In philosophy of mind, the computational theory of mind (CTM), also known as computationalism, is 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. It is closely related to functionalism, a broader theory that defines mental states by what they do rather than what they are made of.
Overview
Warren McCulloch and Walter Pitts (1943) were the first to suggest that neural activity is computational. They argued that neural computations explain cognition. A version of the theory was put forward by Peter Putnam and Robert W. Fuller in 1964. The theory was proposed in its modern form by Hilary Putnam in 1960 and 1961, aided by his then PhD student, philosopher and cognitive scientist Jerry Fodor, who continued the research as a post-doc in the 1960s, 1970s, and 1980s. It was later criticized in the 1990s by Putnam himself, John Searle, and others.
The computational theory of mind holds that the human mind is a
computational system that is realized (i.e., physically implemented) by
neural activity in the brain. The theory can be elaborated in many ways
and varies largely based on how the term computation is understood.
Computation is commonly understood in terms of Turing machines
which manipulate symbols according to a rule, in combination with the
internal state of the machine. The critical aspect of such a
computational model is that we can abstract away from particular
physical details of the machine that is implementing the computation. For example, the appropriate computation could be implemented either by
silicon chips or biological neural networks, so long as there is a
series of outputs based on manipulations of inputs and internal states,
performed according to a rule. CTM therefore holds that the mind is not
simply analogous to a computer program, but that it is literally a
computational system.
Computational theories of mind are often said to require mental representation
because 'input' into a computation comes in the form of symbols or
representations of other objects. A computer cannot compute an actual
object but must interpret and represent the object in some form and then
compute the representation. The computational theory of mind is related
to the representational theory of mind
in that they both require that mental states are representations.
However, the representational theory of mind shifts the focus to the
symbols being manipulated. This approach better accounts for
systematicity and productivity. In Fodor's original views, the computational theory of mind is also related to the language of thought. The language of thought theory allows the mind to process more complex representations with the help of semantics.
Recent work has suggested that we make a distinction between the
mind and cognition. Building from the tradition of McCulloch and Pitts,
the computational theory of cognition (CTC) states that neural computations explain cognition. The computational theory of mind asserts that not only cognition, but also phenomenal consciousness or qualia,
are computational. That is to say, CTM entails CTC. While phenomenal
consciousness could fulfill some other functional role, computational
theory of cognition leaves open the possibility that some aspects of the
mind could be non-computational. CTC, therefore, provides an important
explanatory framework for understanding neural networks, while avoiding
counter-arguments that center around phenomenal consciousness.
"Computer metaphor"
Computational theory of mind is not the same as the computer metaphor, comparing the mind to a modern-day digital computer. Computational theory just uses some of the same principles as those found in digital computing. While the computer metaphor draws an analogy between the mind as
software and the brain as hardware, CTM is the claim that the mind is a
computational system. More specifically, it states that a computational
simulation of a mind is sufficient for the actual presence of a mind,
and that a mind truly can be simulated computationally.
'Computational system' is not meant to mean a modern-day
electronic computer. Rather, a computational system is a symbol
manipulator that follows step-by-step functions to compute input and
form output. Alan Turing describes this type of computer in his concept of a Turing machine.
Criticism
A range of arguments have been proposed against physicalist conceptions used in computational theories of mind.
An early, though indirect, criticism of the computational theory of mind comes from philosopher John Searle. In his thought experiment known as the Chinese room, Searle attempts to refute the claims that artificially intelligent agents can be said to have intentionality and understanding and that these systems, because they can be said to be minds themselves, are sufficient for the study of the human mind. Searle asks us to imagine that there is a man in a room with no way of
communicating with anyone or anything outside of the room except for a
piece of paper with symbols written on it that is passed under the door.
With the paper, the man is to use a series of provided rule books to
return paper containing different symbols. Unknown to the man in the
room, these symbols are of a Chinese language, and this process
generates a conversation that a Chinese speaker outside of the room can
actually understand. Searle contends that the man in the room does not
understand the Chinese conversation. This was originally written as a
repudiation of the idea that computers work like minds.
Searle has further raised questions about what exactly constitutes a computation:
the wall behind my back is right now implementing the WordStar
program, because there is some pattern of molecule movements that is
isomorphic with the formal structure of WordStar. But if the wall is
implementing WordStar, if it is a big enough wall it is implementing any
program, including any program implemented in the brain.
Objections like Searle's might be called insufficiency objections.
They claim that computational theories of mind fail because computation
is insufficient to account for some capacity of the mind. Arguments from
qualia, such as Frank Jackson's knowledge argument,
can be understood as objections to computational theories of mind in
this way—though they take aim at physicalist conceptions of the mind in
general, and not computational theories specifically.
Objections have also been put forth that are directly tailored for computational theories of mind.
Jerry Fodor himself argues that the mind is still a very long way
from having been explained by the computational theory of mind. The
main reason for this shortcoming is that most cognition is abductive
and global, hence sensitive to all possibly relevant background beliefs
to (dis)confirm a belief. This creates, among other problems, the frame problem
for the computational theory, because the relevance of a belief is not
one of its local, syntactic properties but context-dependent.
Putnam himself (see in particular Representation and Reality and the first part of Renewing Philosophy)
became a prominent critic of computationalism for a variety of reasons,
including ones related to Searle's Chinese room arguments, questions of
world-word reference relations, and thoughts about the mind-body problem.
Regarding functionalism in particular, Putnam has claimed along lines
similar to, but more general than Searle's arguments, that the question
of whether the human mind can implement computational states is
not relevant to the question of the nature of mind, because "every
ordinary open system realizes every abstract finite automaton." Computationalists have responded by aiming to develop criteria describing what exactly counts as an implementation.
Roger Penrose
has proposed the idea that the human mind does not use a knowably sound
calculation procedure to understand and discover mathematical
intricacies. This would mean that a normal Turing complete computer would not be able to ascertain certain mathematical truths that human minds can. The application of Gödel's theorem by Penrose to demonstrate it, however, was widely criticized, and is considered erroneous.
Pancomputationalism
CTM
raises a question that remains a subject of debate: what does it take
for a physical system (such as a mind, or an artificial computer) to
perform computations? A very straightforward account is based on a
simple mapping between abstract mathematical computations and physical
systems: a system performs computation C if and only if there is a
mapping between a sequence of states individuated by C and a sequence of
states individuated by a physical description of the system.
Putnam (1988) and Searle (1992) argue that this simple mapping account (SMA) trivializes the empirical import of computational descriptions. As Putnam put it, "everything is a Probabilistic Automaton under some Description". Even rocks, walls, and buckets of water—contrary to appearances—are computing systems. Gualtiero Piccinini identifies different versions of Pancomputationalism.
In response to the trivialization criticism, and to restrict SMA,
philosophers of mind have offered different accounts of computational
systems. These typically include causal account, semantic account,
syntactic account, and mechanistic account. Instead of a semantic restriction, the syntactic account imposes a syntactic restriction. The mechanistic account was first introduced by Gualtiero Piccinini in 2007.
Notable theorists
Daniel Dennett proposed the multiple drafts model, in which consciousness seems linear
but is actually blurry and gappy, distributed over space and time in
the brain. Consciousness is the computation, there is no extra step in
which you become conscious of the computation.
Jerry Fodor
argues that mental states, such as beliefs and desires, are relations
between individuals and mental representations. He maintains that these
representations can only be correctly explained in terms of a language
of thought (LOT) in the mind. Further, this language of thought itself
is codified in the brain, not just a useful explanatory tool. Fodor
adheres to a species of functionalism, maintaining that thinking and
other mental processes consist primarily of computations operating on
the syntax of the representations that make up the language of thought.
In later work (Concepts and The Elm and the Expert), Fodor
has refined and even questioned some of his original computationalist
views, and adopted LOT2, a highly modified version of LOT.
David Marr proposed that cognitive processes have three levels of description: the computational level, which describes what operations the system performs and why it performs them; the algorithmic level, which presents the algorithm used for computing it; and the implementational level, which describes the physical implementation of the algorithm postulated at the algorithmic level.
Ulric Neisser coined the term cognitive psychology
in his book with that title published in 1967. Neisser characterizes
people as dynamic information-processing systems whose mental operations
might be described in computational terms.
Steven Pinker described language instinct as an evolved, built-in capacity to learn language (if not writing). His 1997 book How the Mind Works sought to popularize the computational theory of mind for wide audiences.
Hilary Putnam proposed functionalism
to describe consciousness, asserting that it is the computation that
equates to consciousness, regardless of whether the computation is
operating in a brain or in a computer.
The Chinese room argument holds that a computer executing a program cannot have a mind, understanding, or consciousness, regardless of how intelligently or human-like the program may make the
computer behave. The argument was presented in a 1980 paper by the
philosopher John Searle entitled "Minds, Brains, and Programs" and published in the journal Behavioral and Brain Sciences. Similar arguments had been made by Gottfried Wilhelm Leibniz (1714), Ned Block (1978) and others. Searle's version has been widely discussed in the years since. The centerpiece of Searle's argument is a thought experiment known as the Chinese room.
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, and that simulation of a given
mental state is sufficient for its presence. Specifically, the argument
is intended to refute a position Searle calls the strong AI hypothesis: "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 its proponents originally presented the argument in reaction to statements of artificial intelligence
(AI) researchers, it is not an argument against the goals of mainstream
AI research because it does not show a limit in the amount of
intelligent behavior a machine can display. The argument applies only to digital computers running programs and does not apply to machines in general. While widely discussed, the argument has been subject to significant criticism and remains controversial among philosophers of mind and AI researchers.
Chinese room thought experiment
Suppose
that artificial intelligence research has succeeded in programming a
computer to behave as if it understands Chinese. The machine accepts Chinese characters
as input, carries out each instruction of the program step by step, and
then produces Chinese characters as output. The machine does this so
perfectly that no one can tell that they are communicating with a
machine and not a hidden Chinese speaker.
The questions at issue are these: does the machine actually understand the conversation, or is it just simulating
the ability to understand the conversation? Does the machine have a
mind in exactly the same sense that people do, or is it just acting as if it had a mind?
Now suppose that Searle is in a room with an English version of
the program, along with sufficient pencils, paper, erasers and filing
cabinets. Chinese characters are slipped in under the door, and he
follows the program step-by-step, which eventually instructs him to
slide other Chinese characters back out under the door. If the computer
had passed the Turing test this way, it follows that Searle would do so as well, simply by running the program by hand.
Searle can see no essential difference between the roles of the computer and himself in the experiment. Each simply follows a program,
step-by-step, producing behavior that makes them appear to understand.
However, Searle would not be able to understand the conversation.
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 the normal sense of the
word. Therefore, he concludes that the strong AI hypothesis is false: a
computer running a program that simulates a mind would not have a mind
in the same sense that human beings have a mind.
History
Gottfried Leibniz made a similar argument in 1714 against mechanism
(the idea that everything that makes up a human being could, in
principle, be explained in mechanical terms. In other words, that a
person, including their mind, is merely a very complex machine). 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.
Peter Winch made the same point in his book The Idea of a Social Science and its Relation to Philosophy
(1958), where he provides an argument to show that "a man who
understands Chinese is not a man who has a firm grasp of the statistical
probabilities for the occurrence of the various words in the Chinese
language" (p. 108).
Soviet cyberneticist Anatoly Dneprov made an essentially identical argument in 1961, in the form of the short story "The Game".
In it, 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 know. The game was organized by a "Professor Zarubin" to answer the question
"Can mathematical machines think?" Speaking through Zarubin, Dneprov
writes "the only way to prove that machines can think is to turn
yourself into a machine and examine your thinking process" and he
concludes, as Searle does, "We've proven that even the most perfect
simulation of machine thinking is not the thinking process itself."
In 1974, Lawrence H. 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".
John Searle in December 2005
Searle's version appeared in his 1980 article "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 multiple 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 Behavioral and Brain Sciences 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".
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.
The definition depends on the distinction between simulating a mind
and actually having one. 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 claim is implicit in some of the statements of early AI
researchers and analysts. For example, in 1957, the economist and
psychologist Herbert A. Simon declared that "there are now in the world machines that think, that learn and create". Simon, together with Allen Newell and Cliff Shaw, after having completed the first program that could do formal reasoning (the Logic Theorist),
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 claims to advocates of strong AI:
AI systems can be used to explain the mind;
The study of the brain is irrelevant to the study of the mind; and
The Turing test is adequate for establishing the existence of mental states.
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). 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:
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.
Recent philosophical discussions have revisited the implications of
computationalism for artificial intelligence. Goldstein and Levinstein
explore whether large language models (LLMs) like ChatGPT
can possess minds, focusing on their ability to exhibit folk
psychology, including beliefs, desires, and intentions. The authors
argue that LLMs satisfy several philosophical theories of mental
representation, such as informational, causal, and structural theories,
by demonstrating robust internal representations of the world. However,
they highlight that the evidence for LLMs having action dispositions
necessary for belief-desire psychology remains inconclusive.
Additionally, they refute common skeptical challenges, such as the "stochastic parrots"
argument and concerns over memorization, asserting that LLMs exhibit
structured internal representations that align with these philosophical
criteria.
David Chalmers
suggests that while current LLMs lack features like recurrent
processing and unified agency, advancements in AI could address these
limitations within the next decade, potentially enabling systems to
achieve consciousness. This perspective challenges Searle's original
claim that purely "syntactic" processing cannot yield understanding or
consciousness, arguing instead that such systems could have authentic
mental states.
Strong AI vs. biological naturalism
Searle holds a philosophical position he calls "biological naturalism": that consciousness[a] and understanding require specific biological machinery that is 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 in neuroscience as the "neural correlates of consciousness") must have some causal powers that permit the human experience of consciousness. Searle's belief 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 specific machinery.
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".
Consciousness
Searle's original presentation emphasized understanding—that is, mental states with 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. In Searle's words, "the computer has nothing
more than I have in the case where I understand nothing".
Applied ethics
Sitting in the combat information center aboard a warship—proposed as a real-life analog to the Chinese room
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.
Computer science
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.
Strong AI vs. AI research
Searle's
arguments are not usually considered an issue for AI research. 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. AI researchers Stuart J. Russell and Peter Norvig
wrote in 2021: "We are interested in programs that behave
intelligently. Individual aspects of consciousness—awareness,
self-awareness, attention—can be programmed and can be part of an
intelligent machine. The additional project making a machine conscious
in exactly the way humans are is not one that we are equipped to take
on."
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.
Searle's "strong AI hypothesis" 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—that is, artificial general intelligence, human level AI or superintelligence. Kurzweil is referring primarily to the amount
of intelligence displayed by the machine, whereas Searle's argument
sets no limit on this. Searle argues that a superintelligent machine
would not necessarily have a mind and consciousness.
The
"standard interpretation" of the Turing Test, in which player C, the
interrogator, is given the task of trying to determine which player—A or
B—is a computer and which is a human. The interrogator is limited to
using the responses to written questions to make the determination.
Image adapted from Saygin, et al. 2000.
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.
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, 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.
Twenty-first century AI programs (such as "deep learning")
do mathematical operations on huge matrixes of unidentified numbers and
bear little resemblance to the symbolic processing used by AI programs
at the time Searle wrote his critique in 1980. Nils Nilsson
describes systems like these as "dynamic" rather than "symbolic".
Nilsson notes that these are essentially digitized representations of
dynamic systems—the individual numbers do not have a specific semantics,
but are instead samples or data points
from a dynamic signal, and it is the signal being approximated which
would have semantics. Nilsson argues it is not reasonable to consider
these signals as "symbol processing" in the same sense as the physical
symbol systems hypothesis.
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 machine that 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. 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.
Complete argument
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 Chinese room thought experiment is intended to prove point A3.
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 does not 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 thought experiment 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 no
programs are minds.
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:
(A4) Brains cause minds.
Searle claims that we can derive "immediately" and "trivially" 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.
Refutations of Searle's argument take a number of different forms
(see below). Computationalists and functionalists reject A3, arguing
that "syntax" (as Searle describes it) can have "semantics" if
the syntax has the right functional structure. Eliminative materialists
reject A2, arguing that minds don't actually have "semantics"—that
thoughts and other mental phenomena are inherently meaningless but
nevertheless function as if they had meaning.
Replies
Replies to Searle's argument may be classified according to what they claim to show:
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
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.
Systems and virtual mind replies: finding the mind
These
replies attempt to answer the question: since the man in the room does
not speak Chinese, where is the mind that does? These replies address
the key ontological issues of mind versus body and simulation vs. reality. All of the replies that identify the mind in the room are versions of "the system reply".
System reply
The basic version of the system reply argues that it is the "whole system" that 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.
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 does not
understand Chinese then the system does not 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. 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, 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".
Virtual mind reply
Marvin Minsky suggested a version of the system reply known as the "virtual mind reply". The term "virtual"
is used in computer science to describe an object that appears to exist
"in" a computer (or computer network) only because software makes 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 proposes that 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," thus the "system" cannot be the "mind".
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, where a perfect simulation of the
thing just is the thing? Or is the mind like the rainstorm, a
thing in the world that is more than just its simulation, and not
realizable in full by a computer simulation? For decades, this question
of simulation has led AI researchers and philosophers to consider
whether the term "synthetic intelligence" is more appropriate than the common description of such intelligences as "artificial."
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 cannot argue
that (1) the man does not 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.
These replies, by themselves, do not provide any evidence that
strong AI is true, however. They do not show that the system (or the
virtual mind) understands Chinese, other than the hypothetical premise
that it passes the Turing test. Searle argues that, if we are to
consider Strong AI remotely plausible, the Chinese Room is an example
that requires explanation, and it is difficult or impossible to explain
how consciousness might "emerge" from the room or how the system would
have consciousness. As Searle writes "the systems reply simply begs the
question by insisting that the system must understand Chinese" and thus is dodging the question or hopelessly circular.
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 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.
Robot reply
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."
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."
Derived meaning
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 are 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, like a book, has no understanding of its
own.
Contextualist reply
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.
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.
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 identify some special
technology that would create conscious understanding in a machine. (The
"robot" and "commonsense knowledge" replies above also specify a
certain kind of system as being important.)
Brain simulator reply
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 does not reproduce the
important features of the brain—its causal and intentional states. He is
adamant that "human mental phenomena [are] dependent on actual
physical–chemical properties of actual human brains." 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 does not
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.
China brain
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. It is also obvious that this system would be functionally equivalent to
a brain, so if consciousness is a function, this system would be
conscious.
Brain replacement scenario
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.(See Ship of Theseus for a similar thought experiment.)
Connectionist replies
Closely
related to the brain simulator reply, this claims that a massively
parallel connectionist architecture would be capable of understanding. Modern deep learning is parallel and has displayed intelligent behavior in multiple domains. Nils Nilsson argues that modern AI is using digitized "dynamic signals" rather than symbols of the kind used by AI in 1980. Here it is the sampled
signal which would have the semantics, not the individual numbers
manipulated by the program. This is a different kind of machine than the
one that Searle visualized.
Combination reply
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.
Many mansions / wait till next year reply
Better technology in the future will allow computers to understand. Searle agrees that this is possible, but considers this point
irrelevant. Searle agrees that there may be other hardware besides
brains that have conscious understanding.
These arguments (and the robot or common-sense 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 cannot 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 argument 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.[ae] 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 overly
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 do not
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."
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. 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. 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.
Speed and complexity replies
Many of these critiques emphasize speed and complexity of the human brain, which processes information at 100 billion operations per second (by some estimates). 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: "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!" Churchland's point is that 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.
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.
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." The replies below 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), the
epiphenoma replies question whether we can make any argument at all
about something like consciousness which can not, by definition, be
detected by any experiment, and the eliminative materialist reply argues
that Searle's own personal consciousness does not "exist" in the sense
that Searle thinks it does.
Other minds reply
The "Other Minds 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."
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 does not intend
to solve the problem of other minds (for machines or people) and he
does not think we need to.
Replies considering that Searle's "consciousness" is undetectable
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" i.e. is undetectable in the outside world.
Searle's "causal properties" cannot be detected by anyone outside the
mind, otherwise the Chinese Room could not pass the Turing test—the
people outside would be able to tell there was not a Chinese speaker in
the room by detecting their causal properties. Since they cannot detect
causal properties, they cannot detect the existence of the mental. Thus,
Searle's "causal properties" and consciousness itself is undetectable,
and anything that cannot be detected either does not exist or does not
matter.
Mike Alder calls this the "Newton's Flaming Laser Sword Reply". He argues that the entire argument is frivolous, because it is non-verificationist: not only is the distinction between simulating a mind and having
a mind ill-defined, but it is also irrelevant because no experiments
were, or even can be, proposed to distinguish between the two.
Daniel Dennett provides this illustration: 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 is a philosophical zombie, as formulated 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 is most likely that human beings (as we see them today) are actually
"zombies", who nevertheless insist they are conscious. It is impossible
to know whether we are all zombies or not. Even if we are all zombies,
we would still believe that we are not.
Eliminative materialist reply
Several philosophers argue that consciousness, as Searle describes it, does not exist. Daniel Dennett describes consciousness as a "user illusion".
This position is sometimes referred to as eliminative materialism:
the view that consciousness is not a concept that can "enjoy reduction"
to a strictly mechanical description, but rather is a concept that will
be simply eliminated once the way the material brain works is fully understood, in just the same way as the concept of a demon
has already been eliminated from science rather than enjoying reduction
to a strictly mechanical description. Other mental properties, such as
original intentionality (also called "meaning", "content", and "semantic
character"), are also commonly regarded as special properties related
to beliefs and other propositional attitudes. Eliminative materialism
maintains that propositional attitudes such as beliefs and desires,
among other intentional mental states that have content, do not exist.
If eliminative materialism is the correct scientific account of human
cognition then the assumption of the Chinese room argument that "minds
have mental contents (semantics)" must be rejected.
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.
Other replies
Margaret Boden
argued in her paper "Escaping from the Chinese Room" that even if the
person in the room does not understand the Chinese, it does not mean
there is no understanding in the room. The person in the room at least
understands the rule book used to provide output responses. She then
points out that the same applies to machine languages: a natural
language sentence is understood by the programming language code that
instantiates it, which in turn is understood by the lower-level compiler
code, and so on. This implies that the distinction between syntax and
semantics is not fixed, as Searle presupposes, but relative: the
semantics of natural language is realized in the syntax of programming
language; the semantics of programming language has a semantics that is
realized in the syntax of compiler code. Boden argues that there are
different degrees of understanding and that it is not a binary notion.
Carbon chauvinism
Searle's conclusion that "human mental phenomena [are] dependent on actual physical–chemical properties of actual human brains" has sometimes been described as a form of "carbon chauvinism". Steven Pinker
suggested that a response to that conclusion would be to make a counter
thought experiment to the Chinese Room, where the incredulity goes the
other way. He brings as an example the short story They're Made Out of Meat
which depicts an alien race composed of some electronic beings, who
upon finding Earth express disbelief that the meat brains of humans can
experience consciousness and thought.
However, Searle himself denied being carbon chauvinist. He said "I have not tried to show that only biological based systems
like our brains can think ... I regard this issue as up for grabs". He said that even silicon machines could theoretically have human-like
consciousness and thought, if the actual physical–chemical properties of
silicon could be used in a way that produces consciousness and thought,
but "until we know how the brain does it we are not in a position to
try to do it artificially".
Fanaticism is a belief or behavior involving uncritical zeal or an obsessiveenthusiasm.
The political theorist Zachary R. Goldsmith provides a "cluster
account" of the concept of fanaticism, identifying ten main attributes
that, in various combinations, constitute it: messianism, inappropriate relationship to reason (irrationality), an embrace of abstraction, a desire for novelty, the pursuit of perfection, an opposition to limits, the embrace of violence, absolute certitude, excessive passion, and an attractiveness to intellectuals.
Definitions
Etienne-Pierre-Adrien Gois, Voltaire defending Innocence against Fanaticism, c. 1791
Philosopher George Santayana defines fanaticism as "redoubling your effort when you have forgotten your aim". The fanatic displays very strict standards and little tolerance for
contrary ideas or opinions. Tõnu Lehtsaar has defined the term fanaticism as the pursuit or defence of something in an extreme and passionate way that goes beyond normality. Religious fanaticism is defined by blind faith, the persecution of dissidents and the absence of reality.
Fanaticism is a result from multiple cultures interacting with one another. Fanaticism occurs most frequently when a leader makes minor variations
on already existing beliefs, which then drives the followers into a
frenzy. In this case, fanaticism is used as an adjective describing the
nature of certain behaviors that people recognize as cult-like. Margaret Mead referred to the style of defense used when the followers are approached. The most consistent thing presented is the priming, or preexisting,
conditions and mind state needed to induce fanatical behavior. Each
behavior is obvious once it is pointed out; a closed mind, no interest
in debating the subject of worship, and over reaction to people who do
not believe.
In his book Crazy Talk, Stupid Talk, Neil Postman
states that "the key to all fanatical beliefs is that they are
self-confirming....(some beliefs are) fanatical not because they are
'false', but because they are expressed in such a way that they can
never be shown to be false."
Similar behaviors
The
behavior of a fan with overwhelming enthusiasm for a given subject is
differentiated from the behavior of a fanatic by the fanatic's violation
of prevailing social norms. Though the fan's behavior may be judged as odd or eccentric, it does not violate such norms. A fanatic differs from a crank,
in that a crank is defined as a person who holds a position or opinion
which is so far from the norm as to appear ludicrous and/or probably
wrong, such as a belief in a Flat Earth.
In contrast, the subject of the fanatic's obsession may be "normal",
such as an interest in religion or politics, except that the scale of
the person's involvement, devotion, or obsession with the activity or
cause is abnormal or disproportionate to the average.
Types
Consumer fanaticism – the level of involvement or interest one has in the liking of a particular person, group, trend, artwork or idea
Sports
fanaticism – high levels of intensity surrounding sporting events. This
is either done based on the belief that extreme fanaticism can alter
games for one's favorite team (Ex: Knight Krew), or because the person uses sports activities as an ultra-masculine "proving ground" for brawls, as in the case of football hooliganism.
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