Chinese room

Chinese room
If you can carry on an intelligent conversation using pieces of paper slid under a door, does this imply that someone or something on the other side understands what you are saying?

The Chinese room is a thought experiment by John Searle which first appeared in his paper "Minds, Brains, and Programs", published in Behavioral and Brain Sciences in 1980.[1] It addresses the question: if a machine can convincingly simulate an intelligent conversation, does it necessarily understand? In the experiment Searle imagines himself in a room, acting as a computer by manually executing a program that convincingly simulates the behavior of a native Chinese speaker. People outside the room slide Chinese characters under the door and Searle, to whom "Chinese writing is just so many meaningless squiggles",[1] is able to create sensible replies, in Chinese, by following the instructions of the program; that is, by moving papers around. The question arises whether Searle can be said to understand Chinese in the same way that, as Searle says:

according to strong AI, . . . the appropriately programmed computer really is a mind, in the sense that computers given the right programs can be literally said to understand and have other cognitive states.[1]

The experiment is the centerpiece of Searle's Chinese Room Argument which holds that a program cannot give a computer a "mind" or "understanding", regardless of how intelligently it may make it behave.[1] He concludes that "programs are neither constitutive of nor sufficient for minds."[2] "I can have any formal program you like, but I still understand nothing."[1]

The Chinese room is an argument against certain claims of leading thinkers in the field of artificial intelligence,[3] and is not concerned with the level of intelligence that an AI program can display.[4] Searle's argument is directed against functionalism and computationalism (philosophical positions inspired by AI), rather than the goals of applied AI research itself.[5] The argument leaves aside the question of creating an artificial mind by methods other than symbol manipulation.[6]

Controversial, and the subject of an entire literature of counterargument,[7] it became Behavioral and Brain Sciences's "most influential target article",[8] generating an enormous number of commentaries and responses in the ensuing decades.


Chinese room thought experiment

Searle's thought experiment begins with this hypothetical premise: suppose that artificial intelligence research has succeeded in constructing a computer that behaves as if it understands Chinese. It takes Chinese characters as input and, by following the instructions of a computer program, produces other Chinese characters, which it presents as output. Suppose, says Searle, that this computer performs its task so convincingly that it comfortably passes the Turing test: it convinces a human Chinese speaker that the program is itself a live Chinese speaker. To all of the questions that the person asks, it makes appropriate responses, such that any Chinese speaker would be convinced that he or she is talking to another Chinese-speaking human being.

The question Searle wants to answer is this: does the machine literally "understand" Chinese? Or is it merely simulating the ability to understand Chinese?[9] Searle calls the first position "strong AI" (see below) and the latter "weak AI".[10]

Searle then supposes that he is in a closed room and has a book with an English version of the computer program, along with sufficient paper, pencils, erasers, and filing cabinets. Searle could receive Chinese characters through a slot in the door, process them according to the program's instructions, and produce Chinese characters as output. As the computer had passed the Turing test this way, it is fair, says Searle, to deduce that he would be able to do so as well, simply by running the program manually.

Searle asserts that there is no essential difference between the role the computer plays in the first case and the role he plays in the latter. Each is simply following a program, step-by-step, which simulates intelligent behavior. And yet, Searle points out, "I don't speak a word of Chinese."[11] Since he does not understand Chinese, Searle argues, we must infer that the computer does not understand Chinese either.

Searle argues that without "understanding" (what philosophers call "intentionality"), we cannot describe what the machine is doing as "thinking". Because it does not think, it does not have a "mind" in anything like the normal sense of the word, according to Searle. Therefore, he concludes, "strong AI" is mistaken.


Searle's argument first appeared in his paper "Minds, Brains, and Programs", published in Behavioral and Brain Sciences in 1980.[1] It eventually became the journal's "most influential target article",[8] generating an enormous number of commentaries and responses in the ensuing decades.

Most of the discussion consists of attempts to refute it. "The overwhelming majority," notes BBS editor Stevan Harnad,[12] "still think that the Chinese Room Argument is dead wrong."[13] The sheer volume of the literature that has grown up around it inspired Pat Hayes to quip that the field of cognitive science ought to be redefined as "the ongoing research program of showing Searle's Chinese Room Argument to be false."[8]

The paper has become "something of a classic in cognitive science," according to Harnad.[13] Varol Akman agrees, and has described Searle's paper as "an exemplar of philosophical clarity and purity".[14]

Searle's targets: "strong AI" and computationalism

Although the Chinese Room argument was originally presented in reaction to the statements of AI researchers, philosophers have come to view it as an important part of the philosophy of mind. It is a challenge to functionalism and the computational theory of mind,[15] and is related to such questions as the mind-body problem,[16] the problem of other minds,[17] the symbol-grounding problem, and the hard problem of consciousness.[18]

Strong AI

Searle identified a philosophical position he calls "strong AI":

The appropriately programmed computer with the right inputs and outputs would thereby have a mind in exactly the same sense human beings have minds.[19]

The definition hinges on the distinction between simulating a mind and actually having a mind. Searle writes that "according to Strong AI, the correct simulation really is a mind. According to Weak AI, the correct simulation is a model of the mind."[20]

The position is implicit in some of the statements of early AI researchers and analysts. For example, in 1955, AI founder Herbert Simon declared that "there are now in the world machines that think, that learn and create"[21] and claimed that they had "solved the venerable mind-body problem, explaining how a system composed of matter can have the properties of mind."[22] John Haugeland wrote that "AI wants only the genuine article: machines with minds, in the full and literal sense. This is not science fiction, but real science, based on a theoretical conception as deep as it is daring: namely, we are, at root, computers ourselves."[23]

Searle also ascribes the following positions to advocates of strong AI:

  • AI systems can be used to explain the mind;[9]
  • The study of the brain is irrelevant to the study of the mind;[24] and
  • The Turing test is adequate for establishing the existence of mental states.[25]

Strong AI as computationalism or functionalism

In more recent presentations of the Chinese room argument, Searle has identified "strong AI" as "computer functionalism" (a term he attributes to Daniel Dennett).[26][27] Functionalism is a position in modern philosophy of mind that holds that we can define mental phenomena (such as beliefs, desires, and perceptions) by describing their functions in relation to each other and to the outside world. Because a computer program can accurately represent functional relationships as relationships between symbols, a computer can have mental phenomena if it runs the right program, according to functionalism.

Stevan Harnad argues that Searle's depictions of strong AI can be reformulated as "recognizable tenets of computationalism, a position (unlike 'strong AI') that is actually held by many thinkers, and hence one worth refuting."[28] Computationalism[29] is the position in the philosophy of mind which argues that the mind can be accurately described as an information-processing system.

Each of the following, according to Harnad, is a "tenet" of computationalism:[30]

  • Mental states are computational states (which is why computers can have mental states and help to explain the mind);
  • Computational states are implementation-independent — in other words, it is the software that determines the computational state, not the hardware (which is why the brain, being hardware, is irrelevant); and that
  • Since implementation is unimportant, the only empirical data that matters is how the system functions; hence the Turing test is definitive.

Computers vs. machines vs. brains

The Chinese room has exactly the same design as any modern computer. It has a Von Neumann architecture, which consists of a program (the book of instructions), some memory (the papers and file cabinets), a CPU which follows the instructions (the man), and a means to write symbols in memory (the pencil and eraser). A machine with this design is known in theoretical computer science as "Turing complete", because it has the necessary machinery to carry out any computation that a Turing machine can do, and therefore it is capable of doing a step-by-step simulation of any other digital machine. Alan Turing writes, "all digital computers are in a sense equivalent."[31] In other words, the Chinese room can do whatever any other computer can do (albeit much, much more slowly). The widely accepted Church-Turing thesis holds that any function computable by an effective procedure is computable by a Turing machine.

The Chinese room (and all modern computers) manipulates physical objects in order to carry out calculations and do simulations. AI researchers Allen Newell and Herbert Simon called this kind of machine a physical symbol system. It is also equivalent to the formal systems used in the field of mathematical logic. Searle emphasizes the fact that this kind of symbol manipulation is syntactic (borrowing a term from the study of grammar). The CPU manipulates the symbols using a form of syntax rules, without any knowledge of the symbol's semantics (that is, their meaning).

Searle's argument applies specifically to computers (that is, devices that can only manipulate symbols without knowing what they mean) and not to machines in general. Searle does not disagree that machines can have consciousness and understanding, because, as he writes, "we are precisely such machines".[32] Searle holds that the brain is, in fact, a machine, but the brain gives rise to consciousness and understanding using machinery that is non-computational. Searle writes "brains cause minds"[32] and that "actual human mental phenomena [are] dependent on actual physical-chemical properties of actual human brains",[33] a position called "biological naturalism" (as opposed to alternatives like dualism, behaviorism, functionalism or identity theory).[34] Indeed, Searle accuses "strong AI" of dualism, the idea that the brain and mind are made of different "substances". He writes that "strong AI only makes sense given the dualistic assumption that, where the mind is concerned, the brain doesn't matter."[35]

Intentionality vs. consciousness

Searle's original argument centered on 'understanding' — that is, mental states with what philosophers call 'intentionality' — and did not directly address other closely related ideas such as 'consciousness'. David Chalmers argued that "it is fairly clear that consciousness is at the root of the matter".[36] In more recent presentations of the Chinese Room, Searle has included 'consciousness' as part of the argument as well.[37]

Strong AI vs. AI research

Searle's argument does not limit the intelligence with which machines can behave or act; indeed, it does not address this issue directly. "The Chinese room argument ... assumes complete success on the part of artificial intelligence in simulating human cognition," Searle writes.[38] This leaves open the possibility that a machine could be built that acts more intelligent than a person, but does not have a mind or intentionality in the same way that brains do.

Since the primary mission of artificial intelligence research is only to create useful systems that act intelligently, Searle's arguments are not usually considered an issue for AI research. Stuart Russell and Peter Norvig observe that most AI researchers "don't care about the strong AI hypothesis—as long as the program works, they don't care whether you call it a simulation of intelligence or real intelligence."[39]

Searle's "strong AI" should not be confused with "strong AI" as defined by Ray Kurzweil and other futurists,[40] who use the term to describe machine intelligence that rivals or exceeds human intelligence. Kurzweil is concerned primarily with the amount of intelligence displayed by the machine, whereas Searle's argument sets no limit on this, as long as it is understood that it is a simulation and not the real thing.


Replies to Searle's argument may be classified according to what they claim to show:[41]

  • Those which identify who speaks Chinese;
  • Those which demonstrate how meaningless symbols can become meaningful;
  • Those which suggest that the Chinese room should be redesigned in some way;
  • Those which contend that Searle's argument is misleading; and
  • Those which argue that the argument makes false assumptions about subjective conscious experience and therefore proves nothing.

Some of the arguments (robot and brain simulation, for example) fall into multiple categories.

System and virtual mind replies: finding the mind

These replies attempt to answer the question: since the man in the room doesn't speak Chinese, where is the "mind" that does? These replies address the key ontological issues of mind vs. body and simulation vs. reality. All of the replies that identify the mind in the room are versions of "the system reply".

System reply[42]
The basic "system reply" argues that it is the "whole system" which understands Chinese. While the man understands only English, when he is combined with the program, scratch paper, pencils and file cabinets, they form a system that can understand Chinese. "Here, understanding is not being ascribed to the mere individual; rather it is being ascribed to this whole system of which he is a part" Searle explains.[43] The fact that man does not understand Chinese is irrelevant, because it is only the system as a whole which matters.
Searle notes that (in this simple version of the systems reply) there is nothing more than a list of physical objects; it grants the power of understanding and consciousness to "the conjunction of that person and bits of paper".[43] Searle responds by simplifying the list of physical objects: he asks what happens if the man memorizes the rules and keeps track of everything in his head? Then the whole system consists of just one object: the man himself. Searle argues that if the man doesn't understand Chinese then the system doesn't understand Chinese either and the fact that the man appears to understand Chinese proves nothing.[43] Critics of Searle's response argue that the program has allowed the man to have two minds in one head.[who?]

More sophisticated versions of the system reply try to identify more precisely what "the system" is and they differ in exactly how they describe it. According to these replies,[who?] the "mind that speaks Chinese" could be such things as: the "software", a "program", a "running program", a simulation of the "neural correlates of consciousness", the "functional system", a "simulated mind", an "emergent property", or "a virtual mind" (Marvin Minsky's version of the system reply, described below).

Virtual mind reply[44]
The term "virtual" is used in computer science to describe an object which appears to exist "in" a computer (or computer network) only because software is making it appear to exist. The objects "inside" computers (including files, folders, and so on) are all "virtual", except for the computer's electronic components. Similarly, Minsky argues, a computer may contain a "mind" that is virtual in the same sense as virtual machines, virtual communities and virtual reality.
To clarify the distinction between the simple systems reply given above and virtual mind reply, David Cole notes that two simulations could be running on one system at the same time; one speaking Chinese and one speaking Korean. While there is only one system, there can be multiple "virtual minds."[45]
Searle responds that such a mind is, at best, a simulation, and writes: "No one supposes that computer simulations of a five-alarm fire will burn the neighborhood down or that a computer simulation of a rainstorm will leave us all drenched."[46] Nicholas Fearn responds that, for some things, simulation is as good as the real thing. "When we call up the pocket calculator function on a desktop computer, the image of a pocket calculator appears on the screen. We don't complain that 'it isn't really a calculator', because the physical attributes of the device do not matter."[47] The question is, is the human mind like the pocket calculator, essentially composed of information? Or is the mind like the rainstorm, something other than a computer, and not realizable in full by a computer simulation? (The issue of simulation is also discussed in the article synthetic intelligence.)

These replies provide an explanation of exactly who it is that understands Chinese. If there is something besides the man in the room that can understand Chinese, Searle can't argue that (1) the man doesn't understand Chinese, therefore (2) nothing in the room understands Chinese. This, according to those who make this reply, shows that Searle's argument fails to prove that "strong AI" is false.[48]

However, the replies, by themselves, do not prove that strong AI is true, either: they provide no evidence that the system (or the virtual mind) understands Chinese, other than the hypothetical premise that it passes the Turing Test. As Searle writes "the systems reply simply begs the question by insisting that system must understand Chinese."[43]

Robot and semantics replies: finding the meaning

As far as the person in the room is concerned, the symbols are just meaningless "squiggles." But if the Chinese room really "understands" what it's saying, then the symbols must get their meaning from somewhere. These arguments attempt to connect the symbols to the things they symbolize. These replies address Searle's concerns about intentionality, symbol grounding and syntax vs. semantics.

Robot reply[49]
Suppose that instead of a room, the program was placed into a robot that could wander around and interact with its environment. This would allow a "causal connection" between the symbols and things they represent. Hans Moravec comments: 'If we could graft a robot to a reasoning program, we wouldn't need a person to provide the meaning anymore: it would come from the physical world."[50]
Searle’s reply is to suppose that, unbeknownst to the individual in the Chinese room, some of the inputs came directly from a camera mounted on a robot, and some of the outputs were used to manipulate the arms and legs of the robot. Nevertheless, the person in the room is still just following the rules, and does not know what the symbols mean. Searle writes "he doesn't see what comes into the robot's eyes."[51] (See Mary's room for a similar thought experiment.)
Derived meaning[52]
Some respond that the room, as Searle describes it, is connected to the world: through the Chinese speakers that it is "talking" to and through the programmers who designed the knowledge base in his file cabinet. The symbols Searle manipulates are already meaningful, they're just not meaningful to him.
Searle says that the symbols only have a "derived" meaning, like the meaning of words in books. The meaning of the symbols depends on the conscious understanding of the Chinese speakers and the programmers outside the room. The room, according to Searle, has no understanding of its own.[53]
Commonsense knowledge / contextualist reply[54]
Some have argued that the meanings of the symbols would come from a vast "background" of commonsense knowledge encoded in the program and the filing cabinets. This would provide a "context" that would give the symbols their meaning.
Searle agrees that this background exists, but he does not agree that it can be built into programs. Hubert Dreyfus has also criticized the idea that the "background" can be represented symbolically.[55]

To each of these suggestions, Searle's response is the same: no matter how much knowledge is written into the program and no matter how the program is connected to the world, he is still in the room manipulating symbols according to rules. His actions are syntactic and this can never explain to him what the symbols stand for. Searle writes "syntax is insufficient for semantics."[56]

However, for those who accept that Searle's actions simulate a mind, separate from his own, the important question is not what the symbols mean to Searle, what is important is what they mean to the virtual mind. While Searle is trapped in the room, the virtual mind is not: it is connected to the outside world through the Chinese speakers it speaks to, through the programmers who gave it world knowledge, and through the cameras and other sensors that roboticists can supply.

Brain simulation and connectionist replies: redesigning the room

These arguments are all versions of the systems reply that identify a particular kind of system as being important. They try to outline what kind of a system would be able to pass the Turing test and give rise to conscious awareness in a machine. (Note that the "robot" and "commonsense knowledge" replies above also specify a certain kind of system as being important.)

Brain simulator reply[57]
Suppose that the program simulated in fine detail the action of every neuron in the brain of a Chinese speaker. This strengthens the intuition that there would be no significant difference between the operation of the program and the operation of a live human brain.
Searle replies that such a simulation will not have reproduced the important features of the brain — its causal and intentional states. Searle is adamant that "human mental phenomena [are] dependent on actual physical-chemical properties of actual human brains."[35] Moreover, he argues:

"[I]magine that instead of a monolingual man in a room shuffling symbols we have the man operate an elaborate set of water pipes with valves connecting them. When the man receives the Chinese symbols, he looks up in the program, written in English, which valves he has to turn on and off. Each water connection corresponds to a synapse in the Chinese brain, and the whole system is rigged up so that after doing all the right firings, that is after turning on all the right faucets, the Chinese answers pop out at the output end of the series of pipes. Now where is the understanding in this system? It takes Chinese as input, it simulates the formal structure of the synapses of the Chinese brain, and it gives Chinese as output. But the man certainly doesn't understand Chinese, and neither do the water pipes, and if we are tempted to adopt what I think is the absurd view that somehow the conjunction of man and water pipes understands, remember that in principle the man can internalize the formal structure of the water pipes and do all the "neuron firings" in his imagination. " Searle (1980)

Two variations on the brain simulator reply are:
China brain[58]
What if we ask each citizen of China to simulate one neuron, using the telephone system to simulate the connections between axons and dendrites? In this version, it seems obvious that no individual would have any understanding of what the brain might be saying.
Brain replacement scenario[59]
In this, we are asked to imagine that engineers have invented a tiny computer that simulates the action of an individual neuron. What would happen if we replaced one neuron at a time? Replacing one would clearly do nothing to change conscious awareness. Replacing all of them would create a digital computer that simulates a brain. If Searle is right, then conscious awareness must disappear during the procedure (either gradually or all at once). Searle's critics argue that there would be no point during the procedure when he can claim that conscious awareness ends and mindless simulation begins.[60](See Ship of Theseus for a similar thought experiment.)
Connectionist replies[61]
Closely related to the brain simulator reply, this claims that a massively parallel connectionist architecture would be capable of understanding.
Combination reply[62]
This response combines the robot reply with the brain simulation reply, arguing that a brain simulation connected to the world through a robot body could have a mind.

Arguments such as these (and the robot and commonsense knowledge replies above) recommend that Searle's room be redesigned. Searle's replies all point out that, however the program is written or however it is connected to the world, it is still being simulated by a simple step by step Turing complete machine (or machines). These machines are still just like the man in the room: they understand nothing and don't speak Chinese. They are merely manipulating symbols without knowing what they mean.

Searle also argues that, if features like a robot body or a connectionist architecture are required, then strong AI (as he understands it) has been abandoned.[63] Either (1) Searle's room can't pass the Turing test, because formal symbol manipulation (by a Turing complete machine) is not enough, or (2) Searle's room could pass the Turing test, but the Turing test is not sufficient to determine if the room has a "mind." Either way, it denies one or the other of the positions Searle thinks of "strong AI", proving his argument.

The brain arguments also suggests that computation can't provide an explanation of the human mind (another aspect of what Searle thinks of as "strong AI"). They assume that there is no simpler way to describe the mind than to create a program that is just as mysterious as the brain was. He writes "I thought the whole idea of strong AI was that we don't need to know how the brain works to know how the mind works."[64]

Other critics don't argue that these improvements are necessary for the Chinese room to pass the Turing test or to have a mind. They accept the premise that the room as Searle describes it does, in fact, have a mind, but they argue that it is difficult to see—Searle's description is correct, but misleading. By redesigning the room more realistically they hope to make this more obvious. In this case, these arguments are being used as appeals to intuition (see next section). Searle's intuition, however, is never shaken. He writes: "I can have any formal program you like, but I still understand nothing."[11]

In fact, the room can just as easily be redesigned to weaken our intuitions. Ned Block's "blockhead" argument (Block 1981) suggests that the program could, in theory, be rewritten into a simple lookup table of rules of the form "if the user writes S, reply with P and goto X". At least in principle, any program can be rewritten (or "refactored") into this form, even a brain simulation.[65] In the blockhead scenario, the entire mental state is hidden in the letter X, which represents a memory address—a number associated with the next rule. It is hard to visualize that an instant of one's conscious experience can be captured in a single large number, yet this is exactly what "strong AI" claims. On the other hand, such a lookup table would be ridiculously large (probably to the point of being impossible in practice), and the states could therefore be extremely specific.

Speed and complexity: appeals to intuition

The following arguments (and the intuitive interpretations of the arguments above) do not directly explain how a Chinese speaking mind could exist in Searle's room, or how the symbols he manipulates could become meaningful. However, by raising doubts about Searle's intuitions they support other positions, such as the system and robot replies.

Some of the arguments above also function as appeals to intuition, especially those that are intended to make it seem more plausible that the Chinese room contains a mind, which can include the robot, commonsense knowledge, brain simulation and connectionist replies.

Several critics believe that Searle's argument relies entirely on intuitions. Ned Block writes "Searle's argument depends for its force on intuitions that certain entities do not think."[66] Daniel Dennett describes the Chinese room argument as a misleading "intuition pump"[67] and writes "Searle's thought experiment depends, illicitly, on your imagining too simple a case, an irrelevant case, and drawing the 'obvious' conclusion from it."[68]

Speed and complexity replies[69]
The speed at which our brains process information is (by some estimates) 100 billion operations per second.[70] Several critics point out that the man in the room would probably take millions of years to respond to a simple question, and would require "filing cabinets" of astronomical proportions. This brings the clarity of Searle's intuition into doubt.

An especially vivid version of the speed and complexity reply is from Paul and Patricia Churchland. They propose this analogous thought experiment:

Churchland's luminous room[71]
"Consider a dark room containing a man holding a bar magnet or charged object. If the man pumps the magnet up and down, then, according to Maxwell's theory of artificial luminance (AL), it will initiate a spreading circle of electromagnetic waves and will thus be luminous. But as all of us who have toyed with magnets or charged balls well know, their forces (or any other forces for that matter), even when set in motion produce no luminance at all. It is inconceivable that you might constitute real luminance just by moving forces around!"[72] The problem is that he would have to wave the magnet up and down something like 450 trillion times per second in order to see anything.

Several of the replies above address the issue of complexity. The connectionist reply emphasizes that a working artificial intelligence system would have to be as complex and as interconnected as the human brain. The commonsense knowledge reply emphasizes that any program that passed a Turing test would have to be "an extraordinarily supple, sophisticated, and multilayered system, brimming with 'world knowledge' and meta-knowledge and meta-meta-knowledge," as Daniel Dennett explains.[68]

These arguments, if accepted, prevent Searle from claiming that his conclusion is obvious by undermining the intuitions that his certainty requires.

Stevan Harnad is critical of speed and complexity replies when they stray beyond addressing our intuitions. He writes "Some have made a cult of speed and timing, holding that, when accelerated to the right speed, the computational may make a phase transition into the mental. It should be clear that is not a counterargument but merely an ad hoc speculation (as is the view that it is all just a matter of ratcheting up to the right degree of 'complexity.')"[73]

Other minds and zombies: meaninglessness

Several replies argue that Searle's argument is irrelevant because his assumptions about the mind and consciousness are faulty. Searle believes that human beings directly experience their consciousness, intentionality and the nature of the mind every day, and that this experience of consciousness is not open to question. He writes that we must "presuppose the reality and knowability of the mental."[74] These replies question whether Searle is justified in using his own experience of consciousness to determine that it is more than mechanical symbol processing. In particular, the other minds reply argues that we can't use our experience of consciousness to answer questions about other minds (even the mind of a computer), and the epiphenomena reply argues that Searle's consciousness does not "exist" in the sense that Searle thinks it does.

Other minds reply[75]
This reply points out that Searle's argument is a version of the problem of other minds, applied to machines. There is no way we can determine if other people's subjective experience is the same as our own. We can only study their behavior (i.e., by giving them our own Turing test). Critics of Searle argue that he is holding the Chinese room to a higher standard than we would hold an ordinary person.
Nils Nilsson writes "If a program behaves as if it were multiplying, most of us would say that it is, in fact, multiplying. For all I know, Searle may only be behaving as if he were thinking deeply about these matters. But, even though I disagree with him, his simulation is pretty good, so I’m willing to credit him with real thought."[76]
Alan Turing (writing 30 years before Searle presented his argument) noted that people never consider the problem of other minds when dealing with each other. He writes that "instead of arguing continually over this point it is usual to have the polite convention that everyone thinks."[77] The Turing test simply extends this "polite convention" to machines. He doesn't intend to solve the problem of other minds (for machines or people) and he doesn't think we need to.[78]

Searle disagrees with this analysis and argues that "the study of the mind starts with such facts as that humans have beliefs, while thermostats, telephones, and adding machines don't ... what we wanted to know is what distinguishes the mind from thermostats and livers."[51] He takes it as obvious that we can detect the presence of consciousness and dismisses these replies as being off the point.

Epiphenomenon / zombie reply
Several philosophers[who?] argue that consciousness, as Searle describes it, does not exist. This position is sometimes referred to as eliminative materialism: the view that consciousness is a property that can be reduced to a strictly mechanical description, and that our experience of consciousness is, as Daniel Dennett describes it, a "user illusion".[79]
Russell & Norvig (2003) argue that, if we accept Searle's description of intentionality, consciousness and the mind, we are forced to accept that consciousness is epiphenomenal: that it "casts no shadow", that is undetectable in the outside world. Searle believes that there are "causal properties" in our neurons that give rise to the mind. However, these causal properties can't be detected by anyone outside the mind, otherwise the Chinese Room couldn't pass the Turing test—the people outside would be able to tell there wasn't a Chinese speaker in the room by detecting their causal properties. Since they can't detect causal properties, they can't detect the existence of the mental. Therefore, Russell and Norvig argue, Searle is mistaken about the "knowability of the mental".

Daniel Dennett provides this extension to the "epiphenomena" argument.

Dennett's reply from natural selection[80]
Suppose that, by some mutation, a human being is born that does not have Searle's "causal properties" but nevertheless acts exactly like a human being. (This sort of animal is called a "zombie" in thought experiments in the philosophy of mind). This new animal would reproduce just as any other human and eventually there would be more of these zombies. Natural selection would favor the zombies, since their design is (we could suppose) a bit simpler. Eventually the humans would die out. So therefore, if Searle is right, it's most likely that human beings (as we see them today) are actually "zombies," who nevertheless insist they are conscious. This suggests it's unlikely that Searle's "causal properties" would have ever evolved in the first place. Nature has no incentive to create them.

Formal arguments

Searle has produced a more formal version of the argument of which the Chinese Room forms a part. He presented the first version in 1984. The version given below is from 1990.[81]

The part of the argument which should be controversial is A3 and it is this point which the Chinese room thought experiment is intended to prove.[82]

He begins with three axioms:

(A1) "Programs are formal (syntactic)."
A program uses syntax to manipulate symbols and pays no attention to the semantics of the symbols. It knows where to put the symbols and how to move them around, but it doesn't know what they stand for or what they mean. For the program, the symbols are just physical objects like any others.
(A2) "Minds have mental contents (semantics)."
Unlike the symbols used by a program, our thoughts have meaning: they represent things and we know what it is they represent.
(A3) "Syntax by itself is neither constitutive of nor sufficient for semantics."
This is what the Chinese room argument is intended to prove: the Chinese room has syntax (because there is a man in there moving symbols around). The Chinese room has no semantics (because, according to Searle, there is no one or nothing in the room that understands what the symbols mean). Therefore, having syntax is not enough to generate semantics.

Searle posits that these lead directly to this conclusion:

(C1) Programs are neither constitutive of nor sufficient for minds.
This should follow without controversy from the first three: Programs don't have semantics. Programs have only syntax, and syntax is insufficient for semantics. Every mind has semantics. Therefore programs are not minds.

This much of the argument is intended to show that artificial intelligence will never produce a machine with a mind by writing programs that manipulate symbols. The remainder of the argument addresses a different issue. Is the human brain running a program? In other words, is the computational theory of mind correct?[83] He begins with an axiom that is intended to express the basic modern scientific consensus about brains and minds:

(A4) Brains cause minds.

Searle claims that we can derive "immediately" and "trivially"[2] that:

(C2) Any other system capable of causing minds would have to have causal powers (at least) equivalent to those of brains.
Brains must have something that causes a mind to exist. Science has yet to determine exactly what it is, but it must exist, because minds exist. Searle calls it "causal powers". "Causal powers" is whatever the brain uses to create a mind. If anything else can cause a mind to exist, it must have "equivalent causal powers". "Equivalent causal powers" is whatever else that could be used to make a mind.

And from this he derives the further conclusions:

(C3) Any artifact that produced mental phenomena, any artificial brain, would have to be able to duplicate the specific causal powers of brains, and it could not do that just by running a formal program.
This follows from C1 and C2: Since no program can produce a mind, and "equivalent causal powers" produce minds, it follows that programs do not have "equivalent causal powers."
(C4) The way that human brains actually produce mental phenomena cannot be solely by virtue of running a computer program.
Since programs do not have "equivalent causal powers", "equivalent causal powers" produce minds, and brains produce minds, it follows that brains do not use programs to produce minds.


  1. ^ a b c d e f Searle 1980.
  2. ^ a b Searle 1990.
  3. ^ Larry Hauser writes that the Chinese room is "the most influential and widely cited argument against artificial intelligence". (Hauser 1997)
  4. ^ See Strong AI vs. AI research. Searle writes that the argument "assumes complete success on the part of artificial intelligence in simulating human cognition." (Searle 2004, p. 63).
  5. ^ See Strong AI as computationalism or functionalism. Searle's argument is directed against Strong AI, a philosophical position that he now identifies with functionalism. (Searle 1994, p. 44) (Searle 2004, p. 45)
  6. ^ See Computers vs. machines vs. brains.
  7. ^ Pat Hayes said that the field of cognitive science ought to be redefined as "the ongoing research program of showing Searle's Chinese Room Argument to be false."
  8. ^ a b c Harnad 2001, p. 1.
  9. ^ a b "Partisans of strong AI," Searle writes, "claim that in this question and answer sequence the machine is not only simulating a human ability but also (1) that the machine can literally be said to understand the story and provide the answers to questions, and (2) that what the machine and its program do explains the human ability to understand the story and answer questions about it." (Searle 1980, p. 2)
  10. ^ Searle writes that "according to Strong AI, the correct simulation really is a mind. According to Weak AI, the correct simulation is a model of the mind." (Searle 2008, p. 1)
  11. ^ a b Searle 1980, p. 3.
  12. ^ Harnad edited BBS during the years which saw the introduction and popularisation of the Chinese Room argument.
  13. ^ a b Harnad 2001, p. 2.
  14. ^ In Akman's review of Mind Design II
  15. ^ Harnad (2005) holds that the Searle's argument is against the thesis that "has since come to be called 'computationalism,' according to which cognition is just computation, hence mental states are just computational states". Cole (2004) agrees that "the argument also has broad implications for functionalist and computational theories of meaning and of mind".
  16. ^ See the "Systems reply" below.
  17. ^ See the "Other minds reply" below.
  18. ^ The relationship between Searle's argument and consciousness is detailed in Chalmers 1996
  19. ^ This version is from Searle (1999), and is also quoted in Dennett 1991, p. 435. Searle's original formulation was "The appropriately programmed computer really is a mind, in the sense that computers given the right programs can be literally said to understand and have other cognitive states." (Searle 1980, p. 1). Strong AI is defined similarly by Russell & Norvig (2003, p. 947): "The assertion that machines could possibly act intelligently (or, perhaps better, act as if they were intelligent) is called the 'weak AI' hypothesis by philosophers, and the assertion that machines that do so are actually thinking (as opposed to simulating thinking) is called the 'strong AI' hypothesis."
  20. ^ Searle 2008, p. 1.
  21. ^ Quoted in Russell & Norvig 2003, p. 21. Simon, together with Allen Newell and Cliff Shaw, had just completed the first "AI" program, the Logic Theorist.
  22. ^ Quoted in Crevier 1993, p. 46 and Russell & Norvig 2003, p. 17.
  23. ^ Haugeland 1986, p. 2. (Italics his)
  24. ^ Searle believes that "strong AI only makes sense given the dualistic assumption that, where the mind is concerned, the brain doesn't matter." (Searle 1980, p. 13) He writes elsewhere, "I thought the whole idea of strong AI was that we don't need to know how the brain works to know how the mind works." (Searle 1980, p. 8) This position owes its phrasing to Harnad (2001).
  25. ^ "One of the points at issue," writes Searle, "is the adequacy of the Turing test." (Searle 1980, p. 6)
  26. ^ Searle 1994, p. 44.
  27. ^ Searle 2004, p. 45.
  28. ^ Harnad 2001, p. 3 (Italics his)
  29. ^ Computationalism is associated with Jerry Fodor and Hilary Putnam. (Horst 2005, p. 1) Harnad (2001) also cites Allen Newell and Zenon Pylyshyn. Pinker (1997) also advocates a version of computationalism.
  30. ^ Harnad 2001, pp. 3–5.
  31. ^ Turing 1950, p. 442.
  32. ^ a b Searle 1980, p. 11.
  33. ^ Searle 1990, p. 29.
  34. ^ Hauser 2006, p. 8.
  35. ^ a b Searle 1980, p. 13.
  36. ^ Chalmers 1996, p. 322, quoted in Larry Hauser's annotated bibliography.
  37. ^ Searle 1992, p. 44.
  38. ^ Searle 2004, p. 63.
  39. ^ Russell & Norvig 2003, p. 947.
  40. ^ Kurzweil 2005, p. 260 or see Advanced Human Intelligence
  41. ^ Cole (2004, pp. 5–6) combines the second and third categories, as well as the fourth and fifth.
  42. ^ Searle 1980, pp. 5–6, Cole 2004, pp. 6–7, Hauser 2006, pp. 2–3, Russell & Norvig 2003, p. 959, Dennett 1991, p. 439, Hearn 2007, p. 44, Crevier 1993, p. 269. This position is held by (according to Cole (2004, p. 6)) Ned Block, Jack Copeland, Daniel Dennett, Jerry Fodor, John Haugeland, Ray Kurzweil, and Georges Rey, among others.
  43. ^ a b c d Searle 1980, p. 6.
  44. ^ Cole (2004, pp. 7–9) ascribes this position to Marvin Minsky, Tim Maudlin, David Chalmers and David Cole. According to Cole, the reply was introduced by Marvin Minsky. Minsky (1980).
  45. ^ Cole 2004, p. 8
  46. ^ Searle 1980, p. 12.
  47. ^ Hearn 2007, p. 47
  48. ^ Cole (2004, p. 21) writes "From the intuition that in the CR thought experiment he would not understand Chinese by running a program, Searle infers that there is no understanding created by running a program. Clearly, whether that inference is valid or not turns on a metaphysical question about the identity of persons and minds. If the person understanding is not identical with the room operator, then the inference is unsound."
  49. ^ Searle 1980, p. 7, Cole 2004, pp. 9–11, Hauser 2006, p. 3, Hearn 2007, p. 44. Cole (2004, p. 9) ascribes this position to Margaret Boden, Tim Crane, Daniel Dennett, Jerry Fodor, Stevan Harnad, Hans Moravec and Georges Rey
  50. ^ Quoted in Crevier 1993, p. 272. Cole (2004, p. 18) calls this the "externalist" account of meaning.
  51. ^ a b Searle 1980, p. 7.
  52. ^ Hauser 2006, p. 11, Cole 2004, p. 19. This argument is supported by Daniel Dennett and others.
  53. ^ Searle distinguishes between "intrinsic" intentionality and "derived" intentionality. "Intrinsic" intentionality is the kind that involves "conscious understanding" like you would have in a human mind. Daniel Dennett doesn't agree that there is a distinction. Cole (2004, p. 19) writes "derived intentionality is all there is, according to Dennett."
  54. ^ Cole 2004, p. 18 (where he calls this the "internalist" approach to meaning.) Proponents of this position include Roger Schank, Doug Lenat, Marvin Minsky and (with reservations) Daniel Dennett, who writes "The fact is that any program [that passed a Turing test] would have to be an extraordinarily supple, sophisticated, and multilayered system, brimming with 'world knowledge' and meta-knowledge and meta-meta-knowledge." (Dennett 1997, p. 438)
  55. ^ Dreyfus 1979. See "the epistemological assumption".
  56. ^ Searle 1984. He also writes "Formal symbols by themselves can never be enough for mental contents, because the symbols, by definition, have no meaning (or interpretation, or semantics) except insofar as someone outside the system gives it to them" Searle 1989, p. 45 quoted in Cole 2004, p. 16.
  57. ^ Searle 1980, pp. 7–8, Cole 2004, pp. 12–13, Hauser 2006, pp. 3–4, Churchland & Churchland 1990. Cole (2004, p. 12) ascribes this position to Paul Churchland, Patricia Churchland and Ray Kurzweil.
  58. ^ Cole 2004, p. 4, Hauser 2006, p. 11. Early versions of this argument were put forward in 1974 by Lawrence Davis and in 1978 by Ned Block. Block's version used walky talkies and was called the "Chinese Gym". Churchland & Churchland (1990) described this scenario as well.
  59. ^ Russell Norvig, pp. 956–8, Cole 2004, p. 20, Moravec 1988, Kurzweil 2005, p. 262, Crevier 1993, pp. 271 and 279. An early version of this argument was put forward by Clark Glymour in the mid-70s and was touched on by Zenon Pylyshyn in 1980. Moravec (1988) presented a vivid version of it, and it is now associated with Ray Kurzweil's version of transhumanism.
  60. ^ Searle predicts that, while going through the brain prosthesis, "you find, to your total amazement, that you are indeed losing control of you external behavior. You find, for example, that when doctors test your vision, you hear them say 'We are holding up a red object in front of you; pleas tell us what you see.' You want to cry out 'I can't see anything. I'm going totally blind.' But you hear your voice saying in a way that is completely out your control, 'I see a red object in front of me.' ... [Y]our conscious experience slowly shrinks to nothing, while your externally observable behavior remains the same." Searle 1992 quoted in Russell & Norvig 2003, p. 957.
  61. ^ Cole (2004, pp. 12 & 17) ascribes this position to Andy Clark and Ray Kurzweil. Hauser (2006, p. 7) associates this position with Paul and Patricia Churchland.
  62. ^ Searle 1980, pp. 8–9, Hauser 2006, p. 11,
  63. ^ Searle (1980, p. 7) writes that the robot reply "tacitly concedes that cognition is not solely a matter of formal symbol manipulation." Harnad (2001, p. 14) makes the same point, writing: "Now just as it is no refutation (but rather an affirmation) of the CRA to deny that [the Turing test] is a strong enough test, or to deny that a computer could ever pass it, it is merely special pleading to try to save computationalism by stipulating ad hoc (in the face of the CRA) that implementational details do matter after all, and that the computer's is the 'right' kind of implementation, whereas Searle's is the 'wrong' kind."
  64. ^ Searle 1980, p. 8.
  65. ^ That is, any program running on a machine with a finite amount memory.
  66. ^ Quoted in Cole 2004, p. 13.
  67. ^ Dennett 1991, pp. 437 & 440
  68. ^ a b Dennett 1991, p. 438.
  69. ^ Cole 2004, pp. 14–15, Crevier 1993, pp. 269–270, Pinker, p. 95. Cole (2004, p. 14) ascribes this "speed" position to Daniel Dennett, Tim Maudlin, David Chalmers, Steven Pinker, Paul Churchland, Patricia Churchland and others. Dennett (1991, p. 438) points out the complexity of world knowledge.
  70. ^ Crevier 1993, p. 269.
  71. ^ Churchland & Churchland 1990, Cole 2004, p. 12, Crevier 1993, p. 270, Hearn 2007, pp. 45–46, Pinker 1997, p. 94
  72. ^ Churchland & Churchland 1990.
  73. ^ Harnad 2001, p. 7. Critics of the "phase transition" form of this argument include Harnad, Tim Maudlin, Daniel Dennett and Cole (2004, p. 14). This "phase transition" idea is a version of strong emergentism (what Daniel Dennett derides as "Woo woo West Coast emergence" (Crevier 1993, p. 275)). Harnad accuses Churchland and Patricia Churchland of espousing strong emergentism. Ray Kurzweil (2005) also holds a form of strong emergentism.
  74. ^ Searle 1980, p. 10.
  75. ^ Searle 1980, p. 9, Cole 2004, p. 13, Hauser 2006, pp. 4–5, Nilsson 1984. Turing (1950, pp. 11–12) makes this reply to what he calls "The Argument from Consciousness." Cole (2004, pp. 12–13) ascribes this position to Daniel Dennett, Ray Kurzweil and Hans Moravec.
  76. ^ Nilsson 1984
  77. ^ Turing 1950, p. 11
  78. ^ One of Turing's motivations for devising the Turing test is to avoid precisely the kind of philosophical problems that Searle is interested in. He writes "I do not wish to give the impression that I think there is no mystery ... [but] I do not think these mysteries necessarily need to be solved before we can answer the question with which we are concerned in this paper." (Turing 1950, p. 12) Although Turing is discussing consciousness (not the mind or understanding or intentionality), Norvig & Russell (2003, pp. 952–953) argue that Turing's comments apply the Chinese room.
  79. ^ Dennett 1991,[page needed].
  80. ^ Cole 2004, p. 22, Crevier 1993, p. 271, Harnad 2004, p. 4
  81. ^ Searle 1984, Searle 1990. The wording of each axiom and conclusion if from Searle (1990). This version is based on Hauser 2006, p. 5. (A1-3) and (C1) are described as 1,2,3 and 4 in Cole 2004, p. 5.
  82. ^ Churchland & Churchland (1990, p. 34) explain that the Chinese Room argument is intended to "shore up axiom 3".
  83. ^ Harnad (2001) argues that Searle's primary target is computationalism.


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