Upon Examining Issues Of Mind And Thought, The Questions Of Artificial

Upon examining issues of mind and thought, the questions of artificial intelligence and its capabilities become important considerations for answering the ultimate question of what thought truly is. Computerized calculation is one of the few events that is somewhat analogous to human cognitive thought, so the extension of this current technology to more advanced future applications makes it a very interesting testing area for questions into consciousness. If one concludes that the advancement from cash registers to present day computers is a step closer to human thought, then we must concede that progressing technology will bring us closer and perhaps to the very point of true cognitive skills. The dilemma left to us philosophers and scientists is to determine when a machine has reached the point of thought, or at least to create a rough guideline. A.M. Turing proposed a test to solve this problem. Named, appropriately enough, the Turing test, it contains a controversial method of te sting called the imitation game. The idea is to put one man and one woman in two rooms and have them questioned by an interrogator in a third room. The man would try to answer questions in a way which would suggest he is a woman. The woman attempts to answer in a way to reveal the truth of the matter. If the man fools the interrogator, it is said that he can think like a woman, or, at the very least, mimic a woman's responses. This game can also be played with a computer in the male slot, trying to convince the interrogator that it is human. It would follow reason that if a computer could pass this test, it could think like a human, or at least mimic one. Perhaps the abilities showcased in the test alone would not be sufficient, but Daniel C. Dennett claims that "[t]he assumption Turing was prepared to make was that nothing could possibly pass the Turing test by winning the Imitation Game without being able to perform indefinitely many other clearly intelligent actions" (Dennett 93) . One often cited criticism of this notion is the idea of mimicry. Imagine a program that stored an almost infinite amount of information regarding sentences and grammar and was able to spit out contextualy appropriate sentences to a wide variety of inquiries. The computer has no knowledge of what the information means; it is acting much as a parrot does. Luckily for Turing, there is no shortage of responses for this claim. First of all, as Douglas Hofstadter points outs, "[t]he number of sentences you'd need to store to be able to respond in a normal way to all possible sentences in a conversation is astronomical, really unimaginable" (Hofstadter 92). The computer would also have to contain a complex microprocessor to keep up with conversation in a timely and manageable fashion. It would have to be so advanced indeed that such a microprocessor might be considered a small scale brain, sorting through symbols and their meanings to form contextually valid responses. Accordingly, if su ch a machine existed, it would pass the Turing test and validate the method of testing at the same time. If a machine was capable of mastering the context-sensitive language we use, it may very well have a claim to true thought. At the very least, the computer would surpass mimicry and be labeled a simulation. Human thought is so complicated and demanding that any device that attempts to duplicate it with any success would have to be a highly sensitive simulation. Any machine that passes the Turing test must have a rudimentary "knowledge" of the information it is using and therefore is more than parrot . Assuming this is true, we must then ask hard questions about the value of simulation. The critical claim is that any simulation is just a simulation and not a real example of what it is simulating. Hofstadter finds this fallacious, as do I. First, any simulation can reasonable defined in this context as the recreation of a natural event by an agent other than nature. This view bring s up the idea of levels in simulation. A good example is Dennett's simulated hurricane in Brainstorms. From the programmer's vantage point, the God Upon Examining Issues Of Mind And Thought, The Questions Of Artificial Upon examining issues of mind and thought, the questions of artificial intelligence and its capabilities become important considerations for answering the ultimate question of what thought truly is. Computerized calculation is one of the few events that is somewhat analogous to human cognitive thought, so the extension of this current technology to more advanced future applications makes it a very interesting testing area for questions into consciousness. If one concludes that the advancement from cash registers to present day computers is a step closer to human thought, then we must concede that progressing technology will bring us closer and perhaps to the very point of true cognitive skills. The dilemma left to us philosophers and scientists is to determine when a machine has reached the point of thought, or at least to create a rough guideline. A.M. Turing proposed a test to solve this problem. Named, appropriately enough, the Turing test, it contains a controversial method of te sting called the imitation game. The idea is to put one man and one woman in two rooms and have them questioned by an interrogator in a third room. The man would try to answer questions in a way which would suggest he is a woman. The woman attempts to answer in a way to reveal the truth of the matter. If the man fools the interrogator, it is said that he can think like a woman, or, at the very least, mimic a woman's responses. This game can also be played with a computer in the male slot, trying to convince the interrogator that it is human. It would follow reason that if a computer could pass this test, it could think like a human, or at least mimic one. Perhaps the abilities showcased in the test alone would not be sufficient, but Daniel C. Dennett claims that "[t]he assumption Turing was prepared to make was that nothing could possibly pass the Turing test by winning the Imitation Game without being able to perform indefinitely many other clearly intelligent actions" (Dennett 93) . One often cited criticism of this notion is the idea of mimicry. Imagine a program that stored an almost infinite amount of information regarding sentences and grammar and was able to spit out contextualy appropriate sentences to a wide variety of inquiries. The computer has no knowledge of what the information means; it is acting much as a parrot does. Luckily for Turing, there is no shortage of responses for this claim. First of all, as Douglas Hofstadter points outs, "[t]he number of sentences you'd need to store to be able to respond in a normal way to all possible sentences in a conversation is astronomical, really unimaginable" (Hofstadter 92). The computer would also have to contain a complex microprocessor to keep up with conversation in a timely and manageable fashion. It would have to be so advanced indeed that such a microprocessor might be considered a small scale brain, sorting through symbols and their meanings to form contextually valid responses. Accordingly, if su ch a machine existed, it would pass the Turing test and validate the method of testing at the same time. If a machine was capable of mastering the context-sensitive language we use, it may very well have a claim to true thought. At the very least, the computer would surpass mimicry and be labeled a simulation. Human thought is so complicated and demanding that any device that attempts to duplicate it with any success would have to be a highly sensitive simulation. Any machine that passes the Turing test must have a rudimentary "knowledge" of the information it is using and therefore is more than parrot . Assuming this is true, we must then ask hard questions about the value of simulation. The critical claim is that any simulation is just a simulation and not a real example of what it is simulating. Hofstadter finds this fallacious, as do I. First, any simulation can reasonable defined in this context as the recreation of a natural event by an agent other than nature. This view bring s up the idea of levels in simulation. A good example is Dennett's simulated hurricane in Brainstorms. From the programmer's vantage point, the God