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Introduction: The Substitution of Human Faculties with Technology: Artificial Intelligence and Expert Systems |
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Research in  artificial intelligence, starting in the 1960s, yet formulated a new goal: the automation of thought processes with intelligent machines. Although first attempts to develop "thinking" machines had only little success as the aimed at solving very general problems, the invention of expert systems marked a breakthrough. Albeit the application of those semi-intelligent systems is (still) restricted to quite narrow domains of performance, such as taxation and medical image interpretation, they are able to mimic the knowledge and reasoning capabilities of an expert in a particular discipline. While the development of intelligent machines, which are able to reason, to generalize and to learn from past experience is not likely to become reality in the very near future, research in artificial intelligence progresses quickly and sooner or later the substitution of men's unique faculties will come true.
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Expert system
Expert systems are advanced computer programs that mimic the knowledge and reasoning capabilities of an expert in a particular discipline. Their creators strive to clone the expertise of one or several human specialists to develop a tool that can be used by the layman to solve difficult or ambiguous problems. Expert systems differ from conventional computer programs as they combine facts with rules that state relations between the facts to achieve a crude form of reasoning analogous to artificial intelligence. The three main elements of expert systems are: (1) an interface which allows interaction between the system and the user, (2) a database (also called the knowledge base) which consists of axioms and rules, and (3) the inference engine, a computer program that executes the inference-making process. The disadvantage of rule-based expert systems is that they cannot handle unanticipated events, as every condition that may be encountered must be described by a rule. They also remain limited to narrow problem domains such as troubleshooting malfunctioning equipment or medical image interpretation, but still have the advantage of being much lower in costs compared with paying an expert or a team of specialists.
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