The Chinese room argument holds that a program cannot give a computer a "mind", "understanding" or "consciousness",regardless of how intelligently or human-like the program may make the computer behave. The argument was first presented by philosopher John Searle in his paper, "Minds, Brains, and Programs", published in Behavioral and Brain Sciences in 1980. It has been widely discussed in the years since. The centerpiece of the argument is a thought experiment known as the Chinese room.
The mind is a set of cognitive faculties including consciousness, perception, thinking, judgement, language and memory. It is usually defined as the faculty of an entity's thoughts and consciousness. It holds the power of imagination, recognition, and appreciation, and is responsible for processing feelings and emotions, resulting in attitudes and actions.
Intentionality is a philosophical concept and is defined by the Stanford Encyclopedia of Philosophy as "the power of minds to be about, to represent, or to stand for, things, properties and states of affairs". The once obsolete term dates from medieval scholastic philosophy, but in more recent times it has been resurrected by Franz Brentano and adopted by Edmund Husserl. The earliest theory of intentionality is associated with St. Anselm's ontological argument for the existence of God, and with his tenets distinguishing between objects that exist in the understanding and objects that exist in reality.
Consciousness is the state or quality of awareness or of being aware of an external object or something within oneself. It has been defined variously in terms of sentience, awareness, qualia, subjectivity, the ability to experience or to feel, wakefulness, having a sense of selfhood or soul, the fact that there is something "that it is like" to "have" or "be" it, and the executive control system of the mind. Despite the difficulty in definition, many philosophers believe that there is a broadly shared underlying intuition about what consciousness is. As Max Velmans and Susan Schneider wrote in The Blackwell Companion to Consciousness: "Anything that we are aware of at a given moment forms part of our consciousness, making conscious experience at once the most familiar and most mysterious aspect of our lives."
The argument is directed against the philosophical positions of functionalism and computationalism,which hold that the mind may be viewed as an information-processing system operating on formal symbols. Specifically, the argument is intended to refute a position Searle calls Strong AI:
Functionalism is a viewpoint of the theory of the mind, the latter not to be confused with Theory of Mind. It states that mental states are constituted solely by their functional role in, i.e. causal relations with, other mental states, sensory inputs and behavioral outputs. Functionalism developed largely as an alternative to the identity theory of mind and behaviorism.
The appropriately programmed computer with the right inputs and outputs would thereby have a mind in exactly the same sense human beings have minds.
Although it was originally presented in reaction to the statements of artificial intelligence (AI) researchers, it is not an argument against the goals of AI research, because it does not limit the amount of intelligence a machine can display.The argument applies only to digital computers running programs and does not apply to machines in general.
In the field of computer science, artificial intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. Computer science defines AI research as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. More specifically, Kaplan and Haenlein define AI as “a system’s ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation”. Colloquially, the term "artificial intelligence" is applied when a machine mimics "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving".
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 they are talking to another Chinese-speaking human being.
A thought experiment considers some hypothesis, theory, or principle for the purpose of thinking through its consequences. Given the structure of the experiment, it may not be possible to perform it, and even if it could be performed, there need not be an intention to perform it.
Chinese is a group of related, but in many cases not mutually intelligible, language varieties, forming the Sinitic branch of the Sino-Tibetan language family. Chinese is spoken by the Han majority and many minority ethnic groups in China. About 1.2 billion people speak some form of Chinese as their first language.
A computer program is a collection of instructions that performs a specific task when executed by a computer. A computer requires programs to function.
The question Searle wants to answer is this: does the machine literally "understand" Chinese? Or is it merely simulating the ability to understand Chinese?Searle calls the first position "strong AI" and the latter "weak AI".
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 papers, 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. If the computer had passed the Turing test this way, it follows, says Searle, that he would do so as well, simply by running the program manually.
Searle asserts that there is no essential difference between the roles of the computer and himself in the experiment. Each simply follows a program, step-by-step, producing a behavior which is then interpreted by the user as demonstrating intelligent conversation. However, Searle himself would not be able to understand the conversation. ("I don't speak a word of Chinese,"he points out.) Therefore, he argues, it follows that the computer would not be able to understand the conversation either.
Searle argues that, without "understanding" (or "intentionality"), we cannot describe what the machine is doing as "thinking" and, since it does not think, it does not have a "mind" in anything like the normal sense of the word. Therefore, he concludes that "strong AI" is false.
Gottfried Leibniz made a similar argument in 1714 against mechanism (the position that the mind is a machine and nothing more). Leibniz used the thought experiment of expanding the brain until it was the size of a mill.Leibniz found it difficult to imagine that a "mind" capable of "perception" could be constructed using only mechanical processes. In the 1961 short story "The Game" by Anatoly Dneprov, a stadium of people act as switches and memory cells implementing a program to translate a sentence of Portuguese, a language that none of them knows. In 1974, Lawrence Davis imagined duplicating the brain using telephone lines and offices staffed by people, and in 1978 Ned Block envisioned the entire population of China involved in such a brain simulation. This thought experiment is called the China brain, also the "Chinese Nation" or the "Chinese Gym".
The Chinese Room Argument was introduced in Searle's 1980 paper "Minds, Brains, and Programs", published in Behavioral and Brain Sciences .It eventually became the journal's "most influential target article", generating an enormous number of commentaries and responses in the ensuing decades, and Searle has continued to defend and refine the argument in many papers, popular articles and books. David Cole writes that "the Chinese Room argument has probably been the most widely discussed philosophical argument in cognitive science to appear in the past 25 years".
Most of the discussion consists of attempts to refute it. "The overwhelming majority", notes BBS editor Stevan Harnad,"still think that the Chinese Room Argument is dead wrong". The sheer volume of the literature that has grown up around it inspired Pat Hayes to comment 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".
Searle's argument has become "something of a classic in cognitive science", according to Harnad.Varol Akman agrees, and has described the original paper as "an exemplar of philosophical clarity and purity".
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,and is related to such questions as the mind–body problem, the problem of other minds, the symbol-grounding problem, and the hard problem of consciousness.
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. and is also quoted in Daniel Dennett 's Consciousness Explained . 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." Strong AI is defined similarly by Stuart Russell and Peter Norvig : "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." </ref>
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."
The position is implicit in some of the statements of early AI researchers and analysts. For example, in 1955, AI founder Herbert A. Simon declared that "there are now in the world machines that think, that learn and create"and claimed that they had "solved the venerable mind–body problem, explaining how a system composed of matter can have the properties of mind." 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."
Searle also ascribes the following positions to advocates of strong AI:
In more recent presentations of the Chinese room argument, Searle has identified "strong AI" as "computer functionalism" (a term he attributes to Daniel Dennett).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."Computationalism 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:
Searle holds a philosophical position he calls "biological naturalism": that consciousnessand understanding require specific biological machinery that are found in brains. He writes "brains cause minds" and that "actual human mental phenomena [are] dependent on actual physical–chemical properties of actual human brains". Searle argues that this machinery (known to neuroscience as the "neural correlates of consciousness") must have some (unspecified) "causal powers" that permit the human experience of consciousness. Searle's faith in the existence of these powers has been criticized.
Searle does not disagree with the notion that machines can have consciousness and understanding, because, as he writes, "we are precisely such machines".Searle holds that the brain is, in fact, a machine, but that the brain gives rise to consciousness and understanding using machinery that is non-computational. If neuroscience is able to isolate the mechanical process that gives rise to consciousness, then Searle grants that it may be possible to create machines that have consciousness and understanding. However, without the specific machinery required, Searle does not believe that consciousness can occur.
Biological naturalism implies that one cannot determine if the experience of consciousness is occurring merely by examining how a system functions, because the specific machinery of the brain is essential. Thus, biological naturalism is directly opposed to both behaviorism and functionalism (including "computer functionalism" or "strong AI").Biological naturalism is similar to identity theory (the position that mental states are "identical to" or "composed of" neurological events); however, Searle has specific technical objections to identity theory. Searle's biological naturalism and strong AI are both opposed to Cartesian dualism, the classical idea that the brain and mind are made of different "substances". Indeed, Searle accuses strong AI of dualism, writing that "strong AI only makes sense given the dualistic assumption that, where the mind is concerned, the brain doesn't matter."
Searle's original presentation emphasized "understanding"—that is, mental states with what philosophers call "intentionality"—and did not directly address other closely related ideas such as "consciousness". However, in more recent presentations Searle has included consciousness as the real target of the argument.
Computational models of consciousness are not sufficient by themselves for consciousness. The computational model for consciousness stands to consciousness in the same way the computational model of anything stands to the domain being modelled. Nobody supposes that the computational model of rainstorms in London will leave us all wet. But they make the mistake of supposing that the computational model of consciousness is somehow conscious. It is the same mistake in both cases.— John R. Searle, Consciousness and Language, p. 16
David Chalmers writes "it is fairly clear that consciousness is at the root of the matter" of the Chinese room.
Colin McGinn argues that the Chinese room provides strong evidence that the hard problem of consciousness is fundamentally insoluble. The argument, to be clear, is not about whether a machine can be conscious, but about whether it (or anything else for that matter) can be shown to be conscious. It is plain that any other method of probing the occupant of a Chinese room has the same difficulties in principle as exchanging questions and answers in Chinese. It is simply not possible to divine whether a conscious agency or some clever simulation inhabits the room.
Searle argues that this is only true for an observer outside of the room. The whole point of the thought experiment is to put someone inside the room, where they can directly observe the operations of consciousness. Searle claims that from his vantage point within the room there is nothing he can see that could imaginably give rise to consciousness, other than himself, and clearly he does not have a mind that can speak Chinese.
Patrick Hew used the Chinese Room argument to deduce requirements from military command and control systems if they are to preserve a commander's moral agency. He drew an analogy between a commander in their command center and the person in the Chinese Room, and analyzed it under a reading of Aristotle’s notions of "compulsory" and "ignorance". Information could be "down converted" from meaning to symbols, and manipulated symbolically, but moral agency could be undermined if there was inadequate 'up conversion' into meaning. Hew cited examples from the USS Vincennes incident.
The Chinese room argument is primarily an argument in the philosophy of mind, and both major computer scientists and artificial intelligence researchers consider it irrelevant to their fields.However, several concepts developed by computer scientists are essential to understanding the argument, including symbol processing, Turing machines, Turing completeness, and the Turing test.
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."The primary mission of artificial intelligence research is only to create useful systems that act intelligently, and it does not matter if the intelligence is "merely" a simulation.
Searle does not disagree that AI research can create machines that are capable of highly intelligent behavior. The Chinese room argument leaves open the possibility that a digital machine could be built that acts more intelligently than a person, but does not have a mind or intentionality in the same way that brains do. The Chinese room argument is not a reductio ad absurdum , rather it is an example that requires explanation.
Searle's "strong AI" should not be confused with "strong AI" as defined by Ray Kurzweil and other futurists,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. Searle argues that even a super-intelligent machine would not necessarily have a mind and consciousness.
The Chinese room implements a version of the Turing test.Alan Turing introduced the test in 1950 to help answer the question "can machines think?" In the standard version, a human judge engages in a natural language conversation with a human and a machine designed to generate performance indistinguishable from that of a human being. All participants are separated from one another. If the judge cannot reliably tell the machine from the human, the machine is said to have passed the test.
Turing then considered each possible objection to the proposal "machines can think", and found that there are simple, obvious answers if the question is de-mystified in this way. He did not, however, intend for the test to measure for the presence of "consciousness" or "understanding". He did not believe this was relevant to the issues that he was addressing. He wrote:
I do not wish to give the impression that I think there is no mystery about consciousness. There is, for instance, something of a paradox connected with any attempt to localise it. 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.
To Searle, as a philosopher investigating in the nature of mind and consciousness, these are the relevant mysteries. The Chinese room is designed to show that the Turing test is insufficient to detect the presence of consciousness, even if the room can behave or function as a conscious mind would.
The Chinese room (and all modern computers) manipulate physical objects in order to carry out calculations and do simulations. AI researchers Allen Newell and Herbert A. 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 computer manipulates the symbols using a form of syntax rules, without any knowledge of the symbol's semantics (that is, their meaning).
Newell and Simon had conjectured that a physical symbol system (such as a digital computer) had all the necessary machinery for "general intelligent action", or, as it is known today, artificial general intelligence. They framed this as a philosophical position, the physical symbol system hypothesis: "A physical symbol system has the necessary and sufficient means for general intelligent action."The Chinese room argument does not refute this, because it is framed in terms of "intelligent action", i.e. the external behavior of the machine, rather than the presence or absence of understanding, consciousness and mind.
The Chinese room has a design analogous to that of a 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, given enough memory and time. Alan Turing writes, "all digital computers are in a sense equivalent."The widely accepted Church–Turing thesis holds that any function computable by an effective procedure is computable by a Turing machine.
The Turing completeness of the Chinese room implies that it can do whatever any other digital computer can do (albeit much, much more slowly). Thus, if the Chinese room does not or can not contain a Chinese-speaking mind, then no other digital computer can contain a mind. Some replies to Searle begin by arguing that the room, as described, cannot have a Chinese-speaking mind. Arguments of this form, according to Stevan Harnad, are "no refutation (but rather an affirmation)"of the Chinese room argument, because these arguments actually imply that no digital computers can have a mind.
There are some critics, such as Hanoch Ben-Yami, who argue that the Chinese room cannot simulate all the abilities of a digital computer, such as being able to determine the current time.
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.The only 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.
He begins with three axioms:
Searle posits that these lead directly to this conclusion:
This much of the argument is intended to show that artificial intelligence can 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?He begins with an axiom that is intended to express the basic modern scientific consensus about brains and minds:
Searle claims that we can derive "immediately" and "trivially"that:
And from this he derives the further conclusions:
Replies to Searle's argument may be classified according to what they claim to show:
Some of the arguments (robot and brain simulation, for example) fall into multiple categories.
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".
Searle notes that (in this simple version of the reply) the "system" is nothing more than a collection of ordinary physical objects; it grants the power of understanding and consciousness to "the conjunction of that person and bits of paper"without making any effort to explain how this pile of objects has become a conscious, thinking being. Searle argues that no reasonable person should be satisfied with the reply, unless they are "under the grip of an ideology;" In order for this reply to be remotely plausible, one must take it for granted that consciousness can be the product of an information processing "system", and does not require anything resembling the actual biology of the brain.
Searle then responds by simplifying this 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 because now "the system" and "the man" both describe exactly the same object.
Critics of Searle's response argue that the program has allowed the man to have two minds in one head.[ who? ] If we assume a "mind" is a form of information processing, then the theory of computation can account for two computations occurring at once, namely (1) the computation for universal programmability (which is the function instantiated by the person and note-taking materials independently from any particular program contents) and (2) the computation of the Turing machine that is described by the program (which is instantiated by everything including the specific program). The theory of computation thus formally explains the open possibility that the second computation in the Chinese Room could entail a human-equivalent semantic understanding of the Chinese inputs. The focus belongs on the program's Turing machine rather than on the person's. However, from Searle's perspective, this argument is circular. The question at issue is whether consciousness is a form of information processing, and this reply requires that we make that assumption.
More sophisticated versions of the systems 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 systems reply, described below).
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."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." 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.
However, the thought experiment is not intended to be a reductio ad absurdum, but rather an example that requires explanation. Searle is not asserting that the situation is impossible, but rather that it is difficult or impossible to explain how this system can have subjective conscious experience.The system reply succeeds in showing that it is not impossible but fails to show how the system would have consciousness; the replies, by themselves, 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 the system must understand Chinese."
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 is 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.
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."
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.
These arguments are all versions of the systems reply that identify a particular kind of system as being important; they identify some special technology that would create conscious understanding in a machine. (Note that the "robot" and "commonsense knowledge" replies above also specify a certain kind of system as being important.)
|“||[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. [ page needed ]
These arguments (and the robot or commonsense knowledge replies) identify some special technology that would help create conscious understanding in a machine. They may be interpreted in two ways: either they claim (1) this technology is required for consciousness, the Chinese room does not or cannot implement this technology, and therefore the Chinese room cannot pass the Turing test or (even if it did) it would not have conscious understanding. Or they may be claiming that (2) it is easier to see that the Chinese room has a mind if we visualize this technology as being used to create it.
In the first case, where features like a robot body or a connectionist architecture are required, Searle claims that strong AI (as he understands it) has been abandoned.The Chinese room has all the elements of a Turing complete machine, and thus is capable of simulating any digital computation whatsoever. If Searle's room can't pass the Turing test then there is no other digital technology that could pass the Turing test. If Searle's room could pass the Turing test, but still does not have a mind, then 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 as "strong AI", proving his argument.
The brain arguments in particular deny strong AI if 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."If computation does not provide an explanation of the human mind, then strong AI has failed, according to Searle.
Other critics hold that the room as Searle described it does, in fact, have a mind, however 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).
In fact, the room can just as easily be redesigned to weaken our intuitions. Ned Block's Blockhead argumentsuggests 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. 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 (to the point of being physically impossible), and the states could therefore be extremely specific.
Searle argues that however the program is written or however the machine is connected to the world, the mind is being simulated by a simple step-by-step digital machine (or machines). These machines are always 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 writes: "I can have any formal program you like, but I still understand nothing."
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. These arguments, if accepted, prevent Searle from claiming that his conclusion is obvious by undermining the intuitions that his certainty requires.
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."Daniel Dennett describes the Chinese room argument as a misleading "intuition pump" 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."
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 of the replies above also address the specific 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.
An especially vivid version of the speed and complexity reply is from Paul and Patricia Churchland. They propose this analogous thought experiment:
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.')"
Searle argues that his critics are also relying on intuitions, however his opponents' intuitions have no empirical basis. He writes that, in order to consider the "system reply" as remotely plausible, a person must be "under the grip of an ideology".The system reply only makes sense (to Searle) if one assumes that any "system" can have consciousness, just by virtue of being a system with the right behavior and functional parts. This assumption, he argues, is not tenable given our experience of consciousness.
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."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 cannot 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.
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."
Alan Turing anticipated Searle's line of argument (which he called "The Argument from Consciousness") in 1950 and makes the other minds reply.He 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." 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.
Daniel Dennett provides this extension to the "epiphenomena" argument.
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."He takes it as obvious that we can detect the presence of consciousness and dismisses these replies as being off the point.
The Chinese room argument is a central concept in Peter Watts's novels Blindsight and (to a lesser extent) Echopraxia. [ citation needed ] In Season 4 of the American crime drama Numb3rs there is a brief reference to the Chinese room.[ citation needed ]It is also a central theme in the video game Virtue's Last Reward , and ties into the game's narrative.
The Chinese Room is also the name of a British independent video game development studio best known for working on experimental first-person games, such as Everybody's Gone to the Rapture , or Dear Esther .
Cognitive science is the interdisciplinary, scientific study of the mind and its processes. It examines the nature, the tasks, and the functions of cognition. Cognitive scientists study intelligence and behavior, with a focus on how nervous systems represent, process, and transform information. Mental faculties of concern to cognitive scientists include language, perception, memory, attention, reasoning, and emotion; to understand these faculties, cognitive scientists borrow from fields such as linguistics, psychology, artificial intelligence, philosophy, neuroscience, and anthropology. The typical analysis of cognitive science spans many levels of organization, from learning and decision to logic and planning; from neural circuitry to modular brain organization. The fundamental concept of cognitive science is that "thinking can best be understood in terms of representational structures in the mind and computational procedures that operate on those structures."
John Rogers Searle is an American philosopher. He is currently Willis S. and Marion Slusser Professor Emeritus of the Philosophy of Mind and Language and Professor of the Graduate School at the University of California, Berkeley. Widely noted for his contributions to the philosophy of language, philosophy of mind, and social philosophy, he began teaching at UC Berkeley in 1959.
Consciousness Explained is a 1991 book by the American philosopher Daniel Dennett, in which the author offers an account of how consciousness arises from interaction of physical and cognitive processes in the brain.
The Mind's I: Fantasies and reflections on self and soul is a 1981 collection of essays and other texts about the nature of the mind and the self, edited with commentary by philosophers Douglas R. Hofstadter and Daniel C. Dennett. The texts range from early philosophical and fictional musings on a subject that could seemingly only be examined in the realm of thought, to works from the twentieth century where the nature of the self became a viable topic for scientific study.
Eliminative materialism is the claim that people's common-sense understanding of the mind is false and that certain classes of mental states that most people believe in do not exist. It is a materialist position in the philosophy of mind. Some supporters of eliminativism argue that no coherent neural basis will be found for many everyday psychological concepts such as belief or desire, since they are poorly defined. Rather, they argue that psychological concepts of behaviour and experience should be judged by how well they reduce to the biological level. Other versions entail the non-existence of conscious mental states such as pain and visual perceptions.
"Computing Machinery and Intelligence" is a seminal paper written by Alan Turing on the topic of artificial intelligence. The paper, published in 1950 in Mind, was the first to introduce his concept of what is now known as the Turing test to the general public.
Artificial general intelligence (AGI) is the intelligence of a machine that could successfully perform any intellectual task that a human being can. It is a primary goal of some artificial intelligence research and a common topic in science fiction and future studies. Some researchers refer to Artificial general intelligence as "strong AI", "full AI" or as the ability of a machine to perform "general intelligent action"; others reserve "strong AI" for machines capable of experiencing consciousness.
A philosophical zombie or p-zombie in the philosophy of mind and perception is a hypothetical being that from the outside is indistinguishable from a normal human being but lacks conscious experience, qualia, or sentience. For example, if a philosophical zombie was poked with a sharp object it would not feel any pain sensation, yet could behave exactly as if it does feel pain.
An artificial brain is software and hardware with cognitive abilities similar to those of the animal or human brain.
Synthetic intelligence (SI) is an alternative term for artificial intelligence which emphasizes that the intelligence of machines need not be an imitation or in any way artificial; it can be a genuine form of intelligence. John Haugeland proposes an analogy with simulated diamonds and synthetic diamonds—only the synthetic diamond is truly a diamond. Synthetic means that which is produced by synthesis; combining parts to form a whole, colloquially, a man-made version of that which has arisen naturally. As defined, a "synthetic intelligence" would therefore be man-made, but not a simulation.
A physical symbol system takes physical patterns (symbols), combining them into structures (expressions) and manipulating them to produce new expressions.
Artificial intelligence has close connections with philosophy because both share several concepts and these include intelligence, action, consciousness, epistemology, and even free will. Furthermore, the technology is concerned with the creation of artificial animals or artificial people so the discipline is of considerable interest to philosophers. These factors contributed to the emergence of the philosophy of artificial intelligence. Some scholars argue that the AI community's dismissal of philosophy is detrimental.
In the philosophy of mind, the China brain thought experiment considers what would happen if each member of the Chinese nation were asked to simulate the action of one neuron in the brain, using telephones or walkie-talkies to simulate the axons and dendrites that connect neurons. Would this arrangement have a mind or consciousness in the same way that brains do?
An intuition pump is a thought experiment structured to allow the thinker to use their intuition to develop an answer to a problem.
The symbol grounding problem is related to the problem of how words (symbols) get their meanings, and hence to the problem of what meaning itself really is. The problem of meaning is in turn related to the problem of how it is that mental states are meaningful, hence to the problem of consciousness.
In philosophy, the computational theory of mind (CTM) refers to a family of views that hold that the human mind is an information processing system and that cognition and consciousness together are a form of computation. Warren McCulloch and Walter Pitts (1943) were the first to suggest that neural activity is computational. They argued that neural computations explain cognition. The theory was proposed in its modern form by Hilary Putnam in 1967, and developed by his PhD student, philosopher and cognitive scientist Jerry Fodor in the 1960s, 1970s and 1980s. Despite being vigorously disputed in analytic philosophy in the 1990s due to work by Putnam himself, John Searle, and others, the view is common in modern cognitive psychology and is presumed by many theorists of evolutionary psychology. In the 2000s and 2010s the view has resurfaced in analytic philosophy.
Shadows of the Mind: A Search for the Missing Science of Consciousness is a 1994 book by mathematical physicist Roger Penrose that serves as a followup to his 1989 book The Emperor's New Mind: Concerning Computers, Minds and The Laws of Physics.
The Turing test, developed by Alan Turing in 1950, is a test of a machine's ability to exhibit intelligent behavior equivalent to, or indistinguishable from, that of a human. Turing proposed that a human evaluator would judge natural language conversations between a human and a machine designed to generate human-like responses. The evaluator would be aware that one of the two partners in conversation is a machine, and all participants would be separated from one another. The conversation would be limited to a text-only channel such as a computer keyboard and screen so the result would not depend on the machine's ability to render words as speech. If the evaluator cannot reliably tell the machine from the human, the machine is said to have passed the test. The test results do not depend on the machine's ability to give correct answers to questions, only how closely its answers resemble those a human would give.
Strong artificial intelligence or, True AI, may refer to:
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