The Turing Test, proposed by Alan Turing TURING TEST (1950), was designed to provide a satisfactory operational definition of intelligence. A computer passes the test if a human interrogator, after posing some written questions, cannot tell whether the written responses come from a person or from a computer. For now, we note that programming a computer to pass a rigorously applied test provides plenty to work on. The computer would need to possess the following capabilities:
• natural language processing to enable it to communicate successfully in English;
• knowledge representation to store what it knows or hears;
• automated reasoning to use the stored information to answer questions and to draw new conclusions;
• machine learning to adapt to new circumstances and to detect and extrapolate patterns.
Turing’s test deliberately avoided direct physical interaction between the interrogator and the
computer, because physical simulation of a person is unnecessary for intelligence. However,
the so-called total Turing TOTAL TURING TEST Test includes a video signal so that the interrogator can test the subject’s perceptual abilities, as well as the opportunity for the interrogator to pass physical objects “through the hatch.” To pass the total Turing Test, the computer will need
• computer vision to perceive objects, and
• robotics to manipulate objects and move about.
These six disciplines compose most of AI, and Turing deserves credit for designing a test
that remains relevant 60 years later. Yet AI researchers have devoted little effort to passing
the Turing Test, believing that it is more important to study the underlying principles of intelligence than to duplicate an exemplar. The quest for “artificial flight” succeeded when the Wright brothers and others stopped imitating birds and started using wind tunnels and learning about aerodynamics. Aeronautical engineering texts do not define the goal of their field as making “machines that fly so exactly like pigeons that they can fool even other pigeons.”
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