Artificial Intelligence
The computer revolution has influenced everyday matters from the way letters are written to the methods in which our banks, governments, and credit card agencies keep track of our finances. The development of artificial intelligence is just a small percentage of the computer revolution and how society deals with, learns, and incorporates artificial intelligence. It will only be the beginning of the huge impact and achievements of the computer revolution.
A standard definition of artificial intelligence, or AI, is that computers simply mimic behaviors of humans that would be regarded as intelligent if a human being did them. However, within this definition, several issues and views still conflict because of ways of interpreting the results of AI programs by scientists and critics. The most common and natural approach to AI research is to ask of any program, what can it do? What are the actual results in comparison to human intelligence? For example, what matters about a chess-playing program is how good it is. Can it possibly beat chess grand masters? There is also a more structured approach in assessing artificial intelligence, which began opening the door of the artificial intelligence contribution into the science world. According to this theoretical approach, what matters is not the input-output relations of the computer, but also what the program can tell us about actual human cognition (Ptack, 1994).
From this point of view, artificial intelligence can not only give a commercial or business world the advantage, but also a understanding and enjoyable beneficial extend to everyone who knows how to use a pocket calculator. It can outperform any living mathematician at multiplication and division, so it qualifies as intelligent under the definition of artificial intelligence. This fact does not entertain the psychological aspect of artificial intelligence, because such computers do not attempt to mimic the actual thought processes of people doing arithmetic (Crawford, 1994). On the other hand, AI programs that simulate human vision are theoretical attempts to understand the actual processes of human beings and how they view and interpret the outside world. A great deal of the debate about artificial intelligence confuses the two views, so that sometimes success in artificial intelligence's practical application is supposed to provide structured or theoretical understanding in this branch of science known as cognitive science. Chess-playing programs are a good example. Early chess-playing programs tried to mimic the thought processes of actual chess players, but they were not successful. Ignoring the thoughts of chess masters and just using the much greater computing powers of modern hard wares have achieved more recent successes. This approach, called brute force, comes from the fact that specially designed computers can calculate hundreds of thousands or even millions of moves, which is something no human chess player can do (Matthys, 1995). The best current programs can beat all but the very best chess players, but it would be a mistake to think of them as substantial information to artificial intelligence's cognitive science field (Ptacek, 1994). They tell us almost nothing about human cognitions or thought processes, except that an electrical machine working on different principles can outdo human beings in playing chess, as it can defeat human beings in doing arithmetic.
Assuming that artificial intelligence's practical applications, or AIPA, is completely successful and that society will soon have programs whose performance can equal or beat that of any human in any comprehension task at all. Assume machines existed that could not only play better chess but had equal or better comprehension of natural languages, write equal or better novels and poems, and prove equal or better math and science equations and solutions. What should society make of these results? Even with the cognitive science approach, there are some further distinctions to be made. The most influential claim is if scientists programmed a digital computer with the right programs, and if it had the right inputs and outputs, then it would have thoughts and feelings in exactly the same sense in which humans have thoughts and feelings. In accordance to this view, the computer programming and AICS program is not just mimicking intelligent thought patterns, it actually is going through these thought processes. Again the computer is not just a substitution of the mind. The newly programmed computer would literally have a mind. So if there were an AIPA program that appropriately matched human cognition, scientists would artificially have created an actual mind.
It seems that artificial intelligence is possibly a program that will one day exist. The mind is just the program in hardware of the human brain, but this created mind could also be programmed into computers manufactured by IBM. However, there is a big difference from artificial intelligence and various forms of AICS. Though, it is the weakest claim of artificial intelligence stating that the appropriately programmed computer is a tool that can be used in the study of human cognition. By attempting to impersonate the formal structure of cognitive processes on a computer, we can better come to understand cognition. From this weaker view, the computer plays the same role in the study of human beings that it plays in any other discipline (Taubes, 1995; Crawford, 1994).
We use computers to simulate the behavior of weather patterns, airline flight schedules, and the flow of money in things. No one began programming any of these computer operations so the computer program literally makes brainstorms, or that the computer will literally take off and fly to San Diego when we are doing a computer simulation of airline flights. Also, no one thinks that the computer simulation of the flow of money will give us a better chance at preparing for things like The Great Depression. To stand by the weaker conception of artificial intelligence, society should not think that a computer simulation of cognitive processes actually did any real thinking.
According to this weaker, or more cautious, version of AICS, we can use the computer to do models or simulations of mental processes, as we can use the computer to do simulations of any other process as long as we write a program that will allow us to do so. Since this version of AICS is more cautious, it is probably safe to assume that it is less likely to be controversial, and more likely to be heading towards real possibilities.
Bibliography:
Crawford, Robert, Machine Dreams, Vol. 97, Technology Review, 1 Feb 1994, pp. 77.
Matthys, Erick, Harnessing technology for the future, Vol. 75, Military Review, 1 May 1995, pp. 71
Morss, Ruth, Artificial intelligence guru cultivate natural language, Vol. 14, Boston Business Journal, 20 Jan 1995, pp. 19
Ptacek, Robin, Using artificial intelligence, Vol. 28, Futurist, 1 Jan 1994, pp.38
Taubes, Gary, The rise and fall of thinking machines, Vol. 1995, Inc., 12 Sep 1995, pp. 61
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