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Humans vs. Machines: Can A Machine Know?

Machines, according to the Compact Oxford English Dictionary is an apparatus using mechanical power and having several parts, for performing a particular task or an efficient and well-organized group of powerful people, coming from the Greek mekhane, from mekhos ‘contrivance’. The apparatus machine is created by humans. But can a machine know?. A machine could be a simple electric can opener to a advanced computer missile defense system. Machines provide humans with endless services, making human life easier and even last longer. But is the information fed into machine knowledge, or is it just numbers with a purpose that can only be determined by humans? Could there be artificial intelligence? To begin answering any such question, the definition of knowledge must be taken into consideration.

Knowledge in Greek is Gnosis. Originally a generic term for knowledge, in the first and second centuries A.D. it came to mean an esoteric knowledge of higher religious and philosophic truths to be acquired by an elite group of intellectually developed believers. Knowledge was something that could only be acquired by the select few, and those select few could not have been machines. Knowledge comes from many different aspects of life; like religion and science. In Webster’s dictionary knowledge is defined as (1): the fact or condition of knowing something with familiarity gained through experience or association or (2): acquaintance with or understanding of a science, art, or technique. Knowledge must be learned and one way to do this is observing the environment and thinking for oneself. Knowledge is built from former knowledge, mathematics, philosophy, religion, science and many other aspects.

Alan Turing proposed a test in which a human and computer respond to a series of questions asked by interrogators, observing whether or not the interrogators would be able to tell the difference between a human or a machine; however, no computer has passed such a test. In order for a computer to pass, artificial intelligence would have to be necessary.

The creation of chess programs on computers has marked a turning point in the quest for artificial intelligence; however, do chess programs provide evidence of artificial intelligence, or are they simply complicated normal programs, no more advanced than calculators? Machines are equipped with Artificial Intelligence, which is the ability of a machine, such as a computer, to perform tasks that are thought to require intelligence. Therefore, it would be appropriate to think that because machines are programmed with artificial intelligence, then they must know, after all the word intelligence is defined as the ability to apply knowledge and skills. However, a machine's intelligence is confined to the intelligence that a designer programs into the computer.

Using psychological terms, there are two different types of intelligence; crystallized intelligence, and fluid intelligence. Crystallized intelligence is acquired knowledge, or when discussing a machine, knowledge programmed into a computer. When using the word crystallized intelligence there is an assumption that using the acquired knowledge, one can perform certain tasks, for example in a machine, it would be appropriate to assume that a formula programmed into a calculator is crystallized intelligence, and that the calculator can be programmed to use the formula. However, fluid intelligence is the ability to perform complex and deductive reasoning. They cannot observe for themselves required information to derive formulas, and therefore do not have the ability to know.

According to M. L. Minsky, "artificial intelligence is the science of making machines do things that would require intelligence if done by men." Another definition of artificial intelligence written by Richard W. Dillon is "[making] it appear as though a computer is thinking, reasoning, making decisions, storing or retrieving knowledge, solving problems, and learning." One of the major advances in computer technology with the introduction of artificial intelligence is that computers are no longer limited to program data in order to calculate problems. Using Artificial Intelligence, a computer is able to make inferences and combined with the software determine a solution for the calculations. Artificial intelligence has already made an impact in the world today using "fuzzy logic." Fuzzy logic is a process by which a camera can automatically focus using inexact information such as height, by assigning aspect values ranging from 0 and 1. Subway trains are able to use the same type of process to automatically control acceleration and deceleration. Artificial intelligence is also the enabling factor for a computer in speech recognition programs.

World chess champion Garry Kasparov was defeated by IBM’s computer chess machine, Deep Blue in New York in 1997. In one test, according to critic Charles Krauthammer, in a cover story in the “Weekly Standard” (May 26, 1997), Deep Blue even passed the Turing Test of human, playing comparatively as a human would. But there are oppositions. "Deep Blue is just a machine," wrote the Yale University computer scientist David Gelernter in “Time” (May 19, 1997). As for intelligence, Deep Blue "doesn't have a mind any more than a flowerpot has a mind." Chess champion Boris Gulko; who in his seven encounters with Garry Kasparov, his score is three wins, three draws, and one loss; believes “Deep Blue's victory is far from the stupendous feat which some pundits (and IBM publicists) have cracked it up to be, and the fact that it succeeded in beating the world champion by a score of 3 1/2 to 2 1/2 tells us little about the machine's intelligence or about its impressive ability to calculate.” The effort to develop chess programs began in the 1950s, and a tournament called the Harvard Cup allows for chess grandmasters to play some of the best programs created. But the results show that machines, overall, are no match for human chess wizards. Defeats such as that of Kasparov’s, can be due to bad weeks for the chess player, whereas the computer has no psychological effect on the location, date, time, or opponent it is playing against. The match in New York is hardly any evidence to prove that machines can excel at a game of strategy, as Kasparov certainly did not play at his optimum ability. The match was referred to as "disappointing," by Indian chess wizard Viswanathan Anand and was said to of been played like a "numskull,” by American grandmaster Patrick Wolff. Just as Gelernter and others have pointed out, the computers' major advantage in encounters with human beings is calculation. It has been established that the total number of possible chess games which can develop from the starting position on the board not only exceeds the number of atoms in the known universe, but does so by a wide margin. As computers play, they sort through as many positions as they can generate in the time allotted to them, a task which (like humans) they necessarily perform incompletely, but with incredible speed and thoroughness. Deep Blue is said to examine 200 million positions a second. Against this advantage, however, one must place certain deficiencies: computers lack essential traits like intuition, imagination, and, most fundamentally, a capacity to plan. Furthermore, if a chess program is defeated, and the opponent were to replay the game making the same exact moves as in the previous game, the chess program would also repeat its previous moves, thus losing again. Chess programs cannot learn from games, but merely evaluate positions the way it has been programmed to do so.

A rationalist would believe that knowledge is simply facts or data or observations that any animal can perceive; therefore, similarly any machine can perceive. A computer with passwords and financial numbers technically “knows” the information, and can work with the information following programs and commands given to it. Artificial intelligence, to the rationalist, would exist, as it is merely creating another animal, or evolving an animal out of metals. Questioning the “knowledge” that neurons have when they spark signals through the brain, it would be proclaimed that eventually microprocessors and programs can become as advanced as the human brain, disregarding purpose, and obeying commands.

Metaphorically, the definition of “know” would be eternal knowledge of existence and purpose, as in “Know Thyself,” as said by Socrates. Knowledge is something acquired from synthesizing and thinking, something only a human being can do. A machine can not develop its own thoughts without inputs and a program of commands, whereas a human being can. A human being would be one with capabilities of questioning existence, purpose, and value. A machine cannot determine its own existence, much less the purpose of it. A computer would never be able to develop the idea “I think, therefore I am.” So the metaphorical person would argue that machines cannot know, and that knowledge is thought pertaining to the purpose and value of life acquired from critical thinking.

Another reason machines can't “know” is that they cannot think about God. The ability to think abstractly is developed in humans in what psychologist Jean Piaget called the formal operational stage of cognitive development. In this stage when adolescents are twelve years of age and older, they become interested in questions testing their ability to think abstractly. Machines never develop into the formal operational stage, because thinking abstractly is an ability that requires no computing of data, or searching through a database. It is merely the ability to question the world and ask oneself who created it. Computers don’t have the ability to think in this manner and never will. Personally, I think that machines cannot know because they cannot tell the difference between right and wrong. In other words, machines do not have a conscience. A machine can never be programmed to develop a set of moral values like that of a human. The intangibles in a human such as emotions, and deep thoughts make up a conscience.

Presently, a household pc can hold up to around 80 GB of memory, including songs, photos, documents, etc. The majority of computers have some source of internet access, which holds information for a vast expanse of knowledge. However, knowledge "goes deeper than the ability to recall facts, and implies the ability to relate one thing to another." (Jeff Orkin, MIT) Currently, major areas of research at MIT involve understanding the way in which the brain has varying degrees of confidence about its knowledge, and the ability to make inferences based on prior confidence of knowledge. (Orkin) This ability of the human brain seems to be the missing link in the ability of a machine to act like a human brain. When referring to knowing, it is important to note that a human has the ability to think about the process of knowing, and is able to recognize that it knows what it knows, ability called reflective thought. For example, they know the experiences that they have, or whether or not they are prepared for a calculus exam.

In 1965 Daniel Bobrow designed a computer system that he called STUDENT, that he said had the ability to answer basic algebra word problems such as: The distance from New York to Los Angeles is 3000 miles. If the average speed of a jet plane is 600 miles per hour, find the time it takes to travel from New York to Los Angeles by jet. Most people would agree that in order to answer questions like these, it is necessary to understand the actual meaning of words, and that word problems differ from other computations because a computer must understand sentences and then figure out how to put the information into preprogrammed formulas. However, Bobrow developed a clever way to avoid this problem by programming the computer to recognize about 200 words, and programming the computer to associate the words with simple mathematical computations. For example, he programmed the computer to translate "is" into equals, because of the great possibility that "is" would constitute the equal expression. Using these word tricks, STUDENT was able to sometimes manage to answer correctly, however this still is not thinking, but merely another programmed ability of a computer, that would inevitably become more technologically advanced over time.

However, the problem in denying a computer's ability to know arises when the question is asked how is a computer’s ability to recognize these word tricks, different from the human brain. When learning algebra, teachers teach, or "program" students to solve the problems in a similar manner. The answer by most critics would be the difference between the two, is that a computer is not self-aware of that which it is doing, and does not understand the process involved. In response to the critique, Marvin Minsky would investigate the question of whether or not people are indeed self-aware of their mental processes. He would answer this by denying that people are aware of the mental processes involved in knowing. People do not understand the mechanics and processes involved in solving algebraic equations. Indeed they are aware of relatively simple processes such as hearing, but it is not fully understood how people can speak and other such phenomena. Minsky also believes it may be possible in the future to create computers that are able to understand the processes they use, and perhaps fix and improve these processes, much like in the Hollywood movies of today. Thus, an expert on artificial intelligence at MIT, Henry Lieberman believes the first step in creating a computer that can know, is to first be able to understand how the human brain works. Only, then can it be replicated in a computer. After all isn't the human brain just one very advanced and complicated machine.

Personally, I have dwelled upon this topic for years, the question of knowledge. Certainly there has to be more than memorizing math formulas and history dates in school. In the Shrimad Bhagavad Geeta, Lord Krishna says to Arjuna imam vivasvate yogam, proktavanahamavyayam. Vivasvanmanave praha, mauriksvakave’bravit. “In the very beginning epoch, I revealed the secret of this evergreen Yoga (Sublime Knowledge) to Sun. He passed it on to his son Manu, and Manu imparted the knowledge to his son, Ikshwaku (4:1). This knowledge, according to the Geeta is the knowing of what real state is, the sum total of all knowledge and sciences. It reveals the purpose of life, the meaning of materialism. And, such knowledge cannot be attained by a machine due to the fact that it requires personal insight and thought.

I read your rough draft first to see what you did to improve your essay and your corrections made your paper flow very well. The information you provided was very interesting and informative. I can't believe the terminator is unable to have deep thoughts or emotions. You picked a very interesting topic and although I am not very philosophical or technological I enjoyed reading it. I didn't notice and spelling or grammatical errors and your information provided is relevant to your thesis. You got your point across and did not elaborate on boring details to make your paper longer. Excellant essay!