ABSTRACT
In recent years, there has been increased interest in the development of artificially intelligent systems. The research on artificial intelligence has produced computational models for such complex processes as “vision, language comprehension, knowledge representation, learning, inferring reasoning, planning, and language production” (Wilson & Bates, 1981, p. 336). Further, systems such as PILOT, TICCIT, AND GNOSIS are capable of “understanding” course content, possess interactive processing abilities, and can adjust to fluctuating thought processes (Brown & Burton, 1978). Unfortunately, the critical questions and observations have risen concerning the construction of these superhuman faculties (Longuet-Higgins, 1982, p. 225). As noted by Wilson and Bates (1981), for example, although these systems possess an “impressive amount of intelligence” (p. 337) their expertise is in limited domains and imperfections are vast. Perhaps, however, these weaknesses stem not so much from a failing in the technology of artificial intelligence, but from a lack of understanding of how intelligence is applied to solving problems creatively.
