second technique is evolutionary program development. To develop a regular program, one or more programmers write code telling the computer exactly what to do. The programmers themselves have designed the algorithm used and understand what each part of it is meant to accomplish. In order to develop an evolutionary program, however, the programmers start with a more or less random algorithm and a program to determine how fit that algorithm is for a certain task. The algorithm is then mutated and mated with other algorithms to produce a new generation of algorithms; the most fit algorithms of each succeeding generation are mated together. After many generations, a usable program has been developed, with code written by the computer itself Evolutionary development has been used extensively in hardware development and chip design, and is a basic premise of artificial life, simulating primitive forms of life on a computer (Benedict 263). Both of these approaches have shown aptitude for the kind of reasoning needed by a general artificial intelligence, and as the scientific community comes to the realization that traditional program design is prohibitive for all but the most limited of intelligences, these and other methods will be further studied, implemented, and adopted. Neural networks, evolutionary program development, and other approaches currently being developed truly represent the kind of paradigm shift needed to unite creativity and concept association with logic and order. The Future Several scientists have argued against artificial intelligence on both ethical and scientific grounds. Computers could never possess intelligence, such scientists say, and if they did, they could certainly never be conscious. The nature of consciousness and knowledge, as suggested earlier, is truly unknown. Be this as it may, nothing suggests that these traits are specific to organic material, or that they cannot be reproduced in silicon. Th...
