Is the Chinese Gym Arguments Convincing Argumentative Essay The topic is “Is Paul and Patricia Churchland’s response to John Searle’s ‘Chinese Room’ and ‘C

Is the Chinese Gym Arguments Convincing Argumentative Essay The topic is “Is Paul and Patricia Churchland’s response to John Searle’s ‘Chinese Room’ and ‘Chinese Gym’ arguments convincing? Why or why not?”

Please use the articles I provided below to write this essay.

Thesis statement is necessary!

This essay is argumentative essay. It should has a thesis, supported by a strong argument backed by detailed evidence.

Please only use in-text citations from articles I provided to you, do not use any other references from website.

(You must use an in-text citation when you quote another author directly, i.e., when you include their words in your paper. Whenever you do this, you must enclose their words in quotation marks (“Like this”) and include a proper in-text citation.) 154 of 251
Week 8 – Reading 1 of 1
Hubert Dreyfus. (1974). “Artificial Intelligence,” The Annals of the American
Academy of Political and Social Science 412: 21-33.
155 of 251
Artificial
Intelligence
By HUBERT L. DREYFUS
ABSTRACT: The belief in the
possibility of artificial
intelligence (AI), given present computers, is the belief that
all that is essential to human intelligence can be formalized.
AI has not fulfilled early expectations in pattern recognition
and problem solving. These tasks cannot be formalized.
They necessarily involve a nonformal form of information
processing which is possible only for embodied beings
—where being embodied does not merely mean being able to
move and to operate manipulators. The human world, with its
recognizable objects, is organized by human beings using
their embodied capacities to satisfy their embodied needs.
There is no reason to suppose that a world organized in terms
of the body should be accessible by other means.
Hubert L. Dreyfus, a graduate of Harvard University, is Professor of Philosophy at
the University of California, Berkeley and has also taught at Harvard, Brandeis and
the Massachusetts Institute of Technology. He pursued the question of whether or
not digital computers could be programmed to behave intelligently, first as a consultant at RAND and then, with National Science Foundation support, as a Research
Associate in Computer Sciences at the Harvard Computation Laboratory. He is
author of What Computers Can’t Do: A Critique of Artificial Reason (1972) and of
numerous
papers
on
artificial intelligence.
This article largely follows &dquo;Why Computers Must Have Bodies in Order To Be Intelligent&dquo;
(Review of Metaphysics, 40, no. 1 [September 1967]) and &dquo;Pseudo-Strides towards Artificial
Intelligence&dquo; (Theoria to Theory 2 [January 1968]). Some examples have been incorporated
from &dquo;Phenomenology and Artificial Intelligence&dquo; (in Phenomenology in America, ed. James
M. Edie [Chicago: Quadrangle Books, 1967]). Copyright’O of all these articles is with Hubert L.
Dreyfus. A more detailed analysis of the problems discussed in this article, as well as of those in
the fields of game playing and language translation, can be found in the author’s paper Alchemy
and Artificial Intelligence (RAND paper, p. 3244) and his book, What Computers Can’t Do: A
Critique of Artificial Reason (New York: Harper and Row, 1972).
21
156 of 251
22
to begin with a state- programme at present, however, remade in 1957 by H. A. mains a class C amateur.
one of the originators of the
Similarly unfulfilled predictions
have been made in the areas of
field of artificial intelligence:
and problem
It is not my aim to surprise or shock pattern recognition
However,
solving.
philosophers
you…. But the simplest way I can
summarize is to say that there are now in have interests other than being the
the world machines that think, that learn conscience of a technical field which
and that create. Moreover, their ability to has been lax in critically evaluating
do these things is going to increase its failures. What should interest us
rapidly until-in a visible future-the is the philosophical significance of
range of problems they can handle will these unexpected difficulties: what
ISimon,
mentfitting
T IS
be co-extensive with the range to which
the human mind has been applied.’
The speaker predicts that within ten
years a digital computer will be the
world’s chess champion and that
within ten years a digital computer
will discover and prove an important
mathematical theorem.
We do not have time to go into the
deliberate confusions surrounding
the supposed proof of an important
theorem. Suffice it to say that to date
no
important,
or
even
original,
underlying philosophical
assumptions lead workers in artificial intel-
ligence (AI) to interpret their apparfailures as only temporary set-
ent
backs and their modest
success as
justifying unbounded optimism?
Can these assumptions be justified?
If not, the stagnation of work in AI
would cease to be surprising and,
moreover, would give us new
reasons to question the validity of
the assumptions on which such work
is based.
All AI work is done on digital
computers because they are the only
all-purpose information processing
devices which we know how to
theorem has been proved. The
chess-playing story is also disappointing and typical: continued failure has been followed by optimistic
predictions.22 The best computer design, or even to conceive, at
present. All information with which
these computers operate must be
1. H. A. Simon and Allen Newell, “Heurisrepresented in terms of binary
tic Problem Solving: The Next Advance in
digits-that is, in terms of a series of
Research
6
Operation Research,” Operations
yes’s and no’s, of switches being
(January-February 1958), p. 7-8.
2. Allen Newell, J. C. Shaw and H. A. open or closed. The machine must
Simon, “Chess-Playing Programs and the operate on finite strings of these
Problem of Complexity,” in Computers and determinate elements as a
series of
Thought, ed. Edward A. Feigenbaum and
related
to
each
other
only by
Julian Feldman (New York: McGraw-Hill, objects
1963); Allen Newell, J. C. Shaw and H. A. rules. Thus, psychologically, the
Simon, The Processes of Creative Thinking, computer is a model of the mind as
(RAND Corporation Paper, 1958), p. 1320. conceived of by associationists-for
Norbert Wiener, “The Brain and the Ma- the elements-and intellectualists
chine,” in Dimensions of Mind, ed. Sidney
Hook (New York: Crowell-Collier, 1960); -for the rules. Both associationists
Michael Scriven, “The Compleat Robot: A and intellectualists share the tradiProlegomena to Androidology,” in Dimen- tional conception of thinking as data
I
of Mind; H. A. Simon and Peter A.
Simon, “Trial and Error Search in Solving
processing-a third-person
Difficult Problems: Evidence from the Game
of Chess,” Behavioral Science 7 (October
processor
sions
1962).
process
in which the involvement of the
plays
no
essential part.
Moreover, since all information fed
157 of 251
23
irony. Computer technology has
of bits, the belief that such machines been most successful in simulating
can be made to behave intelligently
the so-called higher rational
into such machines must be in terms
presupposes that all relevant infor-
mation about the world must be
ex-
pressible in an isolable, determinate
way.
Thus, given digital computers,
workers in AI are necessarily committed to two basic assumptions: (1)
epistemological assumption that
all intelligent behavior can be
simulated by a device whose only
mode of information processing is
that of a detached, disembodied,
objective observer; (2) the ontological assumption, related to logical
atomism, that everything essential to
intelligent behavior can in principle be understood in terms of a
determinate set of independent
elements.
In brief, the belief in the possibility of AI, given present computers, is the belief that all that is
essential to human intelligence can
be formalized. This formalist aim has
dominated philosophy since Plato,
who set the goal by limiting the real
to the intelligible and the intelligible to that which could be made fully
explicit so as to be grasped by any
rational being. Leibniz pushed this
position one step further by conceiving of a universal logical language
capable of expressing everything in
explicit terms which would permit
thinking to achieve its goal of
becoming pure manipulation of this
formalism. Digital computers and
information theory have given us the
hardware and the conceptual tools to
implement Leibniz’s vision. We are
now witnessing the last act wherein
this conception of man as essentially
rational-and rationality as essentially calculation-will either triumph or else reveal its inherent
an
inadequacies.
It has already produced
a
certain
functions-those which were once
supposed to be uniquely human.
Computers can deal brilliantly with
ideal languages and abstract logical
relations; for example, Wang’s programme has proved two hundred
theorems from Principia Mathematica in less than three minutes.
It turns out that it is the sort of
intelligence which we share with
animals, such as pattern recognition,
that has resisted machine simulation.
Simon, who was only slightly
daunted by the failures of the first
decade of AI, still felt that &dquo;machines
will be capable, within twenty years,
of doing any work that a man can
do,&dquo;3 although he admits: &dquo;Automation of a flexible central nervous system will be feasible long before
automation of a comparatively flexible sensory, manipulative, or locomotive system.&dquo;4 However, what if
the work of the central nervous system, or what if the higher, determinate, logical and detached forms of
intelligence are necessarily derived
from, and guided by, global and
involved lower forms? Then Simon’s
optimism, as well as the two assumptions underlying AI and traditional
philosophy, would be unjustified. It
is this existentialist thesis which I
shall attempt to explain and defend.
I shall consider two areas in which
work in AI has not fulfilled early
expectations: pattern recognition
and problem solving. In each,I will
try to account for the failure by
arguing that the task in question
cannot be formalized and by isolating the nonformal form of infor3. Herbert Simon, The Shape
tion for Men and Management
Harper and Row, 1965), p. 96.
4. Ibid., p. 40.
of Automa(New York:
158 of 251
24
mation
processing necessarily
in-
volved. Finally, I will try to show
that the nonformalizable form of
information processing in question
is possible only for embodied
beings-where being embodied
does not merely mean being able to
move and to operate manipulators.
PATTERN RECOGNITION
Work in pattern recognition is
characteristic of work in all areas of
AI. Some striking successes have
been achieved; yet, they are based
on techniques which for practical
reasons do not seem to be generalizable, and the important problems for
pattern recognition, such as the recognition of everyday objects or
speech, have so far proved intractable.
There are pattern recognition
programmes now in operation which
can recognize letters and numbers
printed in various type fonts, and
programmes which can be taught
to recognize the handwriting of
specific persons. These all operate
by searching for certain topological
features of the characters to be
recognized and checking these features against preset or learned
definitions of each letter in terms of
these traits. The trick is to find relevant features-that is, those which
remain genetally invariant throughout variations of size and orientation
ceed in some other way; indeed,
phenomenologists such as Aron Gurwitsch, as well as gestalt psychologists, have pointed out that our
recognition of ordinary spatial or
temporal objects does not seem to
operate by checking off a list of
isolable, neutral, specific traits. For
example, in recognizing a melody
the notes get the values they have by
being recognized as part of the
melody rather than by the melody’s
being built up out of independently
recognized notes. Likewise, in the
preception of objects there are no
neutral traits. The same hazy layer
which I would see as dust if I thought
I was confronting a wax apple might
appear as moisture if I thought I
was
seeing a fresh apple. The
significance of the details and, indeed, their very look is determined
by my perception of the whole.
The recognition of spoken language offers the most striking demonstration of this global character
of our experience. From time to time
brash predictions have been made
about mechanical secretaries into
which-or at whom-one could
speak and whose programmes would
analyze the sounds into words and
type out the results. In fact, no one
knows how to begin to make such a
versatile device. Current work has
shown that the same physical constellation of sound waves is heard as
quite different phonemes depending on the expected meaning. As
Anthony Oettinger, of the Harvard
Computation Laboratory, has put it
in a paper published by Bell
Laboratories5:
and other distortions. This approach
has been surprisingly successful
where recognition depends on a
small number of specific traits.
However, the number of traits which
can be looked up in a reasonable
The essentially discrete and invariant
amount of time is limited, and nature of the
phoneme, so evident to the
present programmes have already linguist concerned with the phonemic
reached this technological limit.
The restricted applicability of
5. Anthony Oettinger, Human Communisuch programmes suggests that cation: A Unified View (New York:
human pattern recognition may pro- McGraw-Hill, 1973).
159 of 251
25
analysis … has turned out to be most spit it out. Or, if the right noema is
unexpectedly elusive in the absence of a found fast enough, one may recover
human agent.
in time to recognize-that is, to
This leads Oettinger to the conclu- organize-the milk for what it is. Its
sion :
Perhaps …
in
in conscious
perception
as
well
scholarly analysis, the
phoneme comes after the fact, namely,
it is constructed, if at all, as a conas
…
sequence of perception not as a step
in the process of perception itself.
other characteristics-whether it is
fresh or sour, buttermilk or skimmed
milk-will then fall into place.
One might well wonder how it is
possible to avoid looking for some
neutral features to begin this process
of recognition. In fact, such a
description may seem so paradoxical
as to make us try to explain the
sentence or a melody phenomenon. away. However, we
or a perceptual object determines
must bear in mind that each meaning
the value to be assigned to the is given in a context which is already
elements.
organized and on the basis of which
Oettinger goes on reluctantly to we have certain expectations. It is
This would
meaning of a
that the total
mean
suggest these conclusions:
It may well be that an understanding of
the meaning of a sentence is a precondition for … the analysis of the sentence into phonemic components. The
possibility
is
a
frightening
one
to
face…. Yet the school boy asked to
parse a sentence proceeds neither like a
machine nor like a generative grammar,
at least there is no evidence that he does.
On the contrary, the scant evidence there
is, suggests that he works backwards,
going from meaning to structure.
The phenomenologist Edmund
Husserl argued that, in recognizing
an
object,
we
give
a
global
mean-
otherwise ining-a
determinant but determinable sensuous matter. We then proceed to
make this open global meaning more
determinate by exploring what
Husserl called its inner horizon.
This process can best be noticed
when it is breaking down. If one
reaches for a glass of water and gets
milk by mistake, on taking a sip the
first reaction is total disorientation.
One does not taste water, but one
does not taste milk, either. One has
a mouthful of what Husserl would
call pure sensuous matter-hyletic
noema-to
an
data-and, naturally,
one
wants to
also important that we sometimes do
give the wrong meaning. In these
cases the data coming in makes no
sense at all, and we have to try a new
total hypothesis.
It is hard to imagine how a
computer, which must operate on
completely determinate data according to strictly defined rules, could be
programmed to use an underdetermined expectation of the whole in
order to determine the elements of
that whole. Workers in AI might
answer: even though people do
use some sort of holistic approach
based on context which no one now
knows how to program, there is no
in
reason,
principle, why
some
alternative approach could not be
discovered which would do the same
job. One could, for example, deal
more efficiently with a large number
of specific traits, or one could
develop a sort of anticipation which,
on the basis of certain traits in the
context, would assign an object to a
class defined in terms of a large
number of traits which would then
serve as
This
hypotheses.
however, ignores a
unique feature of human pattern
recognition: our ability to recognize
answer,
160 of 251
26
is a skill
which has to be learned. Focusdividuals recognized as belong- ing, getting the right perspective
ing to the same family need have and picking out certain details,
no exactly similar traits in common. all involve coordinated actions and
We can nonetheless recognize such anticipations. As Piaget remarks,
similarities by picking out a typical &dquo;Perceptual constancy seems to be
case and introducing intermediate the product of genuine actions,
cases. This use of paradigms and which consist of actual or potential
context, rather than class definitions, movements of the glance or of the
allows our recognition of patterns to organs concerned…..&dquo;6
be open-textured in a way which is
Moreover, as Merleau-Ponty has
impossible for recognition based on pointed out, the body is able to
a specific list of traits. Oettinger is respond as a whole to its environjustified in concluding his paper ment. When the percipient acquires
on a pessimistic note: &dquo;If indeed a skill, he:
we have an ability to use a global
does not weld together individual
context without recourse to for- movements and individual stimuli but
malization
then our optimistic acquires the power to respond with a
family
resemblances where,
Wittgenstein points out, two
as
touch, but seeing, too,
in-
…
…
discrete enumerative approach is
doomed….&dquo;
How, then, do human beings
operate with wholes, the elements
of which cannot exhaustively be
specified? Husserl has no answer
beyond the assertion that we do: that
transcendental consciousness has
the wunderbar capacity for giving
certain type of solution to situations of a
certain general form. The situations may
except to say that it is frustrating;
it states a problem without proposing any solution. For further help
we must turn to the existential
flexible skill which can be brought to
bear in an indefinite number of
ways. I can feel silk with either
hand or even with my feet. As
already noted, these anticipations
need not be completely specific,
but can become more specific in
the course of examining the object.
differ widely from place to place, and the
response movements may be entrusted
sometimes to
sometimes to
one
operative organ,
another, both
situations
and responses in the various cases
having in common not so much a partial identity of elements as shared
significance.7
meanings and, thus, making possible
the perception, recognition and
Thus, an anticipation of an object
does
not arouse a single response or
of
exploration
enduring objects.
There is no way to criticize this view specific set of responses but a
phenomenologists and, in particular,
Merleau-Ponty who postulates
that it is the body which confers the
meanings discovered by Husserl.
Being prepared to feel silk, for Thus, we give a global meaning to
example, is to move or be prepared to our perceptual experience by bringmove our hand in a certain way and
ing to it a set of interdependent and
to
to have certain expectations. As in
6. Compare, J. Piaget, Psychology of
the case of the milk, if we have the
York: Humanities, 1966),
wrong expectations we experience Intelligence (New
p.
82.
confused
sensations.
only
7. Maurice Merleau-Ponty, PhenomenolIt is easiest to become aware of ogy of Perception (London: Routledge and
the role of the body in taste and Kegan Paul, 1962), p. 142.
161 of 251
underdetermined skills which experience gradually fills in and makes
more determinate.
A human perceiver, as does a
machine, needs feedback to find out
if he has successfully recognized an
object; however, there is an important difference in the feedback
involved. A machine can, at best,
make a specific set of hypotheses and
then find out if they have been
confirmed or refu…
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