Information Technology Reference
In-Depth Information
the space of about ten years. In GOFAI—good, old-fashioned AI—the aim was
to mimic mental performances. Alan Newell and Herbert Simon's Logic Theo-
rist program was an early landmark, and it was a program that mimicked the
proofs to be found in Bertrand Russell and Alfred North Whitehead's
Principia
Mathematica
. In robotics this translated into the problematic of generating
computer representations (maps, models) of environments and operating on
them to execute plans, such as moving from A to B while avoiding obstacles.
This style of AI and robotics, then, can stand as a piece of ontological theater
for the other ontology from that of cybernetics, the modern ontology of know-
ability. AI robots sought to know their worlds substantively, and to accomplish
their goals through that knowledge. AI robotics was the other to Walter-style
robotics.
Historically, representational, or symbolic, AI quickly became the domi-
nant paradigm in the universities, largely displacing cybernetics from its al-
ready tenuous foothold, not only from computer science departments and
their ilk, but from social science departments, too, in the so-called cognitive
revolution, in which human mental powers were conceived by analogy to
digital computers as information processors (Gardner 1987). Of course, the
rise of AI and the associated “cognitive sciences” is an immense historical
story in itself, but let me just comment briefly. How did AI come to exert such
a fascination over the academic and popular imagination? Part of the answer
must lie in its very familiar ontology. It is easy to think of the brain and mind
as the organ of knowledge, and AI thus conceived presents a straightforward
problem of mimicking very familiar (especially to academics) mental perfor-
mances. At the same time, AI was uniquely associated with digital computers
and their programming and thus fitted very naturally into the agenda of novel
postwar departments of computer science (unlike the odd machines of Walter
et al.). And third, the military bought it. Almost all the funding for AI research
was provided by the U.S. military, and almost all of that went to research in
symbolic AI (Edwards 1996).
36
Cybernetics thus lost much of its social basis in the universities from the
mid-1950s onward; the cyberneticians became even more marginal there than
they had been before—which is another kind of answer to the question, what
happened to cybernetics? But this gets us back to the story of Rodney Brooks.
In robotics, symbolic AI promised much but never quite delivered. Machines
were never quite fast enough to accomplish real-time control.
37
In his first
years in the United States, Brooks worked within this tradition, focusing on
computer models of environments, but became increasingly frustrated with
it. In the late 1970s at Stanford, he helped Hans Moravec, a future leader in
