Shafer, Glenn (Ray) 1946-

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SHAFER, Glenn (Ray) 1946-

PERSONAL: Born November 21, 1946, in Caney, KS; son of Richard Glenn (a farmer and mail carrier) and Anna Loucile (a homemaker; maiden name, Mayfield) Shafer; married Teresa Ann Shistar, August 25, 1970 (divorced, November, 1985); married Nell Elizabeth Irvin Painter, October 14, 1989; children: Richard Glenn, Dennis Steven. Ethnicity: "White." Education: Princeton University, A.B., 1968, Ph.D., 1973. Politics: Democrat. Religion: Christian Church (Disciples of Christ).

ADDRESSES: Home—577 Ridge St., Newark, NJ 07104. Offıce—Rutgers Business School—Newark and New Brunswick, Rutgers University, 180 University Ave., Newark, NJ; fax: 973-483-1693. E-mail— gshafer@andromeda.rutgers.edu.

CAREER: Princeton University, Princeton, NJ, assistant professor of statistics, 1973-76; University of Kansas, Lawrence, began as assistant professor, became professor of mathematics, 1976-84, began as professor, became distinguished professor of business, 1984-92; Rutgers University, Newark, NJ, professor of management, 1992—. Center for Advanced Study in the Behavioral Sciences, fellow, 1988-89.

MEMBER: American Statistical Association, Institute of Mathematical Statistics (fellow), American Accounting Association, American Association for Artificial Intelligence (fellow), History of Science Society, Philosophy of Science Association, Judgment and Decision Making Society.

AWARDS, HONORS: Guggenheim fellow, 1983-84; Fulbright fellow in Germany, 2001.

WRITINGS:

A Mathematical Theory of Evidence, Princeton University Press (Princeton, NJ), 1976.

(Editor, with Judea Pearl) Readings in Uncertain Reasoning, Morgan Kaufmann (San Mateo, CA), 1990.

Probabilistic Expert Systems, Society for Industrial and Applied Mathematics (Philadelphia, PA), 1996.

The Art of Causal Conjecture, MIT Press (Cambridge, MA), 1996.

(With Vladimir Vovk) Probability and Finance: It'sOnly a Game!, John Wiley and Sons (New York, NY), 2001.

WORK IN PROGRESS: Continuing research on the game-theoretical treatment of probability, finance, and causality.

SIDELIGHTS: Glenn Shafer once told CA: "I think of myself first and foremost as a philosopher and, to a lesser extent, a historian of probability and mathematical statistics. Since my graduate work in statistics in the graduate schools of Berkeley, Harvard, and Princeton in the early 1970s, I have been fascinated by the historical and contemporary diversity of opinion about the meaning of mathematical probability. Yet I am a fairly practical philosopher. Most of my university teaching has been practical and applied. I have taught statistics, artificial intelligence, finance, and information systems in statistics and mathematics departments and in business schools. Much of my published work has also found practical applications. The non-standard theory of probability developed in my first book, A Mathematical Theory of Evidence, has been widely used, especially in expert systems, and my more recent work on causality is directed toward applications in both statistics and expert systems.

"My motivation is both philosophical and applied; I want to understand the meaning and justification of the methods of inference used by practicing statisticians and other research workers, and to use that analysis to improve on those methods. This means that my inspiration tends to come from mathematical and applied writers, not from philosophers. In recent decades, the writing on probability and statistics by professional philosophers has tended, unfortunately, to focus on puzzles and concepts developed entirely within the philosophical tradition, with decreasing relevance to application.

"My most successful writing experiences have involved the blossoming of an idea, which took on a life of its own. My first two major books, A Mathematical Theory of Evidence and The Art of Causal Conjecture, both began as short papers—papers that were obviously incomplete and demanded elaboration, expansion, and clarification that could not stop until they became books. My more deliberate book projects have always been too ambitious to be completed, but I may yet write the great American probability book.

"Currently I am working on a very different and very rewarding project—a collaboration with a fellow mathematician, Vladimir Vovk. Together we have completed a book that explains how the standard foundation for mathematical probability theory, Kolmogorov's measure-theoretic framework, can be replaced by a game-theoretic foundation, whose greater simplicity offers advantages for many applications. The book is constructed around Vovk's unpublished mathematical work, but it has given me an opportunity to synthesize many of the ideas on the philosophy of probability that have occupied me for several decades."

More recently Shafer added: "The game-theoretic approach is especially important for finance, because it offers ways to improve substantially the efficiency of markets for derivatives. There are also important applications to statistics and the understanding of causality. I plan to continue working on these topics with Vovk during the coming decades."