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A brief history of artificial intelligence

Last updated: 02-16-2020

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A brief history of artificial intelligence

In the early days of artificial intelligence, computer scientists attempted to recreate aspects of the human mind in the computer. This is the type of intelligence that is the stuff of science fiction—machines that think, more or less, like us. This type of intelligence is called, unsurprisingly, intelligibility. A computer with intelligibility can be used to explore how we reason, learn, judge, perceive, and execute mental actions.

Early research on intelligibility focused on modeling parts of the real world and the mind (from the realm of cognitive scientists) in the computer. It is remarkable when you consider that these experiments took place nearly 60 years ago.

Early models of intelligence focused on deductive reasoning to arrive at conclusions. One of the earliest and best known A.I. programs of this type was the Logic Theorist, written in 1956 to mimic the problem-solving skills of a human being. The Logic Theorist soon proved 38 of the first 52 theorems in chapter two of the Principia Mathematica, actually improving one theorem in the process. For the first time, it was clearly demonstrated that a machine could perform tasks that, until this point, were considered to require intelligence and creativity.

Soon research turned toward a different type of thinking, inductive reasoning. Inductive reasoning is what a scientist uses when examining data and trying to come up with a hypothesis to explain it. To study inductive reasoning, researchers created a cognitive model based on the scientists working in a NASA laboratory, helping them to identify organic molecules using their knowledge of organic chemistry. The Dendral program was the first real example of the second feature of artificial intelligence, instrumentality, a set of techniques or algorithms to accomplish an inductive reasoning task, in this case molecule identification.

Dendral was unique because it also included the first knowledge base, a set of if/then rules that captured the knowledge of the scientists, to use alongside the cognitive model. This form of knowledge would later be called an expert system. Having both kinds of “intelligence” available in a single program allowed computer scientists to ask, “What makes certain scientists so much better than others? Do they have superior cognitive skills, or greater knowledge?”

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