How Can a Machine Be Intelligent?

How Can a Machine Be Intelligent?

The science ARTIFICIAL of making machines act intelligently is usually referred to as artifi-
INTELLIGENCE cial intelligence, or AI for short. Artificial Intelligence has no commonly accepted
definitions. One of the first textbooks on AI defined it as “the study
of ideas that enable computers to be intelligent,” 143 which seemed to beg the
question. A later textbook was more specific, “AI is the attempt to get the
computer to do things that, for the moment, people are better at.”120 This
definition is interesting because it implies that once a task is performed successfully
by a computer, then the technique thatmade it possible is no longer
AI, but something mundane. That definition is fairly important to a person
researching AI methods for robots, because it explains why certain topics
suddenly seem to disappear from the AI literature: it was perceived as being
solved! Perhaps the most amusing of all AI definitions was the slogan for
the now defunct computer company, Thinking Machines, Inc., “... making
machines that will be proud of us.”


The term AI is controversial, and has sparked ongoing philosophical debates
on whether a machine can ever be intelligent. As Roger Penrose notes
in his book, The Emperor’s New Mind: “Nevertheless, it would be fair to
say that, although many clever things have indeed been done, the simulation
of anything that could pass for genuine intelligence is yet a long way
off.“115 Engineers often dismiss AI as wild speculation. As a result of such
vehement criticisms, many researchers often label their work as “intelligent
systems” or "knowledge-based systems” in an attempt to avoid the controversy
surrounding the term “AI.”
A single, precise definition of AI is not necessary to study AI robotics. AI
robotics is the application of AI techniques to robots. More specifically, AI
robotics is the consideration of issues traditional covered by AI for application
to robotics: learning, planning, reasoning, problem solving, knowledge
representation, and computer vision. An article in the May 5, 1997 issue
of Newsweek, “Actually, Chess is Easy,” discusses why robot applications
are more demanding for AI than playing chess. Indeed, the concepts of the
reactive paradigm, covered in Chapter 4, influenced major advances in traditional,
non-robotic areas of AI, especially planning. So by studying AI robotics,
a reader interested in AI is getting exposure to the general issues in
AI.