The case for an ambitious new particle accelerator to be built in the United States has just gotten a major boost.
Today, the National Academies of Sciences, Engineering, and
Medicine have endorsed the development of the Electron Ion Collider, or
EIC. The proposed facility, consisting of two intersecting accelerators,
would smash together beams of protons and electrons traveling at nearly
the speed of light. In the aftermath of each collision, scientists
should see “snapshots” of the particles’ inner structures, much like a
CT scan for atoms. From these images, scientists hope to piece together a
multidimensional picture, with unprecedented depth and clarity, of the
quarks and gluons that bind together protons and all the visible matter
in the universe.
The EIC, if built, would significantly advance the field of
quantum chromodynamics, which seeks to answer fundamental questions in
physics, such as how quarks and gluons produce the strong force — the
“glue” that holds all matter together. If constructed, the EIC would be
the largest accelerator facility in the U.S. and, worldwide, second only
to the Large Hadron Collider at CERN. MIT physicists, including Richard
Milner, professor of physics at MIT, have been involved from the
beginning in making the case for the EIC.
MIT News checked in with Milner, a member of the Laboratory for
Nuclear Science, about the need for a new particle collider and its
prospects going forward.
Q: Tell us a bit about the history of this design. What has it taken to make the case for this new particle accelerator?
A: The development of both the scientific and
technical case for the EIC has been in progress for about two decades.
With the development of quantum chromodynamics (QCD) in the 1970s by MIT
physics Professor Frank Wilczek and others, nuclear physicists have
long sought to bridge the gap between QCD and the successful theory of
nuclei based on experimentally observable particles, where the
fundamental constituents are the undetectable quarks and gluons.
A high-energy collider with the ability to collide electrons with the
full range of nuclei at high rates and to have the electrons and
nucleons polarized was identified as the essential tool to construct
this bridge. High-energy electron scattering from the proton was how
quarks were experimentally discovered at SLAC
in the late 1960s (by MIT physics faculty Henry Kendall and Jerome
Friedman and colleagues), and it is the accepted technique to directly
probe the fundamental quark and gluon structure of matter.
Significant initial impetus for the EIC came from nuclear physicists
at the university user-facilities at the University of Indiana and MIT
as well as from physicists seeking to understand the origin of the
proton’s spin, at laboratories and universities in the U.S. and Europe.
Over the last three long-range planning exercises by U.S. nuclear
physicists in 2002, 2007, and 2015, the case for the EIC has matured and
strengthened. After the 2007 exercise, the two U.S. flagship nuclear
facilities, namely the Relativistic Heavy Ion Collider at Brookhaven
National Laboratory and the Continuous Electron Beam Accelerator
Facility at Jefferson Laboratory, took a leadership role in coordinating
EIC activities across the broad U.S. QCD community. This led to the
production in 2012 of a succinct summary of the science case,
“Electron-Ion Collider: The Next QCD Frontier (Understanding the glue
that binds us all).”
The 2015 planning exercise established the EIC as the highest
priority for new facility construction in U.S. nuclear physics after
present commitments are fulfilled. This led to the formation of a
committee by the U.S. National Academy of Sciences (NAS) to assess the
EIC science case. The NAS committee deliberated for about a year and the
report has been publicly released this month.
Q: Give us an idea of how powerful this new collider
will be and what kind of new interactions it will produce. What kinds
of phenomena will it help to explain?
A: The EIC will be a powerful and unique new
accelerator that will offer an unprecedented window into the fundamental
structure of matter. The electron-ion collision rate at the EIC will be
high, more than two orders of magnitude greater than was possible at
the only previous electron-proton collider, namely HERA, which operated
at the DESY laboratory in Hamburg, Germany, from 1992 to 2007. With the
EIC, physicists will be able to image the virtual quarks and gluons
that make up protons, neutrons, and nuclei, with unprecedented spatial
resolution and shutter speed. A goal is to provide images of the
fundamental structure of the microcosm that can be appreciated broadly
by humanity: to answer questions such as, what does a proton look like?
And what does a nucleus look like?
There are three central scientific issues that can be addressed by an
electron-ion collider. The first goal is to understand in detail the
mechanisms within QCD by which the mass of protons and neutrons, and
thus the mass of all the visible matter in the universe, is generated.
The problem is that while gluons have no mass, and quarks are nearly
massless, the protons and neutrons that contain them are heavy, making
up most of the visible mass of the universe. The total mass of a nucleon
is some 100 times greater than the mass of the various quarks it
contains.
The second issue is to understand the origin of the intrinsic angular
momentum, or spin, of nucleons, a fundamental property that underlies
many practical applications, including magnetic resonance imaging (MRI).
How the angular momentum, both intrinsic as well as orbital, of the
internal quarks and gluons gives rise to the known nucleon spin is not
understood. And thirdly, the nature of gluons in matter — that is, their
arrangements or states — and the details of how they hold matter
together, is not well-known. Gluons in matter are a little like dark
matter in the universe: unseen but playing a crucial role. An
electron-ion collider would potentially reveal new states resulting from
the close packing of many gluons within nucleons and nuclei. These
issues are fundamental to our understanding of the matter in the
universe.
Q: What role will MIT have in this project going forward?
A: At present, more than a dozen MIT physics
department faculty lead research groups in the Laboratory for Nuclear
Science that work directly on understanding the fundamental structure of
matter as described by QCD. It is the largest university-based group in
the U.S. working on QCD. Theoretical research is focused at the Center
for Theoretical Physics, and experimentalists rely heavily on the Bates
Research and Engineering Center for technical support.
MIT theorists are carrying out important calculations using the
world’s most powerful computers to understand fundamental aspects of
QCD. MIT experimental physicists are conducting experiments at existing
facilities, such as BNL, CERN, and Jefferson Laboratory, to reach new
insight and to develop new techniques that will be used at the EIC.
Further, R&D into new polarized sources, detectors, and innovative
data-acquisition schemes by MIT scientists and engineers is in progress.
It is anticipated that these efforts will ramp up as the realization of
the EIC approaches.
It is anticipated that the U.S. Department of Energy Office of
Science will initiate in the near future the official process for EIC by
which the U.S. government approves, funds, and constructs new, large
scientific facilities. Critical issues are the selection of the site for
EIC and the participation of international users. An EIC user group has
formed with the participation of more than 700 PhD scientists from over
160 laboratories and universities around the world. If the realization
of EIC follows a schedule comparable to that of past large facilities,
it should be doing science by about 2030. MIT has a long history of
providing leadership in U.S. nuclear physics and will continue to play a
significant role as we proceed along the path to EIC.
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 argument is directed against the philosophical positions of functionalism and computationalism,[3]
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:
The appropriately programmed computer with the right
inputs and outputs would thereby have a mind in exactly the same sense
human beings have minds.[b]
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.[4] The argument applies only to digital computers running programs and does not apply to machines in general.[5]
Chinese room thought experiment
John Searle
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.
The question Searle wants to answer is this: does the machine literally "understand" Chinese? Or is it merely simulating the ability to understand Chinese?[6][c] Searle calls the first position "strong AI" and the latter "weak AI".[d]
Searle then supposes that he is in a closed room and has a book
with an English version of the computer program, along with sufficient
paper, pencils, erasers, and filing cabinets. Searle could receive
Chinese characters through a slot in the door, process them according to
the program's instructions, and produce Chinese characters as output.
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
as demonstrating intelligent conversation. However, Searle would not be
able to understand the conversation. ("I don't speak a word of
Chinese,"[9] 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.
History
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.[10]
Leibniz found it difficult to imagine that a "mind" capable of
"perception" could be constructed using only mechanical processes.[e] 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".[11]
The Chinese Room Argument was introduced in Searle's 1980 paper "Minds, Brains, and Programs", published in Behavioral and Brain Sciences.[12] It eventually became the journal's "most influential target article",[1]
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".[13]
Most of the discussion consists of attempts to refute it. "The overwhelming majority," notes BBS editor Stevan Harnad,[f] "still think that the Chinese Room Argument is dead wrong."[14] 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".[15]
Searle's argument has become "something of a classic in cognitive science," according to Harnad.[14]Varol Akman agrees, and has described the original paper as "an exemplar of philosophical clarity and purity".[16]
The appropriately programmed computer with the right
inputs and outputs would thereby have a mind in exactly the same sense
human beings have minds.[b]
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."[7]
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"[22][h] and claimed that they had "solved the venerable mind–body problem, explaining how a system composed of matter can have the properties of mind."[23]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."[24]
Searle also ascribes the following positions to advocates of strong AI:
The study of the brain is irrelevant to the study of the mind;[i] and
The Turing test is adequate for establishing the existence of mental states.[j]
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).[3][29] 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."[30]Computationalism[k] 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:[33]
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.
Strong AI vs. biological naturalism
Searle holds a philosophical position he calls "biological naturalism": that consciousness[a] and understanding require specific biological machinery that are found in brains. He writes "brains cause minds"[5] and that "actual human mental phenomena [are] dependent on actual physical–chemical properties of actual human brains".[34] 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.[35] Searle's faith in the existence of these powers has been criticized.[l]
Searle does not disagree with the notion that machines can have
consciousness and understanding, because, as he writes, "we are
precisely such machines".[5]
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").[36] 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.[37][m] Searle's biological naturalism and strong AI are both opposed to Cartesian dualism,[36]
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."[25]
Consciousness
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.[3]
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.[38]
— 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.[39]
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.[40]
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.[41]
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.[4] 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. 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."[4] 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. Indeed, Searle writes that "the Chinese room argument ... assumes
complete success on the part of artificial intelligence in simulating
human cognition."[42]
Searle's "strong AI" should not be confused with "strong AI" as defined by Ray Kurzweil and other futurists,[43]
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.
Turing test
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, 2000.[44]
The Chinese room implements a version of the Turing test.[45]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.[45]
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 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."[46][47]
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.
Chinese room and Turing completeness
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."[48] 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)"[49] of the Chinese room argument, because these arguments actually imply that no digital computers can have a mind.[27]
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.[50]
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.[51][n]
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.[o]
A program uses syntax to manipulate symbols and pays no attention to the semantics
of the symbols. It knows where to put the symbols and how to move them
around, but it doesn't know what they stand for or what they mean. For
the program, the symbols are just physical objects like any others.
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?[g] 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"[35] 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.
Replies
Replies to Searle's argument may be classified according to what they claim to show:[p]
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 doesn't speak Chinese, where is the "mind" that does? These replies address the key ontological issues of mind vs. body and simulation vs. reality. All of the replies that identify the mind in the room are versions of "the system reply".
System reply
The basic "systems reply" argues that it is the "whole system" that understands Chinese.[56][q]
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.[28] The fact that man does not understand Chinese is irrelevant, because it is only the system as a whole that matters.
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"[28]
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;"[28]
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.[28]
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).[58]
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.[59] 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).
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 argues, a computer may contain a "mind" that is virtual in the same sense as virtual machines, virtual communities and virtual reality.[r]
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".[63]
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."[64]
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."[65]
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.[s]
However, the replies, by themselves, do not prove that strong AI is true, either: they provide no evidence that the system (or the virtual mind) understands Chinese, other than the hypothetical premise that it passes the Turing Test. As Searle writes "the systems reply simply begs the question by insisting that system must understand Chinese."[28]
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.[67][t]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."[69][u]
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."[71] (See Mary's room for a similar thought experiment.)
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're just not meaningful to him.[72][v]
Searle says that the symbols only have a "derived" meaning, like
the meaning of words in books. The meaning of the symbols depends on
the conscious understanding of the Chinese speakers and the programmers
outside the room. The room, according to Searle, has no understanding of
its own.[w]
Commonsense knowledge / 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.[70][x]
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.[75]
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."[76][y]
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. (Note that 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.[78][z]
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. Searle is adamant that "human mental phenomena [are] dependent on actual physical–chemical properties of actual human brains."[25] Moreover, he argues:
[I]magine that instead of a monolingual man in a room
shuffling symbols we have the man operate an elaborate set of water
pipes with valves connecting them. When the man receives the Chinese
symbols, he looks up in the program, written in English, which valves he
has to turn on and off. Each water connection corresponds to a synapse
in the Chinese brain, and the whole system is rigged up so that after
doing all the right firings, that is after turning on all the right
faucets, the Chinese answers pop out at the output end of the series of
pipes.
Now where is the understanding in this system? It takes Chinese as
input, it simulates the formal structure of the synapses of the Chinese
brain, and it gives Chinese as output. But the man certainly doesn't
understand Chinese, and neither do the water pipes, and if we are
tempted to adopt what I think is the absurd view that somehow the
conjunction of man and water pipes understands, remember that in
principle the man can internalize the formal structure of the water
pipes and do all the "neuron firings" in his imagination.[12]
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.[80][aa]
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.[82][ab]
Searle predicts that, while going through the brain prosthesis, "you
find, to your total amazement, that you are indeed losing control of
your external behavior. You find, for example, that when doctors test
your vision, you hear them say 'We are holding up a red object in front
of you; please tell us what you see.' You want to cry out 'I can't see
anything. I'm going totally blind.' But you hear your voice saying in a
way that is completely outside of your control, 'I see a red object in
front of me.' [...] [Y]our conscious experience slowly shrinks to
nothing, while your externally observable behavior remains the same."[84] (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.[ac]
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.[87]
Many mansions/Wait till next year reply
Better technology in the future will allow computers to understand.[26][ad]
Searle agrees that this is possible, but considers this point
irrelevant. His argument is that a machine using a program to manipulate
formally defined elements can't produce understanding. Searle's
argument, if correct, rules out only this particular design. Searle
agrees that there may be other designs that would cause a machine to
have conscious understanding.
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.[ae]
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."[26] 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[88] 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.[af] 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."[9]
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. Ned Block writes "Searle's argument depends for its force on intuitions that certain entities do not think."[89]Daniel Dennett describes the Chinese room argument as a misleading "intuition pump"[90]
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."[90]
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.[74]
Speed and complexity replies
The speed at which human brains process information is (by some estimates) 100 billion operations per second.[91]
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.[92][ag]
An especially vivid version of the speed and complexity reply is from Paul and Patricia Churchland. They propose this analogous thought experiment:
Churchland's luminous room
"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!"[81]
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.[94]
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.')"[95][ah]
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".[28]
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."[98] 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.
Other minds reply
This reply points out that Searle's argument is a version of the problem of other minds,
applied to machines. There is no way we can determine if other people's
subjective experience is the same as our own. We can only study their
behavior (i.e., by giving them our own Turing test). Critics of Searle argue that he is holding the Chinese room to a higher standard than we would hold an ordinary person.[99][ai]
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."[101]
Alan Turing
anticipated Searle's line of argument (which he called "The Argument
from Consciousness") in 1950 and makes the other minds reply.[102]
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."[103] 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.[aj]
Epiphenomenon / zombie reply
Several philosophers argue that consciousness, as Searle describes
it, does not exist. This position is sometimes referred to as eliminative materialism:
the view that consciousness is a property that can be reduced to a
strictly mechanical description, and that our experience of
consciousness is, as Daniel Dennett describes it, a "user illusion".[106]
Stuart Russell and Peter Norvig
argue that, if we accept Searle's description of intentionality,
consciousness and the mind, we are forced to accept that consciousness
is epiphenomenal:
that it "casts no shadow", that it is undetectable in the outside
world. They argue that Searle must be mistaken about the "knowability of
the mental", and in his belief that there are "causal properties" in
our neurons that give rise to the mind. They point out that, by Searle's
own description, these causal properties can't be detected by anyone
outside the mind, otherwise the Chinese Room couldn't pass the Turing test—the
people outside would be able to tell there wasn't a Chinese speaker in
the room by detecting their causal properties. Since they can't detect
causal properties, they can't detect the existence of the mental. In
short, Searle's "causal properties" and consciousness itself is
undetectable, and anything that cannot be detected either does not exist
or does not matter.[107]
Daniel Dennett provides this extension to the "epiphenomena" argument.
Dennett's reply from natural selection
Suppose that, by some mutation, a human being is born that does not
have Searle's "causal properties" but nevertheless acts exactly like a
human being. (This sort of animal is called a "zombie" in thought experiments in the philosophy of mind).
This new animal would reproduce just as any other human and eventually
there would be more of these zombies. Natural selection would favor the
zombies, since their design is (we could suppose) a bit simpler.
Eventually the humans would die out. So therefore, if Searle is right,
it 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.[108]
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."[71] He takes it as obvious that we can detect the presence of consciousness and dismisses these replies as being off the point.
Mike Alder argues that the entire argument is frivolous, because it is non-positivist: 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.[109]
In popular culture
The Chinese room argument is a central concept in Peter Watts's novels Blindsight and (to a lesser extent) Echopraxia. It is also a central theme in the video game Virtue's Last Reward, and ties into the game's narrative. In Season 4 of the American crime drama Numb3rs there is a brief reference to the Chinese room.[citation needed]
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