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By Root 1203 0

Computers can learn, for example, empirically the rule that it is better in the beginning game to control the center of the chessboard than the periphery. The ten best chess players in the world still have nothing to fear from any present computer. But the situation is changing. Recently a computer for the first time did well enough to enter the Minnesota State Chess Open. This may be the first time that a non-human has entered a major sporting event on the planet Earth (and I cannot help but wonder if robot golfers and designated hitters may be attempted sometime in the next decade, to say nothing of dolphins in free-style competition). The computer did not win the Chess Open, but this is the first time one has done well enough to enter such a competition. Chess-playing computers are improving extremely rapidly.

I have heard machines demeaned (often with a just audible sigh of relief) for the fact that chess is an area where human beings are still superior. This reminds me very much of the old joke in which a stranger remarks with wonder on the accomplishments of a checker-playing dog. The dog’s owner replies, “Oh, it’s not all that remarkable. He loses two games out of three.” A machine that plays chess in the middle range of human expertise is a very capable machine; even if there are thousands of better human chess players, there are millions who are worse. To play chess requires strategy, foresight, analytical powers, and the ability to cross-correlate large numbers of variables and to learn from experience. These are excellent qualities in those whose job it is to discover and explore, as well as those who watch the baby and walk the dog.

With this as a more or less representative set of examples of the state of development of machine intelligence, I think it is clear that a major effort over the next decade could produce much more sophisticated examples. This is also the opinion of most of the workers in machine intelligence.

In thinking about this next generation of machine intelligence, it is important to distinguish between self-controlled and remotely controlled robots. A self-controlled robot has its intelligence within it; a remotely controlled robot has its intelligence at some other place, and its successful operation depends upon close communication between its central computer and itself. There are, of course, intermediate cases where the machine may be partly self-activated and partly remotely controlled. It is this mix of remote and in situ control that seems to offer the highest efficiency for the near future.

For example, we can imagine a machine designed for the mining of the ocean floor. There are enormous quantities of manganese nodules littering the abyssal depths. They were once thought to have been produced by meteorite infall on Earth, but are now believed to be formed occasionally in vast manganese fountains produced by the internal tectonic activity of the Earth. Many other scarce and industrially valuable minerals are likewise to be found on the deep ocean bottom. We have the capability today to design devices that systematically swim over or crawl upon the ocean floor; that are able to perform spectrometric and other chemical examinations of the surface material; that can automatically radio back to ship or land all findings; and that can mark the locales of especially valuable deposits—for example, by low-frequency radio-homing devices. The radio beacon will then direct great mining machines to the appropriate locales. The present state of the art in deep-sea submersibles and in spacecraft environmental sensors is clearly compatible with the development of such devices. Similar remarks can be made for off-shore oil drilling, for coal and other subterranean mineral mining, and so on. The likely economic returns from such devices would pay not only for their development, but for the entire space program many times over.

When the machines are faced with particularly difficult situations, they can be programmed to recognize that the situations are beyond their abilities and to inquire of