English; a reader doesn't delineate each symbol but just consumes the meaning. Bloom, wandering through a newspaper office, reads in type the name of the friend whose funeral he has just attended: mangiD kcirtaP (Patrick Dignam backward). In Chinese the eight characters used to render the name are likewise reversed. When the moral pub owner, Davy Byrne, "smiledyawnednodded all in one," the issue was trickier. Chinese characters are never smooshed together. Xiao and Wen used a quirk of Chinese grammar that implies simultaneously occurring actions. They also adapted Chinese styles to Joycean ones. Molly, Leopold, and Stephen all have interior monologues, and all sound different. Molly is not very well educated. She occasionally misuses difficult words, and her thoughts, in the famous soliloquy that ends the book, have an earthy resonance. Stephen, the teacher and literary scholar, is philosophical. And Leopold is a middle-class bloke with a big heart who often thinks about sex and bowel movements. So in the Chinese, Molly is rendered in working-class Beijing slang, Stephen mostly in classical Chinese, and Leopold mostly in a mixture of modern and classical that dates from the early twentieth century. By varying the styles, the translation manages to convey the differences in character among the three. When there is no linguistic or literary analogue, which is most of the time, footnotes do the job. So much of Ulysses is built around puns, allusions, and time- and place-specific Irish humor that it really cannot be translated; one must simply plough through. Wen and Xiao made the most readable Chinese translation they could and then explained the Joycean quirks in footnotes--5,991 of them, the most in any Chinese book ever published. Xiao thought that was several thousand too many, but Wen prevailed. The reviews in the Chinese press pay tribute to the couple's thoroughness, and however unwieldly the footnotes may be to read, they are the only way to clue Chinese readers in to Joyce's intentions. Take the pun on Shakespeare's wife, Anne Hathaway (whose name Joyce misspells, incidentally). The translation reads "If other women are capable of following their hearts for that which they desire, Ann herself has her own ways." A footnote makes the point that the original is a pun on "Ann Hathaway." Sometimes--a lot of the time--the explanations are considerably more complex. T. Lenehan bumps into Bloom at a newspaper office and announces, "Madam, I'm Adam. And Able was I ere I saw Elba." In the Chinese text this is translated "Madam, I'm Adam. And before seeing Eve, I was Abel." The footnote fills in the considerable gaps: These two short sentences can be read the same from either end, joined together by "and." "Eva" [Eve] and "Elba" have similar pronunciations. The sound of Adam and Eve's second-born son, "Abel," is similar to "Able"; the quotation can be read as "Madam, I'm Adam. Before seeing Eve, I was Abel." Another reading comes from mixing together the several elements of Napoleon's saying that there is no "cannot" in his dictionary, his post-defeat banishment to the island of Elba, and his impotence; the first phrase can be reconstituted as "Mad am, I mad am," and the latter as "Before seeing Elba, I did not know the word `cannot.'" "Able" can be understood as "can be done" or "not impotent." Elementary, really. Anthony Burgess, no mean Joyce scholar, has said, "Literature cannot be translated, only the appearance of literature, the arrangement on a page of words which do a minimal job, that of describing action, feelings, and dialogue of a fairly easily translatable kind." True enough, and yet . . . so what? By the Burgess standard, the English-speaking monoglot would be cut off from Tolstoy, GarcÝa Mßrquez, and Lu Xun. And even if the poetry doesn't always rise, action, feelings, and dialogue count too. One of the joys of Ulysses is just getting lost in the pub talk and the commonplace to-ings and fro-ings of dear, dirty Dublin. The texture may not--cannot--be exactly the same in Chinese as in English, but it is possible to get a rude, true sense of it. Joyce himself was a gifted linguist who spent his working life as an instructor of languages. He must have known that if Ulysses fulfilled its destiny, it would inevitably find a home beyond English--itself a foreign import to Ireland. In fact, the first translation of Ulysses, a German effort in 1927, came out before the book could be legally published in the United States or Britain. It is difficult to believe that Joyce, hardly parochial in his own work, would frown on the labors of Xiao and Wen. For if Ulysses is the end of literature, as Joyce believed, the remaining eternity must include China, the world's longest-lived civilization. There are limits, though. No one in China is offering to translate Finnegans Wake.

		Re: language posted on 07/08/2002 4:41 AM by normdoering@mad.scientist.com	[Top] [Mind·X] [Reply to this post]
	There has been lot of work done on Natural Language Processing from Parsing to disambiguations and from semantic analysis to context learning. However, I can't pretend to predict when good translators will be in use. One interesting path toward it might be represented by Cyc: http://www.cyc.com/tech.html

		Re: language posted on 07/08/2002 10:33 PM by rtb333@hotmail.com	[Top] [Mind·X] [Reply to this post]
	Thanks for the www. I'll have a look at it and see if it helps. I know a bit about what has been done with parsing etc etc including corpus linguistics but precious little of this seems to have carried over into translation and interpreting. There's the problem, isn't it? Am I being cynical, do you think, if I suggest that applying the fruits of a century of modern descriptive linguistics to translation and interpreting is just too tough a test for where the linguists have got to? Bests Roger

		Re: Chapter 6: Locked in His Chinese Room posted on 06/29/2002 4:08 AM by rtb333@hotmail.com	[Top] [Mind·X] [Reply to this post]
	I have to say I'm rather disappointed. The only responses I've had about computers and spoken translation (i.e. interpreting into and out of SPEECH) have either led off (fasinatingly) into the problems of literary TRANSLATION (i.e. written texts) or have (like the one below) focused on rubbishing Searle. True or not, Searle's Chinese Room argument is NOT what I'm talking about. Presumably, the response was generated by the word 'Searle' and it was that that triggered off the reply about the argument. Let me explain. The Searle I am talking about is the philosopher of language J. R. Searle who wrote (in 1969) an eminently sensible book called 'Speech Acts' in which he attempted to direct the attention of linguists away from Chomskian TG syntax (with a bit of semantics thrown in in 1965 in Aspects of the Theory of Syntax)and onto pragmatics: situated communication. The book had an enormous impact but not so much in 'core' linguistics as in sociolinguistics and psycholinguistics and, hugely, in applied linguistics where it led to communicative syllabuses and far more learner friendly learning activities. The whole effect of THAT Searle's writing was extremely exciting and humanising for language teaching and learning. Now I don't care what the Searle of 199+ says or said or is saying about machines thinking etc. I am no philosopher and the issue of whether what is doing the translating in the Chinese room is thinking or not is of very secondary importance to me. You may find this unacceptable and tell me that I OUGHT to care but I have to say, remember that I'm a practical teacher trainer faced by the immediate task of helping people to learn languages. The analogy I'd like to use is that of the successful driving instructor: if my learners pass their tests, does it matter if they know the principles of the internal combustion engine or the laws of physics and mechanics which drive (pun!) the car? Teaching them this isn't precluded in a driving course (and I do teach my students some linguistics) but isn't that just an added bonus and not essential to driving a car in a way which obeys the rules and is appropriate in the conditions in which the driver finds him/herself? Now back to my question. The test I'm after is not Chinese rooms but a SPEAKER of Chinese and a speaker of English who share no common language and wish to communicate. I'll mark them C and E in the extremely truncated simulation of a little conversation below: C (in Chinese) Would you like a cup of tea? E (in English) Yes please. Here's the test I want to apply. Do C and E, face to face, in a context in which the initial question is not crazy (i.e. there actually IS tea available and something to drink it out of)HEAR what is said to them as English and Chinese respectively and is that C/E grammatically correct and communicatively appropriate? (does it, like the successful driver, obey the rules - of the language - and suit the social conditions of the exchange?) Do the words of C constitute (in Searle 1969's terms)the issuing of a speech act of 'offering' which the computer turns into different words (in English) which count as an equivalent speech act? i.e. the offering of a cup of tea (in the xample above). Does E recognise the communicative value of what C (through the computer) has said? If (s)he does, (s)he will know that the expected response is either to issue a speech act which counts as acceptance or rejection. Does what E says which C hears in Chinese (again via the computer) count as an acceptance (in this case of a cup of tea)? Very pragmatically, does E get the cup of tea or not? If E gets a bowl of rice or C gets a punch in the teeth, the system isn't working adequately but if my test is passed, to the satisfaction of the two speakers (who do not need to be philosophers, AI experts or anything other than just ordinary people), I am satisfied. If the answer is NO, I would like to know when (if ever) this is likely to happen. I have taken the advice I have been given (for which thanks)and am ensuring that my pants have not fallen down without my realising and I haven't given up my day job but I still have heard no hard arguments either way which help me resolve the problem. All I've had so far have been assertions in favour or against the possibility/practicality of such a system. Could someone, please, try and answer MY question? There are over 4000 languages in the world. Ten of these have over 100 million native speakers. International communication is increasingly dominated by a much smaller number. Babel is here. What do we do? Is the Babel fish hooked and being hauled in or still swimming in Chinese rooms full of water (i.e. goldfish bowls)? My goldfish can so far only say his name 'Bob' (they all think they're called Bob)but is looking forword to some multilingual IT help to extend his communicative competence. Bests Roger

		Re: Chapter 6: Locked in His Chinese Room posted on 06/29/2002 5:10 AM by azb0@earthlink.net	[Top] [Mind·X] [Reply to this post]
	Roger, It seems that to answer your question properly, one must make assumptions about the "sophistication" of this babelfish. It it were merely programmed with some "E-word maps to C-word" translation, it would be hopelessly inadequate, I think you would agree. (Aside, we must assume that the babelfish, at least, properly "hears" the input words. If the speaker is mumbling, even a perfect human translator will have difficulty, right?) In English (at least) we often follow a sentence in which one or more nouns were made explicit, with another sentence employing pronouns. Clearly, the bablefish will need to maintain a bit of the "history of the conversation" in order to disambiguate certain phrases in the given context. Even two English speakers can get confused when too many pronouns pile up, and the bablefish would fare no better under such circumstances. Finally (in order to do a really superb job) the babelfish needs to "understand" the logical relationships between thousands of real-world "things", as a further disambiguation mechanism. "The book was read/red" Are we speaking about color? "The book was read/red out loud" Aha, we are NOT referring to the color... etc. I firmly believe ALL of this will come about. How soon, and at what cost, is a matter of some real debate. (Am I one the right track with your question?) Cheers! ____tony____

		Re: Chapter 6: Locked in His Chinese Room posted on 06/29/2002 10:28 PM by rtb333@hotmail.com	[Top] [Mind·X] [Reply to this post]
	Two very helpful replies. Thank you. I was beginning to become unsure that I was communicating with the right group. I think what we have come to is this: 1. Context is the crucial feature 2. Meaning lies in the context not in language. Someone (forget who) said 'Meanings are in people, not in words' 3. We learn to relate meaning in to meaning person to person in context. The language facilitates this. There are(says Dell Hymes)rules of use without the rules of usage (i.e. grammar) would be, literally useless. 4. How can/when will the computer learn to find contextual meaning? 5. How can it get the practice it needs? Any of the AI people have answers to 4 and 5? Great. Keep it going. Bests Roger

		Re: Chapter 6: Locked in His Chinese Room posted on 06/30/2002 2:57 AM by tomaz@techemail.com	[Top] [Mind·X] [Reply to this post]
	> 4. How can/when will the computer learn to find contextual meaning? Computer has to simulate the outside world. Just as we do. We simulate a large portion of what MIGHT somebody think, when saying this or that. What (visual) pictures might go along with her talking, what she is going to do. We are not always very good at this, so not need computer to be, but that is, what the language is all about. A simulation language for the (social) world is the natural language. We would need 100 years or so, to teach the computer program to do that. But when things go automatization - 10 years from now. IMHO. - Thomas

		Re: Chapter 6: Locked in His Chinese Room posted on 06/30/2002 12:42 PM by rtb333@hotmail.com	[Top] [Mind·X] [Reply to this post]
	Tomaz don't go all gnomic on me. I was doiung fine with your reply till I hit 'when things go automization'. What DO you mean? I hazard a guess that you are contrasting some pre 'automization' process of 'experts' teaching the computer about the 'real world' with some post 'automisation' process. If I'm right and, especially, if I'm wrong, please explain. Bests Roger

		Re: Chapter 6: Locked in His Chinese Room posted on 06/30/2002 2:44 PM by tomaz@techemail.com	[Top] [Mind·X] [Reply to this post]
	Roger! What do I mean with the automatization of the language learning process. First you have a random world&language model. You test, how often your model sees in the pictures on the net, what is written bellow them. Then you randomly do some child model of the first model and see which do the best. After some generations, you get a working model, which understands (many) language(s) and recognizes the pictures and sounds. Simple, isn't it? You do need a substantial amount of CPU, that's right. - Thomas

		Re: Chapter 6: Locked in His Chinese Room posted on 06/30/2002 3:27 PM by tomaz@techemail.com	[Top] [Mind·X] [Reply to this post]
	http://www.sciam.com/article.cfm?articleID=000C3551-C705-1D18-8B07809EC588EEDF&catID=1 This is, of what I am talking about. ;) - Thomas

		Re: Chapter 6: Locked in His Chinese Room posted on 07/02/2002 2:24 AM by rtb333@hotmail.com	[Top] [Mind·X] [Reply to this post]
	Tomaz. Problems with ooening the article. It's Scientific American, that much I've discovered, but I can't get any further. I've typed the address very diligently and carefully but, no luck. Don't be coy: just give us the title and we'll go back to the old ways (i.e. look in the periodicals section of the library!). Bests Roger ps hope this is in the right place. Help!

		Re: Chapter 6: Locked in His Chinese Room posted on 06/29/2002 10:47 AM by grantc4@hotmail.com	[Top] [Mind·X] [Reply to this post]
	The important thing about speech in face-to-face situations is the redundancy of language. You are not dealing with just vocabulary and syntax, although these become more important as the communication becomres more complex. But you are also dealing with facial expression, body language, tone of vocie, gestures, etc., etc. For example, if your face-to-face speakers are sitting in the kitchen or the living room next to a pot of tea and two cups (environment being one of the primary elements of redundancy) and C gestures with his hand toward the pot and says, "Ni yau i bei cha ma?" all the while smiling and nodding in the direction of E, I'm pretty sure E will come back with something like "Yes, I'd like that." which C would not understand on a vocabulary basis, but would see by the nodding of E's head, the smile on his face, and the way he leans forward as he speaks that pouring tea into the cup is the proper thing to do. At the same time, E would no doubt pick up the information that "cha" probably means "tea" and file it away until the next time he hears the word in a similar situation. C will pick up on the word "yes" and do the same. Language is based largely on expectation and we tend to hear what we expect to hear. What we expect to hear also depends on the environment and situation. Therefore, language is an adjunct to that environment and is supplemented by the years of learning not only vocabulary but also what is expected in the roles people play in various situations. In other words, the culture of both the speaker and the listener. The role and the situation are both elements of the language and culture we know or wish to learn. I don't know if that answers your question or not, but it's the spoken language situation as I see it after many years of teaching English to Chinese students in Taiwan. I usually summarize my experience by telling them that you learn what you practice. If you practice thinking and speaking you will learn to speak. If you practice listening, you will learn to hear and understand. And if you practice doing little exercises out of a book, that's what you'll learn how to do. Language is a skill. Like any skill, our ability to do it depends a lot on when we started learning (Tiger Woods started playing golf at age four) and how much time we spend practicing the skill we want to learn. Language skills are also separate from each other. Speaking is a different skill from listening or reading and writing. There is some crossover but you shouldn't expect that skill in one will automatically carry over to the others. They are separate skills and use different parts of the brain and the body. Learning to catch a ball won't teach you much about throwing one, but it's hard to do one without also doing the other. That applies to language as much as it applies to ball playing.

		Re: Chapter 6: Locked in His Chinese Room posted on 07/01/2002 6:20 AM by rtb333@hotmail.com	[Top] [Mind·X] [Reply to this post]
	Look very simple indeed. Would I be accused of being cynical if I used the word 'simplistic' instead? :-) The problem (and I suppose we need a philosopher to tell us whether this is just an 'in practice' one or 'in principle')is the model. I have spent forty years looking at such models (not computer ones though)as a major challenge for sociolinguistics and we've got somewhere but it's been very very slow. Are you thinking of a culturally and linguistically aware adult acting as the 'expert' inthe creation of an expert system? Is this the sort of line that is being followed? If so, I will seriously think about giving up my day job and applying for that! Is there a dummies' guide to all this? I mean the kind of equivalent of Sesame Street for the pre- or is it proto-) computer literate like me? Thanks. I'm enjoying this. Bests Roger

		Re: Chapter 6: Locked in His Chinese Room posted on 07/01/2002 2:12 PM by tomaz@techemail.com	[Top] [Mind·X] [Reply to this post]
	Roger! I assume, that you are referring to me, despite the place order. ;) Yes ... I think, we can do this. But instead of the initial random model, we could use yours. And put it through the digital evolution - why not. There were a lot of people, who dedicated their lives, to the quest for new alloys. But now it seems - the computer will evolve every possible alloy in a few years. Sad? No reason to be. It's a celebration time! - Thomas

		Re: Chapter 6: Locked in His Chinese Room posted on 07/01/2002 3:02 PM by s_paliwoda@hotmail.com	[Top] [Mind·X] [Reply to this post]
	Thomas! This is a little bit off topic, but I would like to ask you one thing, namely, when will Singularity happen? Slawek

		Re: Chapter 6: Locked in His Chinese Room posted on 07/01/2002 3:35 PM by tomaz@techemail.com	[Top] [Mind·X] [Reply to this post]
	It's not off topic. When this Digital Evolution Intelligence (DEI) will be fashionable ... the Singularity Is Near. ;)) No way 2040, but half of it! (~2020) - Thomas

		Road to Singularity posted on 07/01/2002 4:43 PM by s_paliwoda@hotmail.com	[Top] [Mind·X] [Reply to this post]
	Not off topic but a little bit off topic. Anyway, I like your optimism, and enjoyed your double translation earlier in this discussion. That was impressive. Now, if you don't mind, could you outline the sequence of events (with years) leading to Singularity in 2020? Slawek

		Re: Road to Singularity posted on 07/01/2002 6:27 PM by tomaz@techemail.com	[Top] [Mind·X] [Reply to this post]
	Slawek! There are several roads to the Singularity. More or less parallel. One would be suficient, but there is more than one way. Let me mention two! The digital simulation. We are about to simulate the real physics. Instead of doing experiments which processor behaves better or has better performance, we will be able to simulate any physical machine (for example a CPU), how it behaves, inside a (super)computer. We will not begin with the processors, but with the atomic bombs, for example. At first, the simulation couldn't match with the real blow up of an A bomb. But soon, it will reveal more and faster, than a real explosion would. The observation with simulation, will soon be more comfortabe, faster and informative, than any classical observation. Now, we are already employing the automatic checkings and controls. And even adjusting the parameters of a simulation. The digital evolution of those parameters inside the program, is also an already well known method. Now those two - simulation and evolution combined - will become one fast road to ever better products, in almost any area of human endeavour. It is even self propeled and accerelated process. What we need, is some critical density of this technology - and we are on! From supercomputers, drugs, RAMs, bridges, jet engines ... to algorithms or programs ... we will do that way. Where does it stop? On the other side of the Singularity somewhere - I guess. This is the shortest path from here to the Singularity - I think. How far is it? Not very. How fast it will go? Faster and faster. - Thomas

		Re: Road to Singularity posted on 07/01/2002 10:50 PM by s_paliwoda@hotmail.com	[Top] [Mind·X] [Reply to this post]
	Interesting. I've heard about that bomb simulation. It's supposed to be done on one of the new supercomputers, isn't it? As for other simulations, when are they going to be done routinely, and are you aware of any articles on the net that deal with this particular road to Singularity? Where do you see nanotechnology in all this? Slawek

		Re: Road to Singularity posted on 07/01/2002 11:22 PM by azb0@earthlink.net	[Top] [Mind·X] [Reply to this post]
	I happen to work at the lab where the "ASCI White" (Advanced Strategic Computing Initiative) machine, roughly the most powerful computer on earth, does its simulation stuff. Not my area (I do R&D for network/information security with CIAC.) They do simulations of chemical and nuclear reactions all the time, even with lesser machines. The issue is how finely one can detail the smallest interactions in sufficient number to get results that mirror what would happen physically. Certain weapons-grade materials decay naturally, and neutron flux weakens surrounding materials, so all of these things are fair game for simulation, when you cannot do "real" testing. These machines also simulate the details of varied models of turbulence, global weather stuff, etc. The are breaking ground for a new facility called the "Terascale Computing Facility", expected to house a system 100-1000 times as powerfile as ASCI White. (By 2005, or so, I think.) I would like to see them applying such power to areas more interesting than simulating explosions. There are other areas of "strategic concern". Of course, for all I know, they may use it to analyse all network traffic and deduce who all the players are, not by the "handles" they go by, but by a thousand other clues we leave behind. I would like to see that power applied to AI, but that is likely not a high priority, despite the DARPA call for "intelligent" systems. Cheers! ____tony____

		Re: Road to Singularity posted on 07/02/2002 3:20 AM by tomaz@techemail.com	[Top] [Mind·X] [Reply to this post]
	tony! When one masters A bomb simulations, everything else - like nano robot simulations - will just follow as a business opportunity driven commercialization. 1000 times more CPU than today, is just staggering. So, shortly after 2005, we should be able to simulate the CPU (parts) - for example. To get some more CPU power. And so on. Byproducts like drugs and machines, will be money driven necessity - I guess. What am I doing now? Just simulating the near future inside my head - of course. - Thomas

		Re: Road to Singularity posted on 07/02/2002 5:03 AM by azb0@earthlink.net	[Top] [Mind·X] [Reply to this post]
	Thomas, There is an important difference between simulating a thermonuclear explosion, and (say) correctly simulating even a a single E. Coli cell. A long history of carefully "smashing particles", a few at a tome, in accelerators, has yielded details about the mass, energies, spins, and forces of their internal "structures" (gluon/quark/hadron...) and so forth, allowing very accurate predictions to be made about how "small numbers" of such things would interact. Armed with accurate "small-numbers" information, one then applies "huge simulations" to examine how these effects interact when billions are (simulated) to get compressed together. Now, I'm not saying this is simple. It is complex, scores of particle types and multiple forces with differing effects/ranges, etc. But compared to the complexity of a single biological cell, it is simple indeed. In order to accurately simulate a single living sell IN DETAIL, you need to do the equivalent of the "atom smashing", and understand the "small-numbers" information. But even the simplest protein molecule is far more complex than a simple nucleus of uranium or plutonium, and the number of different types of protein molecules is enormous. Internal cellular structures like ribosomes are another order or two of greater magnitude in complexity, etc. And the living cell is a virtual city of thousands of such structures. They cannot be simulated with any accuracy by just guessing, willy-nilly, at their individual interaction types, forces, forms, etc. This "small-numbers information" must be garnered first, in order to feed the model, and have anything emulating "biology in detail" appear as a result. Moreover, although we understand the detailed QM behaviors of atoms and subatomic stuff, and the "classical physics" of large scale stuff, the forces at work in the "middle regime" were both QM and classical behaviors manifest is only beginning to be explored. New "Operating Principles" for this regime are being discovered all the time, and this is the "scale of the nanobots". So we need to understand this "physics" in order to give the computer something to "simulate with". My complaint: We are employing these very huge (and very expensive) machines to simulate the "very simple, in huge scale" (what happens when you pound sand with a really big hammer) as opposed to simulating the relatively complex and interesting (self-evolving genetic algorithms, etc.) Huge machines to support huge simulations is a great research tool, but using it to simulate a trillion simultaneous games of tic-tac-toe is not likely to lead to the singularity... :( ____tony____

		Re: Road to Singularity posted on 07/02/2002 5:56 AM by tomaz@techemail.com	[Top] [Mind·X] [Reply to this post]
	tony! QM is just enough to operate with. You need a midscale physics just as an optimization tool. A nanorobot can be modeled by the today knowledge of physics. There is nothing - except that a lot of computing is to be performed - what can prevent us from simulating any molecule tower. We have some partial solutions inside (bio) chemistry, like those you have mentioned as the accelerator data in (sub)atomic physics. We will be able to employ this simulation/evolution technique in a few years, I am quite confident. Jet engines, turbines, alloys ... are just the humble begging. The living cell may be reachable in 10 or so years. After several improvements will be made - in tools. That is my whole point. - Thomas

		Re: Road to Singularity posted on 07/02/2002 12:25 PM by s_paliwoda@hotmail.com	[Top] [Mind·X] [Reply to this post]
	Yes, I would also prefer to use all that power to create better, more advanced technology. Perhaps, it might be used for AI in the future. If not, maybe someday there will be an AI project in need of distributed computing power similar in that respect to the one set up by SETI. I would definitely donate my share of CPU power to something like that. Slawek

		Re: Road to Singularity posted on 07/02/2002 12:56 PM by tomaz@techemail.com	[Top] [Mind·X] [Reply to this post]
	Slawek! Who says anything about donating? I know you would donate. I am donating it all the time to some distributed computing effort. Don't know and don't care what they are really doing. But we are in a minority. When the time will be right (soon) for a massive AI internet computing, it should have a bait! "We will tip you for a good stock purchase (or something of that kind) - every time you will donate us a trillion CPU ops. Here is the history of our tips and statistics. THIS AI is 30% commited to those calculation, 70% to some important stuff ... blah, blah, blah ..." Something like that! This way, it will be possible to buy 10^17 ops in 2005. - Thomas

		Re: Road to Singularity posted on 07/02/2002 3:12 AM by tomaz@techemail.com	[Top] [Mind·X] [Reply to this post]
	Slawek! I don't know for any link to the simulation (evolution) driven Singularity. It's nothing more than my (rational) bet. Our thinking is nothing else, than "what if" simulations. And if we can do it inside computer faster and better - the thinking business will go there, I would say. - Thomas

		Re: Road to Singularity posted on 07/02/2002 12:32 PM by s_paliwoda@hotmail.com	[Top] [Mind·X] [Reply to this post]
	You bring up a good point since it's safe to assume that once the whole world goes virtual, further development of technology will occur in this environment as well. Slawek

		Re: Chapter 6: Locked in His Chinese Room posted on 07/01/2002 10:21 PM by rtb333@hotmail.com	[Top] [Mind·X] [Reply to this post]
	Yes. I was intended for you. Maybe I put it in the wrong place. Sorry. Please don't misunderstand about models. I haven't got one: wish I had. What I 'have' is bits and pieces of models from lots of other people but there is nothing cohesive or comprehensive yet. I'm going to download the article today and see if that helps. Bests Roger

		Re: Chapter 6: Locked in His Chinese Room posted on 08/27/2002 7:17 PM by boca_de_verity@yahoo.com	[Top] [Mind·X] [Reply to this post]
	I've only read the first couple of lines but it appears Searle is way out of Kurzweil league. I doubt that Searle argued that machines can only maipulate sysbols, but only that symbol manipulation alone would never produce understanding.

		Re: Chapter 6: Locked in His Chinese Room posted on 08/27/2002 11:26 PM by claire@cthisspace.com	[Top] [Mind·X] [Reply to this post]
	"Meaning" is analog. Claire

		Re: Chapter 6: Locked in His Chinese Room posted on 08/28/2002 10:42 PM by grantc4@hotmail.com	[Top] [Mind·X] [Reply to this post]
	All of human culture and civilization is based on symbol manipulation. That doesn't seem trivial to me.

		Re: Chapter 6: Locked in His Chinese Room posted on 08/28/2002 11:37 PM by azb0@earthlink.net	[Top] [Mind·X] [Reply to this post]
	Grant, > "All of human culture and civilization is based on symbol manipulation." One might frame the "great symbol/semantic" debate in terms of whether it should be "based on", or "interpreted in terms of". Let me play a bit of Devil's Advocate (or at least explore both sides of the issue, since I don't claim to have answers.) Clearly, all humans (and thus human culture/civilization) are "based on" chemistry. Since human culture requires humans, and humans would support no culture if not for "brains", culture is based upon brains, and brains in turn upon chemistry. One could also characterize culture as "humans involved in "meaning exchange", however this might occur. Since brains (somehow) entertain "meaning", and have evolved to the point of rationality, we can create categories, and VIEW the world in terms of "objects and relations". Thus, however we exchange "meaning" (and however it might be based upon chemistry), we are free to INTERPRET this activity in terms of symbols, and the manipulation of symbols. This description is a conceptual abstraction of something that is nonetheless "physically happening" when humans exchange "meaning". The question thus becomes, if we create artificial systems that conform (only) to match our conceptualization of "culture" in terms of symbol manipulation, is this "as good" as real culture? Do the artificial actors originate "real meaning"? And if they become so advanced that they "seem to" originate meaning and develop culture, do we (humans) have any particular right to denigrate these entities, simply because we happen to understand their origins? Cheers! ____tony b____

		Re: Chapter 6: Locked in His Chinese Room posted on 08/29/2002 11:35 AM by grantc4@hotmail.com	[Top] [Mind·X] [Reply to this post]
	>Clearly, all humans (and thus human culture/civilization) are "based on" chemistry. Since human culture requires humans, and humans would support no culture if not for "brains", culture is based upon brains, and brains in turn upon chemistry. To paraphrase Bill Clinton, it all depends on what you mean by "based on." What I meant when I used it was that without symbols and symbol manipulation we would not have a culture. The symbols I was referring to are the symbols we call memes and words. Without these, we would have a primate we call homo sapiens (but not very sapient), but we wouldn't have culture and civilization. >The question thus becomes, if we create artificial systems that conform (only) to match our conceptualization of "culture" in terms of symbol manipulation, is this "as good" as real culture? Do the artificial actors originate "real meaning"? >And if they become so advanced that they "seem to" originate meaning and develop culture, do we (humans) have any particular right to denigrate these entities, simply because we happen to understand their origins? I'm not sure what you mean by "real culture." To the best of my knowledge, I've never met an artificial culture. As to symbol manipulation, this is just the tool we use to build the institutions of culture. The answer to "Do artificial actors originate "real meaning?" the answer is no. The person who creates these actors and the acts they perform originates the meaning. But the actors can pass real meaning on to the audience taking in their performance. Any ad you see on television provides you with real meaning although the characters saying the words may just be cartoons. The ad tells you, basically, why you should buy a product and where you are likely to find it. That is real information and the symbols used convey real meaning. Not deep, by any means, but real. In this case, the actors themselves are symbols (think Smoky the Bear or Tony the Tiger) and represent part of the meaning conveyed. It is difficult for nonhuman actors to originate real meaning because every move they make is scripted and controlled by humans. Therefore it is the humans who create the meaning. A human actor can add meaning to a script by interpreting the words and using them in conjunction with unscripted body language, facial expression, and intonation to add meaning that was not intended by the writer of the script. The actions of an artificial actor are scripted as much as the words it says. Therefore, any meaning conveyed comes from the humans who did the scripting, not from the actor itself. This also happens when a director is overly manipulative in directing the actions of a human actor. I'm reminded of a story in which an actor was frustrated by such a director and told him, "God dammit, give me my balls back!" Instead of answering, the director looked over at his assistant and yelled, "Props!" When artificial actors become capable of making their own decisions about what symbols to use based on their own interpretation of how those symbols should be manipulated to accomplish the objective of adding meaning and passing that meaning on to the audience, they too will be creating meaning. Humans, by the way, have the right to denigrate anything they feel like denigrating. That merely reveals more about the human than what they are talking about. Cheers, Grant

		Re: Chapter 6: Locked in His Chinese Room posted on 08/29/2002 4:15 PM by azb@llnl.gov	[Top] [Mind·X] [Reply to this post]
	Grant, > "When artificial actors become capable of making their own decisions about what symbols to use based on their own interpretation of how those symbols should be manipulated to accomplish the objective of adding meaning and passing that meaning on to the audience, they too will be creating meaning." Indeed. That is also my view. Perhaps I was not clear when I used the term "artificial actor". I mean "something we consciously create" that serves to interact "as a being". The issue of symbol manipulation is harder to see when, for instance, you might convey an idea to me (in person), and I react not by speaking, but by shifting my weight, furrowing my brow, etc. These are not distinct "symbols" and may bleed into one another, yet some sense of "meaning" is still conveyed. Speaking to "robo-culture", I try to imagine a world where the original "intelligent species" had perished, but only aftyer having created AI-robot-like entities whose (initial) tasking might be simply to "gain knowledge and produce order" (pick something better if you like). Initially embedded as a literal "directive", over many robo-generations (robots designing better successors) the actual directive may no longer "exist as code", but rather become effectively present because of the way their "society" has become organized. The initial directive helped to provide the constraints which led to certain organizational structures over others, but now, it is those very forms of organization that "embody" the directive. If we were to happen upon this world, we might see variety of behaviors that appear meaningful, and even exhibit cultural differentiation due to local circumstance. It is no longer "obvious", nor perhaps entirely ascertainable what the "program" is intended to be doing. Even the originating "creators" might not recognize this system of "beings" as derived from their original instructions. Thus, hard to say wherein "meaning" arises. Cheers! ____tony b____

		Re: Chapter 6: Locked in His Chinese Room posted on 08/29/2002 6:19 PM by grantc4@hotmail.com	[Top] [Mind·X] [Reply to this post]
	Tony, Meaning is something the mind manufactures out of the input from the body's senses. A sunset is beautiful because a viewer's mind makes it so. When a person tries to convey what his mind has manufactured, he uses symbols to do it. What gets transferred will be a mixture of the first mind's creation and what the receiver's mind creates from the new input of data from the first mind. Only a portion of the meaning projected from the first mind will make it to the second mind as it will be modified by the sights and sounds that accompany it. For example, when I say something to someone, my thoughts are conveyed through a montage of facial expressions, body language, words, shaping of the sounds that convey the words, and the listener's past experience with the person who is saying them as well as his/her experience with the words being used in the communication. In addition, you have to take into account the setting in which the words are said as well as such things as the emotions being generated by the setting and the people involved in the transaction. Cyrano said, "There are a thousand ways to say 'I love you.'" A man who is crazy drunk and saying it to a frightened wife while holding her throat in one hand and a pistol to her head with the other will convey a much different meaning than the man who says it while giving her roses and a gentle kiss on the lips. Meaning, therefore, like beauty, is more in the eye of the beholder than in the words of the speaker. Cheers, Grant

		Re: Chapter 6: Locked in His Chinese Room posted on 02/08/2003 9:52 PM by Ted	[Top] [Mind·X] [Reply to this post]
	Is it really good to make so many words in the text of these pages links? Is there some automatic program doing this? It is irritating. Fancy making the word "chess" or "computers" a link on a page devoted to chess and computers! The absurdity would be alleviated only marginally if there were quick loading links - but not even this.

		Re: Chapter 6: Locked in His Chinese Room posted on 02/09/2003 1:15 AM by zoe	[Top] [Mind·X] [Reply to this post]
	my browser doesnt show them but im sure they could be or are distracting i say vote on sites, vote on the internet. how sites should be, the colors, the chosen words, the animations, what options there should be. one can imagine this being intrusive towards webmasters, but who cares and i really mean -who- cares, not even the webmasters themselves if they too can determine the shape of the (rest of) the internet which can then positively influence the world > I am writing in the hopes that someone would give me a straight answer to a straight question: Is it possible or not that we will soon have adequate CAT spoken translation between natural languages? i would say its almost a 'straight question' > I doubt that Searle argued that machines can only maipulate sysbols, but only that symbol manipulation alone would never produce understanding. i think what Searle really is saying is that he doesnt understand understanding. who does -- now what may be annoying is that too flawed logic isnt boycotted enough > Who says anything about donating? I know you would donate. I am donating it all the time to some distributed computing effort. Don't know and don't care what they are really doing. then you trust them enough. but nobody really does one more note on internet layouts and writings: simply mentioning any word like 'die' is offensive. and any letter, the shape of it. and anagrams and anything you can imagine. so to keep things simple and correct, i would say keep it at a level that doesnt avoid too many things. am i preaching? you bet your ass i am. but im not saying anything we already dont know P E A C E

		Re: Chapter 6: Locked in His Chinese Room posted on 02/10/2003 2:49 PM by Matt Bridges	[Top] [Mind·X] [Reply to this post]
	You can see a version of the article without the links if you look at the "printable version" of the article. At the top of every article page is a link to the "printable version," which does not have those hyperlinks. -Matt

		Re: Chapter 6: Locked in His Chinese Room posted on 02/11/2003 11:04 AM by zoezoe	[Top] [Mind·X] [Reply to this post]
	but at first it comes else. like with the agent NGreader. the lay-out and colors are offensive, 'subtle', and you can change them but they still come as they come also the way the menu's are put together: hopeless.

		Re: Chapter 6: Locked in His Chinese Room posted on 02/14/2003 8:07 PM by jennifergrizzle	[Top] [Mind·X] [Reply to this post]
	I dont use chineese laundrys much. A mate of mine used to ski with john searle. the chineese room thing isn't understood, nor will it go out of fashion because it revolves around the idea that we do or dont have cognition on a pseudo-spiritual medium. godel prooves we can never model ourselves, there would always be an incompleteness. The question of defining everything we are is utterly impossible.

		Re: Chapter 6: Locked in His Chinese Room posted on 09/15/2003 11:04 PM by mikew12345	[Top] [Mind·X] [Reply to this post]
	re: Chinese Room One: A Person and a Computer in a Room 1. Searle builds the case saying the computer is receiving and responding with language symbols, but he builds his case as if they were actually math symbols. With math, a given set of inputs (operators and values) can always produce a valid output. His case breaks down with language, where as Kurzweil describes, complete language understanding requires at least human level intelligence. 2. Let's not throw away the human in the room. In his current role, he is merely feeding data into the computer and taking it back out. However, think of a real human in that role, one with curiosity and a desire to learn. No doubt, over time he will begin to see patterns in the data that he passes back and forth. Given the way Chinese characters are designed this is almost a certainty: the symbol for "forest" is the same as 3 symbols for "tree", and the symbol for "tree" does vaguely resemble an actual tree, etc. However, even if these patterns did not exist, the repeated use of certain symbols would eventually suggest meanings, and given enough repetitions, the human could be expected to learn the language, and eventually to understand the questions and responses. Who is to say that a second computer, replacing the human, could not be programmed to perform the same search for patterns and to learn the language? Considering the computer's superior memory, it might be expected to learn it faster than the human.

		Re: Chapter 6: Locked in His Chinese Room posted on 11/15/2004 1:39 AM by titan_	[Top] [Mind·X] [Reply to this post]
	Your suggestion of teaching a computer to look for symbols in the Chinese Room is interesting in this context. But remember that the CRA argument is supposed to apply to any algorithm, including pattern recognition. So as I see it, you'd have to consider a room *within* a room if a computer is searching for language patterns, to be fair to this analogy. We return to the question of whether mechanical pattern recognition can actually become understanding. Seems like you've made it a RECURSIVE question. I think the real problem with the CRA is that Searle assumes that a computer can be no more sophisticated than the person following rules in the example. This assumption is used in the conclusion: that Strong AI cannot exist, i.e. machines can never think/understand. In Kurzweil's words, the "man" in the room doesnĺt understand anything because, after all, "he is just a computer," thereby illuminating Searleĺs own bias. Searle then concludesŚno surpriseŚthat the computer doesnĺt understand.

		Re: Chapter 6: Locked in His Chinese Room posted on 11/15/2004 2:26 AM by sushi101	[Top] [Mind·X] [Reply to this post]
	Ofcourse the man in the room doesn't understand chineese, neither does the individual braincells in my brain. The correct analogy as noted is of course that the ROOM is the computer/brain. Searle is everything that is wrong with anglo/american analytical philosophical thinking.

		Re: Chapter 6: Locked in His Chinese Room posted on 11/15/2004 2:27 AM by sushi101	[Top] [Mind·X] [Reply to this post]
	braincells = neurons

		Re: Chapter 6: Locked in His Chinese Room posted on 09/23/2007 2:28 AM by zenheadache	[Top] [Mind·X] [Reply to this post]
	[Ray Kurzweil] insists that they [the machines] will claim to be conscious . . . and consequently their claims will be largely accepted. People will eventually just come to accept without question that machines are conscious. But this misses the point. I can already program my computer so that it says that it is consciousŚi.e., it prints out ôI am consciousöŚand a good programmer can even program it so that it will carry on a rudimentary argument to the effect that it is conscious. But that has nothing to do with whether or not it really is conscious. Searle fails to point out that I make exactly the same point, and further that I refer not to such idle claims that are easily feasible today but rather to the convincing claims of future machines. As one example of many, I write in my book (p. 60) that these claims ôwonĺt seem like a programmed response. The machines will be earnest and convincing. Well it appears to me that Kurzweil is missing Searle's point, which is: whether AI is really conscious, or just seems that way, are two different issues. I have no doubt that as Kurzweil suggests "The machines will be earnest and convincing." But again, so what? If your wife convinces you that her adultery is merely in your imagination, does that mean she is not cheating on you? A trompe l'oeil painting appears quite convincing, until you try to walk through it. So AI may be the best illusion yet achieved, making us think something that is completely false because we are "convinced." The issue that applies to the "idle claims" Kurzweil objects to applies to the "convincing claims" as well, and is not answered by Kurzweil as far as I can tell. There are no shortage of credulous people convinced of many strange things. That doesn't make the object of their powerful beliefs real. That is the point I think Searle was making, and which I think Kurzweil was missing.