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Is the Chinese Gym Arguments Convincing Argumentative Essay

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I’m studying and need help with a Writing question to help me learn.

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.

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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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Hi, please see the attached paper. Have a look at it and in case of any edit, please let me know. Otherwise, it is my pleasure to have you as my buddy now and future. Until the next invite, Bye!

Running Head: ARGUMENTATIVE ESSAY

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Argumentative Essay
Name
Institution
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ARGUMENTATIVE ESSAY

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Argumentative Essay

Several questions have been lingering on the minds of scholars and researchers on the
issue of artificial intelligence ever since its inception. The ultimate goal would be to create superintelligent machines, which means that they would have the ability to think and use emotions.
This brings in the most common question, can machines ever think? Before delving into this, it is
essential to understand the meaning of the term ‘think.' This is the process of reasoning about
something.
Some people argue that machines do not have consciousness; neither do they have
emotions; therefore, they have limited ability to think. They can only use that which has been
thought out for them by human beings and programmed into them. This perspective is in line
with John Searle’s Chinese room argument, which ...

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Boston College

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