Artificial intelligence. Many people expect advances in artificial intelligence to provide the revolutionary breakthrough that will give order-of-magnitude gains in software productivity and quality. I do not. To see why, we must dissect what is meant by “artificial intelligence” and then see how it applies.
Parnas has clarified the terminological chaos:
Two quite different definitions of AI are in common use today.
AI-1: The use of computers to solve problems that previously could only be solved by applying human intelligence.
AI-2: The use of a specific set of programming techniques knows as heuristic or rule-based programming. In this approach human experts are studies to determine what heuristics or rules of thumb they use in solving problems. . . . The program is designed to solve a problem the way that humans seem to solve it.
The first definition has a sliding meaning. . . . Something can fit the definition of AI-1 today but, once we see how the program works and understand the problem, we will not think of it as AI anymore. . . . Unfortunately I cannot identify a body of technology that is unique to this field. . . . Most of the work is problem-specific, and some abstraction or creativity is require to see how to transfer it
