William J. Rapaport

The proper treatment of computationalism, as the thesis that cognition is computable, is presented and defended. Some arguments of James H. Fetzer against computationalism are examined and found wanting, and his positive theory of minds as semiotic systems is shown to be consistent with computationalism. An objection is raised to an argument of Selmer Bringsjord against one strand of computationalism, namely, that Turing-Test± passing artifacts are persons, it is argued that, whether or not this objection holds, such artifacts will inevitably be persons

H´ector-Neri Casta˜neda-Calder´on (December 13, 1924–September 7, 1991) was born in San Vicente Zacapa, Guatemala. He attended the Normal School for Boys in Guatemala City, later called the Military Normal School for Boys, from which he was expelled for refusing to fight a bully; the dramatic story, worthy of being filmed, is told in the “De Re” section of his autobiography, “Self-Profile” (1986). He then attended a normal school in Costa Rica, followed by studies in philosophy at the University of San Carlos, Guatemala. He won a scholarship to the University of Minnesota, where he received his B.A. (1950), M.A. (1952), and Ph.D. (1954), all in philosophy. His dissertation, “The Logical Structure of Moral Reasoning”, was written under the direction of Wilfrid Sellars. He returned to teach in Guatemala, and then received a scholarship to study at Oxford University (1955–1956), after which he took a sabbatical-replacement position in philosophy at Duke University (1956). His first full-time academic appointment was at Wayne State University (1957– 1969), where he founded the philosophy journal Noˆus (1967, a counter-offer made to him by Wayne State to encourage him to stay there rather than to take the chairmanship of philosophy at the University of Pennsylvania). In 1969, he moved (along with several of his Wayne colleagues) to Indiana University, where he eventually became the Mahlon Powell Professor of Philosophy and, later, its first Dean of Latino Affairs (1978–1981). He remained at Indiana until his death. He was also a visiting professor of philosophy at the University of Texas at Austin (1962–1963) and a fellow at the Center for Advanced Study in the Behavioral Sciences (1981–1982). He received grants and fellowships from the Guggenheim Foundation (1967–1968), the T. Andrew Mellon Foundation, the National Endowment for the Humanities, and the National Science Foundation. He was elected President of the American Philosophical Association Central Division (1979– 1980), named to the American Academy of Arts and Sciences (1990), and received the Presidential Medal of Honor from the Government of Guatemala (1991). Casta˜neda’s philosophical interests spanned virtually the entire spectrum of philosophy, and his theories form a highly interconnected whole..

Syntactic semantics is a holistic, conceptual-role-semantic theory of how computers can think. But Fodor and Lepore have mounted a sustained attack on holistic semantic theories. However, their major problem with holism (that, if holism is true, then no two people can understand each other) can be fixed by means of negotiating meanings. Syntactic semantics and Fodor and Lepore’s objections to holism are outlined; the nature of communication, miscommunication, and negotiation is discussed; Bruner’s ideas about the negotiation of meaning are explored; and some observations on a problem for knowledge representation in AI raised by Winston are presented

In the Fall of 1983, I offered a junior/senior-level course in Philosophy of Artificial Intelligence, in the Department of Philosophy at SUNY Fredonia, after returning there from a year’s leave to study and do research in computer science and artificial intelligence (AI) at SUNY Buffalo. Of the 30 students enrolled, most were computerscience majors, about a third had no computer background, and only a handful had studied any philosophy. (I might note that enrollments have subsequently increased in the Philosophy Department’s AI-related courses, such as logic, philosophy of mind, and epistemology, and that several computer science students have added philosophy as a second major.) This article describes that course, provides material for use in such a course, and offers a bibliography of relevant articles in the AI, cognitive science, and philosophical literature.

This essay considers what it means to understand natural language and whether a computer running an artificial-intelligence program designed to understand natural language does in fact do so. It is argued that a certain kind of semantics is needed to understand natural language, that this kind of semantics is mere symbol manipulation (i.e., syntax), and that, hence, it is available to AI systems. Recent arguments by Searle and Dretske to the effect that computers cannot understand natural language are discussed, and a prototype natural-language-understanding system is presented as an illustration.

It is a matter of fact—and has been so for a considerable amount of time—that philosophy is taught at the pre—college level. However, to teach philosophy at that (or at any) level is one thing; to teach it well is quite another. Fortunately, it can be taught well, as a host of successful experiences and programs have shown. But in what ways can it be taught? Are there differences in the ways in which it can or should be taught at the pre-college level from the ways in which it is taught in college? Are there differences in the ways in which it can or should be taught at the elementary-school level from ways in which it can or should be taught at the secondary-school level? There are other questions, of a similar nature, that the beginning college-level teacher of philosophy might ask: “I have never taught Introduction to Philosophy before; how should I go about it?” And there is a further question: Should it be taught at all? This question can, of course, be raised at any educational level, but it is especially acute at the elementary level.

This essay presents a philosophical and computational theory of the representation of de re, de dicto, nested, and quasi-indexical belief reports expressed in natural language. The propositional Semantic Network Processing System (SNePS) is used for representing and reasoning about these reports. In particular, quasi-indicators (indexical expressions occurring in intentional contexts and representing uses of indicators by another speaker) pose problems for natural-language representation and reasoning systems, because--unlike pure indicators--they cannot be replaced by coreferential NPs without changing the meaning of the embedding sentence. Therefore, the referent of the quasi-indicator must be represented in such a way that no invalid coreferential claims are entailed. The importance of quasi-indicators is discussed, and it is shown that all four of the above categories of belief reports can be handled by a single representational technique using belief spaces containing intensional entities. Inference rules and belief-revision techniques for the system are also examined.