Chinese Room Argument

The Chinese Room argument, devised by John Searle, is an argument against the possibility of true artificial intelligence. The argument centers on a thought experiment in which someone who knows only English sits alone in a room following English instructions for manipulating strings of Chinese characters, such that to those outside the room it appears as if someone in the room understands Chinese. The argument is intended to show that while suitably programmed computers may appear to converse in natural language, they are not capable of understanding language, even in principle. Searle argues that the thought experiment underscores the fact that computers merely use syntactic rules to manipulate symbol strings, but have no understanding of meaning or semantics. Searle's argument is a direct challenge to proponents of Artificial Intelligence, and the argument also has broad implications for functionalist and computational theories of meaning and of mind. As a result, there have been many critical replies to the argument.

. . .

4.2 The Robot Reply

The Robot Reply concedes Searle is right about the Chinese Room scenario: it shows that a computer trapped in a computer room cannot understand language, or know what words mean. The Robot reply is responsive to the problem of knowing the meaning of the Chinese word for hamburger — Searle's example of something the room operator would not know. It seems reasonable to hold that we know what a hamburger is because we have seen one, and perhaps even made one, or tasted one, or at least heard people talk about hamburgers and understood what they are by relating them to things we do know by seeing, making, and tasting. Given this is how one might come to know what hamburgers are, the Robot Reply suggests that we put a digital computer in a robot body, with sensors, such as video cameras and microphones, and add effectors, such as wheels to move around with, and arms with which to manipulate things in the world. Such a robot — a computer with a body — could do what a child does, learn by seeing and doing. The Robot Reply holds that such a digital computer in a robot body, freed from the room, could attach meanings to symbols and actually understand natural language. Margaret Boden, Tim Crane, Daniel Dennett, Jerry Fodor, Stevan Harnad, Hans Moravec and Georges Rey are among those who have endorsed versions of this reply at one time or another.

Searle does not think this reply to the Chinese Room argument is any stronger than the Systems Reply. All the sensors do is provide additional input to the computer — and it will be just syntactic input. We can see this by making a parallel change to the Chinese Room scenario. Suppose the man in the Chinese Room receives, in addition to the Chinese characters slipped under the door, a stream of numerals that appear, say, on a ticker tape in a corner of the room. The instruction books are augmented to use the numbers from the tape as input, along with the Chinese characters. Unbeknownst to the man in the room, the numbers in the tape are the digitized output of a video camera. Searle argues that additional syntactic inputs will do nothing to allow the man to associate meanings with the Chinese characters. It is just more work for the man in the room.

Jerry Fodor, with Hilary Putnam and David Lewis, was a principle architect of the computational theory of mind that Searle's wider argument attacks. In his original 1980 reply to Searle, Fodor allows Searle is certainly right that “instantiating the same program as the brain does is not, in and of itself, sufficient for having those propositional attitudes characteristic of the organism that has the brain.” But Fodor holds that Searle is wrong about the robot reply. A computer might have propositional attitudes if it has the right causal connections to the world — but those are not ones mediated by a man sitting in the head of the robot. We don't know what the right causal connections are. Searle commits the fallacy of inferring from “the little man is not the right causal connection” to conclude that no causal linkage would succeed. There is considerable empirical evidence that mental processes involve “manipulation of symbols”; Searle give us no alternative explanation (this is sometimes called Fodor's “Only Game in Town” argument for computational approaches). Since this time, Fodor has written extensively on what the connections must be between a brain state and the world for the state to have intentional (representational) properties.

In a later piece, “Yin and Yang in the Chinese Room” (in Rosenthal 1991 pp.524-525), Fodor substantially revises his 1980 view. He distances himself from his earlier version of the robot reply, and holds instead that “instantiation” should be defined in such a way that the symbol must be the proximate cause of the effect — no intervening guys in a room. So Searle in the room is not an instantiation of a Turing Machine, and “Searle's setup does not instantiate the machine that the brain instantiates.” He concludes: “…Searle's setup is irrelevant to the claim that strong equivalence to a Chinese speaker's brain is ipso facto sufficient for speaking Chinese.” Searle says of Fodor's move, “Of all the zillions of criticisms of the Chinese Room argument, Fodor's is perhaps the most desperate. He claims that precisely because the man in the Chinese room sets out to implement the steps in the computer program, he is not implementing the steps in the computer program. He offers no argument for this extraordinary claim.” (in Rosenthal 1991, p. 525)

In a 1986 paper, Georges Rey advocated a combination of the system and robot reply, after noting that the original Turing Test is insufficient as a test of intelligence and understanding, and that the isolated system Searle describes in the room is certainly not functionally equivalent to a real Chinese speaker sensing and acting in the world. In a 2002 second look, “Searle's Misunderstandings of Functionalism and Strong AI”, Rey again defends functionalism against Searle, and in the particular form Rey calls the “computational-representational theory of thought — CRTT”. CRTT is not committed to attributing thought to just any system that passes the Turing Test (like the Chinese Room). Nor is it committed to a conversation manual model of understanding natural language. Rather, CRTT is concerned with intentionality, natural and artificial (the representations in the system are semantically evaluable — they are true or false, hence have aboutness). Searle saddles functionalism with the “blackbox” character of behaviorism, but functionalism cares how things are done. Rey sketches “a modest mind” — a CRTT system that has perception, can make deductive and inductive inferences, makes decisions on basis of goals and representations of how the world is, and can process natural language by converting to and from its native representations. To explain the behavior of such a system we would need to use the same attributions needed to explain the behavior of a normal Chinese speaker.

Tim Crane discusses the Chinese Room argument in his 1991 book, The Mechanical Mind. He cites the Churchlands' luminous room analogy, but then goes on to argue that in the course of operating the room, Searle would learn the meaning of the Chinese: “…if Searle had not just memorized the rules and the data, but also started acting in the world of Chinese people, then it is plausible that he would before too long come to realize what these symbols mean.”(127). (It is not clear if Crane realizes that any such realizing would arguably not be by the symbol manipulating system, but by the mind of the implementer.) Crane appears to end with a version of the Robot Reply: “Searle's argument itself begs the question by (in effect) just denying the central thesis of AI — that thinking is formal symbol manipulation. But Searle's assumption, none the less, seems to me correct ... the proper response to Searle's argument is: sure, Searle-in-the-room, or the room alone, cannot understand Chinese. But if you let the outside world have some impact on the room, meaning or ‘semantics' might begin to get a foothold. But of course, this concedes that thinking cannot be simply symbol manipulation.” (129)

Margaret Boden 1988 also argues that Searle mistakenly supposes programs are pure syntax. But programs bring about the activity of certain machines: “The inherent procedural consequences of any computer program give it a toehold in semantics, where the semantics in question is not denotational, but causal.” (250) Thus a robot might have causal powers that enable it to refer to a restaurant.

Steven Harnad also finds important our sensory and motor capabilities: “Who is to say that the Turing Test, whether conducted in Chinese or in any other language, could be successfully passed without operations that draw on our sensory, motor, and other higher cognitive capacities as well? Where does the capacity to comprehend Chinese begin and the rest of our mental competence leave off?” Harnad believes that symbolic functions must be grounded in “robotic” functions that connect a system with the world. And he thinks this counts against symbolic accounts of mentality, such as Jerry Fodor's, and, one suspects, the approach of Roger Schank that was Searle's original target.

. . .

A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z

Stanford Encyclopedia of Philosophy