ARTIFICIAL INTELLIGENCE: ENGINEERING, SCIENCE,

This paper presents the view that artificial intelligence (AI) is primarily concerned with propositional languages for representing knowledge and with techniques for manipulating these representations. In this respect, AI is analogous to applied mathematics; its representations and techniques can be applied in a variety of other subject areas. Typically, AI research (or should be) more concerned with the general form and properties of representational languages and methods than it is with the content being described by these languages Notable exceptions involve “commonsense” knowledge about the everyday world (no other specialty claims this subject area as its own), and metaknowledge (or knowledge about the properties and uses of knowledge itself). In these areas AI is concerned with content as well as form. We also observe that the technology that seems to underly peripheral sensory and motor activities (analogous to low-level animal or human vision and muscle control) seems to be quite different from the technology that seems to underly cognitive reasoning and problem solving. Some definitions of AI would include peripheral as well as cognitive processes; here we argue against including the peripheral processes.