Artificial Intelligence

Computer-based technology intended to replicate the complicated processes of human cognition, including such complex tasks as reasoning, and machine learning, whereby a man-made device actually incorporates its experiences into new endeavors, learning from its mistakes and engaging in creative problem solving.

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The study of artificial intelligence, referred to as AI, has accelerated in recent years as advancements in computer technology have made it possible to create more and more sophisticated machines and software programs. The field of AI is dominated by computer scientists, but it has important ramifications for psychologists as well because in creating machines that replicate human thought, much is learned about the processes the human brain uses to "think."

Creating a machine to think highlights the complexities and subtleties of the human mind. For instance, creating a machine to recognize objects in photographs would seem, at first thought, rather simple. Yet, when humans look at a photograph, they do so with expectations about the limitations of the media. We fill in the missing third dimension and account for other missing or inconsistent images with our sense of what the real world looks like. To program a computer to make those kinds of assumptions would be a gargantuan task. Consider, for instance, all the information such a computer would need to understand that the array of images all pressed up against a flat surface actually represent the three-dimensional world. The human mind is capable of decoding such an image almost instantaneously.

This process of simulating human thought has led to the development of new ideas in information processing. Among these new concepts are fuzzy logic, whereby a computer is programmed to think in broader terms than either/or and yes/no; expert systems, a group of programming rules that describe a reasoning process allowing computers to adapt and learn; data mining, detecting patterns in stimuli and drawing conclusions from them; genetic algorithm, a program that provides for random mutation for the machine to improve itself; and several others.

Recent applications of AI technology include machines that track financial investments, assist doctors in diagnoses and in looking for adverse interactions in patients on multiple medications, and spotting credit card fraud. An Australian scientist working in Japan is attempting to create a silicon brain using newly developed quantum resistors. Reported in a 1995 article in Business Week, Hugo de Garis is leading a team of scientists to create a computing system capable of reproducing itself. As Business Week reports, the project will attempt to "not only coax silicon circuits into giving birth to innate intelligence but imbue them with the power to design themselves—to control their own destiny by spawning new generations of ever improving brains at electronic speeds." This type of technology is called evolvable hardware.

Other recent advances in AI have been the creation of artificial neural systems (ANS) which has been described as "an artificial-intelligence tool that attempts to simulate the physical process upon which intuition is based—that is, by simulating the process of adaptive biological learning." ANS, essentially, is a network of computers that are grouped together in ways similar to the brain's configuration of biological processing lobes.

Even considering all of these advancements, many people are skeptical that a machine will ever replicate human cognition. Marvin Minsky, a scientist at the Massachusetts Institute of Technology, states that the hardest thing of all in the creation of artificial intelligence is building a machine with common sense.