entire book - Chris Hables Gray

Definitions of Artificial Intelligence
The Uses of Science [ 71 ]
The dream of AI, the formalization/mechanization/creation of intelligence,
goes back a long way. Ancient creation stories are often about some divinity's
artificial intelligence project and its problems. Even the human quest for
artificial intelligence predates science by thousands of years, witness Pygmalion's
Galatea (made for him by Aphrodite, goddess of love) and the cabalistic
tales of the golem. Certainly the idea is older than G. W. Leibniz and his
perfect mathematical language and Rene Descartes' perfect machine. It is at
least as old as Plato with his perfect models, models he thought were more
real than real, more real than us, shadows on the cave wall.
Ramon Llull (or Raymond Lully), Thomas Bacon, and many alchemists
of gnostic, Moslem, Christian, and pagan bent have had their talking heads
or sought the creation of the homunculus, the artificial man. AI has not
always been linked to the demands of war, but the AI dream today is a
militarized dream, and in a strong sense it is a dream of an impossible human
future, where war is a science. There are other equal if more subtle dangers
from militarized AI.
Paul Edwards points out that cybernetic work is one of the most
important touchstones of human self-definition of our times. As such it
represents a profoundly significant political and psychological focus.
Cybernetic science has become a primary source of meanings for us.
Formal/mechanical modeling practices are therefore political issues in the
profound sense that they provide the categories and techniques by which
we understand ourselves. (1986b, p. 39; emphasis in original)
Just exactly what AI means is fluid. One common definition is that if it takes
intelligence to do something by a human, then if a machine can do it you
have an artificial intelligence. However, this misses actions humans can't
do—actions that if we could do them we would certainly consider intelligent,
such as distinguishing thousands of ICBMs from decoys and then telling
hundreds of weapon systems when and where to shoot them down, all within
a few seconds. These are all feats that AI researchers are trying to get
machines to do. Some work originally done in the field, such as time-sharing,
is now considered mainstream computer science, leading to the joke among
computer hackers that "if it works, it isn't AI."
Specific subfields of computer science that are conceded to fall within
AI are expert systems, natural language processing, and most learning and
reasoning research. AI also generally describes work involving symbolic
processors—computers that use logical inferences of one kind or another, as
opposed to the strictly binary mathematics used in traditional programs and
machines. The trendy second wave of neurocomputing sometimes tries to