Download Report of the Research Briefing Panel on Cognitive Science and

RESEARCH BRIEFINGS 1983
Report of the
Research Briefing Panel on
Cognitive Science and Artificial Intelligence
Reprinted from Research Briefings 1983, National Academy Press, Washington, D.C.
19
Research Briefing Panel on
Cognitive Science and Artificial Intelligence
Shimon Ullman, Massachusetts Institute of
Technology
William K. Estes (Co-chair), Harvard
University
Alien Newell (Co-chair), Carnegie-Mellon
University
John R. Anderson, Carnegie-Mellon
University
John Seely Brown, Xerox Palo Alto Research
Center
Edward A. Feigenbaum, Stanford
University
James Greeno, University of Pittsburgh
Patrick J. Hayes, University of Rochester
Earl Hunt, University of Washington, Seattle
Stephen M. Kosslyn, Harvard University
Mitchell Marcus, Bell Telephone
Laboratories
Staff
Paul S. Rosenbloom, Rapporteur, CarnegieMellon University
David A. Goslin, Executive Director,
Commission on Behavioral and Social
Sciences and Education
Sarah M. Streuli, Administrative Secretary,
Commission on Behavioral and Social
Sciences and Education
Allan R. Hoffman, Executive Director,
Committee on Science, Engineering, and
Public Policy
20
future problem situations. Building this feature effectively into computer systems can be
seen as the next major advance in the power
of intelligent systems. Cultivating it during
human cognitive development may be a key
to materially increasing human problemsolving abilities.
An important offshoot of research on artificial intelligence is its clarification of the
problems and its development of methods
pertaining to the systematization and codification of the enormous accumulation of
knowledge in technical domains. It is coming
to be widely believed that information processing will be the heart of the next industrial
revolution. (Witness the scale of the Japanese
Fifth Generation Computer project, centered
on very large scale machines for artificial
intelligence.) As occurred earlier for energy
and the physical sciences, and later for medicine and the biological sciences, only massive basic research efforts can prepare us to
keep up with this fast-moving worldwide
development.
But machine intelligence alone will not
suffice. Human intelligence must comprehend the emerging problems and the
machines that aid in their solution. Thus, new
challenges face our already heavily burdened
education system. Cognitive science may be
able to provide the broadened theoretical
framework within which significant progress can occur and artificial intelligence major
components of the needed new educational
technology.
5. The application of what is being learned
about high-level human reasoning and
processes of skill and knowledge acquisition to the development of a new level
of expert systems in artificial intelligence.
6. The development of computer-based
intelligence tutoring systems, which can
play an important role in educating and
reeducating our people for a high-technology society.
However, we do not wish to place too much
weight on specific lines of research. Cognitive science and artificial intelligence differ
from various predecessors most importantly
in the emphasis on general problems of fundamental theoretical significance. Though a
full theory of intelligence is still remote, the
insight that both intelligent machines and their
human counterparts can be seen as instances
of the class of symbol-manipulating systems
has yielded some general results and opened
the way for more.
Broadly viewed, research in both cognitive
science and artificial intelligence is showing
that the acquisition and organization of
information are basic aspects of intelligence
in both humans and machines. A salient and
pervasive characteristic of human beings,
distinguishing them sharply from lower
organisms and special-purpose computers,
is a tendency to acquire information that goes
far beyond current task demands and to
organize the accumulating knowledge so that
it can be accessed and used in unforeseeable
36