One's doctoral advisor is one's academic parent. This relation defines an academic genealogy of researchers that describes the academic ancestors and descendents of a particular set of researchers. While many students have a single doctoral advisor, some have more than one, so the genealogy has a lattice structure that branches both forward and backward in time. This project will build an academic genealogy for the field of Artificial Intelligence (AI), a remarkably interdisciplinary field that draws on computer science, mathematics, electrical, control, and mechanical engineering, cognitive, perceptual, and developmental psychology, linguistics, and philosophy, among other fields. AI is made up of a highly diverse collection of intellectual threads, which can often be made clear through examination of intellectual heritage. . A landmark in the creation of the field of AI was a workshop held at Dartmouth College in the summer of 1956. A number of the attendees at that workshop became the founding researchers in AI and many of their students have gone on to become leaders in the field. Although some of the founders and early leaders of AI have died in recent years, we are fortunate that many are still alive and vigorously pursuing research. It is thus a propitious time to collect historical information from these AI pioneers.

Developing an academic genealogy of AI will be valuable and timely for the field. This project will provide a formal definition for the genealogy task, a representation for the data to be collected, criteria for starting points, and visualization methods. The resulting genealogical data will provide a useful resource for historians and social scientists studying the nature of science as well as the particulars of the field of AI. For instance, the student-advisor relation is an important special case of intellectual influence, and one that is approximated by the formal structure of the academic genealogy. This project will help reveal the human face of science to a wider audience and demonstrate the strength and limitations of the advisor-student relationship in the ongoing process of science. It will also help demonstrate how important new ideas enter a field "from the side", outside of the established links of the academic genealogy.

Agency
National Science Foundation (NSF)
Institute
Division of Information and Intelligent Systems (IIS)
Type
Standard Grant (Standard)
Application #
0538927
Program Officer
Douglas H. Fisher
Project Start
Project End
Budget Start
2005-07-01
Budget End
2007-06-30
Support Year
Fiscal Year
2005
Total Cost
$19,850
Indirect Cost
Name
University of Texas Austin
Department
Type
DUNS #
City
Austin
State
TX
Country
United States
Zip Code
78712