Some challenges and grand challenges for computational intelligence

Abstract

When the terms “intelligence” or “intelligent” are used by scientists, they are referring to a large collection of human cognitive behaviors— people thinking. When life scientists speak of the intelligence of animals, they are asking us to call to mind a set of human behaviors that they are asserting the animals are (or are not) capable of. When computer scientists speak of artificial intelligence, machine intelligence, intelligent agents, or (as I chose to do in the title of this essay) computational intelligence, we are also referring to that set of human behaviors. Although intelligence means people thinking, we might be able to replicate the same set of behaviors using computation. Indeed, one branch of modern cognitive psychology is based on the model that the human mind and brain are complex computational “engines,” that is, we ourselves are examples of computational intelligence. 2. Turing’s Vision and the Turing Test for Humanoid Behavior The idea, of course, is not new. It was discussed by Turing in the 1940s. In the play about Turing’s life, Breaking the Code [Whitemore 1987], Turing is shown visiting his old grammar school and delivering a talk to the boys, in which he offers a vision of the thinking computer. The memories of those of Turing’s colleagues of the 1940s who are still alive confirm that he spoke often of this vision. In 1950, he wrote of it, in a famous article [Turing 1950], in which he proposed a test (now called the Turing Test (TT)) for computational intelligence. In the test, a human judgment must be made concerning whether a set of observed behaviors is sufficiently similar to human behaviors that the same word—intelligent—can justifiably be used. The judgment is about behavior not mechanism. Computers are not like human brains, but if they perform the same acts and one performer (the human) is labeled intelligent, then the other must be labeled intelligent also. I have always liked the Turing Test because it gave a clear and tangible vision, was reasonably objective, and made concrete the tie to human behavior by using the unarticulated criteria of a human judge. Turing Award winner Jim Gray, who works in fields of Computer Science other than AI, appears to agree. His list of challenges for the future includes: “The Turing test: Win the imitation game 30% of the time.” Significantly, he adds: “Read and understand as well as a human. Think and write as well as a human,” [Gray 2003]. I will have more to say about necessary conditions for these human activities later. But there are problems with the Turing Test (TT). Human intelligence is very multidimensional. However, the judge must fuse all of these dimensions into a