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Transcript
AI ESSAY CONTEST THIRD PLACE CAN MACHINES THINK? MORGAN COHEN ‘08 Great minds have struggled for centuries to explain the origin and nature of knowledge. The rise of computers has compounded this great philosophical dilemma as we now must struggle to reconcile the advancements of technology with the hitherto accepted assumptions about the relationship of man to the universe. Traditionally, we have considered our ability to think as the defining difference between mankind and all other beings. Indeed, thought has long been cited as the hallmark quality of man. In deciding whether or not a computer can think, we are reevaluating one of the most distinctive features of our humanity. Before we can determine whether or not computers are capable of thought, we must first dispel the equivocation and ambiguity that obscures the meaning of the word thought itself, specifically the notion that consciousness and thought are mutually inclusive. Once the word thought has been thoroughly disambiguated, we will examine the test devised by Alan Turing used to test for thought in computers. Finally, we will look at the structure of the main objection to the Turing Test and the effect it has on the question at hand. Any attempt to answer the question “Can machines think?” must begin with the definition of thought itself. It is a common enough assumption that only conscious beings can think, and it would therefore seem that computers - composed of plastic, metal, and wires – could never achieve consciousness, and thus, never achieve thought. This assumption is patently false. It is widely accepted amongst psychologists, Freudian and non-Freudian alike, that we are not consciously aware of all, or even most of our thought processes. This notion of subconscious mental activity is reinforced by the concept of speech. We almost always find ourselves saying what we want to say without consciously choosing the words. When engaging in any form of conversation, we are not conscious of the thought processes that transform the sounds we hear into the meaning attached to the words that have been spoken. SPRING 2006 Thought and consciousness are not mutually inclusive, realizing this allows us to consider the question of artificial intelligence within a much more precise framework. Those who hold that the terms “thinking” and “consciously thinking” can be used interchangeably are merely equivocating thinking with being aware that one is thinking. Many fundamental human mental activities, from the understanding of speech to the perception of the external world can be performed non-consciously. The real question is whether an inanimate object (such as a computer) could be said to perform these cognitive activities; and since we can perform these activities non-consciously, the question can be discussed without considering whether or not the object could be conscious. The answer to this new question is a resounding yes, but the problem of how to test and recognize this new disambiguated definition of thought still remains. The new problem can be resolved by the laboratory experiment devised by Alan Turing. The experiment, which can be used to settle the question of whether a given computer is capable of thought is known simply as the Turing Test. The Test, also known as The Imitation Game supposes that we have a person, a computer, and an interrogator. The interrogator is in a room separated from the other person and the computer. The objective of the test is for the interrogator to determine through conversation which of the other two is the person and which is the computer. The interrogator converses with the computer and the other human by means of a keyboard and screen and is allowed to ask as penetrating and wide-ranging questions as he or she likes. The object of the computer is to try and cause the interrogator to mistakenly conclude that the computer is the other person, while the object of the other person is to try and help the interrogator expose the computer. The experiment is then repeated a number of times with a wide range of people in the two human positions, and if the number of successful identifications is not significantly higher than 15 “guessing frequency” – which in the case of the Turing Test is fifty percent – we can conclude that the computer in question can think. The Turing Test is predicated upon the underlying assumption that if a computer can convince a computer expert that it has mental states, then it really has those mental states. If, for example, a machine could “converse” with a native English speaker in such a way as to convince the speaker that it understood English then it would literally understand English (1). If trees could converse with us as fluently as they do in some fairy tales, wouldn’t we unhesitatingly say that trees can think? The question and answer format presented by the Turing Test allows for almost any human mental process – from mathematics, to poetry, to chess - to be tested and searched for in a computer. The notion that language is the hallmark quality of thought has a long philosophical history. The French philosopher Rene Descartes ironically believed that conversation was the surest way of differentiating a genuine thinking being from a machine. He wrote that it is “not conceivable that such a machine should produce different arrangements of words so as to give an appropriately meaningful answer to whatever is said in its presence, as the dullest of men can do.” This statement seems anachronistic in light of the technological achievements of the computer age, where computers now can respond not only textually, but also audibly to a wide-range of questions. If Descartes’ notion of thought – the “appropriately meaningful answer to whatever is said” – is held to be true, then the Turing Test is an accurate way to evaluate whether or not a computer is capable of thought. So far, we have reshaped and disambiguated our notion of thought, and concluded that the Turing Test is an appropriate way to inductively suggest whether computers can think. However, the Turing Test, and the definition of thought that engenders it are not beyond reproach. We must now consider the main objections to these theories, the most prominent of which is the simulation objection. The objection centers on the belief that simulation does not constitute reality. Artificially created coal is not really coal just as simulated diamonds are not really diamonds. A simulated X is X-like, but it is not the original. Should a computer pass the Turing Test, it would 16 only demonstrate its ability to simulate thought, which, proponents of the simulation objection argue, is very different actually possessing the capability of thought. The difference lies in the fact that computers, by definition, consist of sets of purely formalized operations on formally specified symbols. As far as the computer is concerned, these symbols don’t symbolize anything or represent anything. Not only does the computer attach no meaning, interpretation, or content to these formal symbols, but any attempt to endow a computer with the power to interpret its symbols would only result in more uninterpreted symbols. If, for example, I were to print on a calculator “4 X 4 =,” the calculator would print “16,” but it has no idea that “4” means “4” or that “16” means “16” or that anything means anything. The computer only manipulates the formal symbols that is has been programmed with but attaches no meaning to them. This simple observation is intended to refute the possibility that computers are capable of thought, but it is riddled with ambiguity and equivocation. Primarily, it is false to assert that a simulated X is never X. Consider voice simulation. If a computer can produce a voice identical to a human voice, would this not be considered a voice? Granted, it is an artificial voice as opposed to a human voice, but it is still a voice nonetheless. Similarly, organic compounds produced in a laboratory were not created naturally, but are they not still organic compounds? A comparison of these examples with the case of simulated death, for instance, makes clear the equivocation that surrounds the word “simulation,”(2) Indeed, there are two very different grounds for classifying something as a simulation. The first type of simulation, which we shall call simulation A, occurs if a simulation lacks the essential feature of whatever is being simulated. Therefore, a simulated death is a simulation A because the person involved in the simulation is still living. The second form of simulation, or simulation B, is identical in every way to whatever is being simulated except for the fact that it has been produced by non-standard means. Coal produced artificially in a laboratory may still be called simulated coal even though it is identical in appearance and composition to naturally coal. The same is true for the aforementioned artificial voice, which contains DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE all the essential characteristics of human voice but is artificially produced. The main flaw of the simulation objective is now apparent. The objection assumes, without cause, that a computer simulation of thought must always be a mere simulation and never the real thing - always simulation A and never simulation B - no matter how accurate the simulation has become. However, the main question we specifically ask concerning the possibility of “thinking machines” is whether a computer simulation of thinking could be a simulation B. Therefore, by assuming that the purpose of the Turing Test is to examine whether a computer can produce a simulation A of thought, the simulation objection simply pre-judges the central issue and is thus irrelevant. Our concept of thinking beings was shaped by an environment in which only naturally occurring, living organisms were capable of thought. Now, in the face of computers that are indistinguishable from humans in their ability to solve problems, understand concepts, make decisions, and so on, we must choose whether or not their nature warrants the application of the term “thinking thing.” Much as a judge consults the intention behind the laws when he issues his verdict, we must look to the purpose for which we use the concept of thinking and decide if it is best served by counting a computer as a thinking thing. Thus, the concept of thought is crucial in making a distinction between objects that think and those that do not. Intrinsic to the notion of thought are highly adaptable mental processes that allow thinking things to reason, develop analogies, deliberate, and revise beliefs in light of experience. All we must consider now is whether the mental processes of the properly programmed computer more or less match ours in adaptability. Currently, such massively adaptive programs do not exist in the programming lexicon. If we assume that AI researches will one day succeed in achieving this auspicious feat, it would become extremely difficult to say that computers are not capable of thought. These highly adaptive computers would display the same purposefulness and ingenuity that we do, and more importantly, their behavior would be the result of their programs engaging in what we refer to (when biologically rooted of course) as reasoning, analyzing, making informed guesses, and forming plans. As long as we are willing to describe these acts in the same manner that we describe them when referring to our own adaptable mental process, we can and must conclude that it will be possible for computers to think. References 1. Robert J. Fogelin & Walter Sinnott-Armstrong, Understanding Arguments, pg. 591 2. Brian Copeland, Artificial Intelligence: A Philosophical Introduction, pg. 47 Congratulations to our contest winners and thanks to all who partcipated. For more about artificial intelligence, be sure to check out the AI@50 conference from July 13th-15th. SPRING 2006 17