Part 20

This doesn’t sound like too big a problem. However, since there are twelve on-off signals to be considered, and since each has two possible states, there are 4,096 possible missile combinations. Not all these are probable, of course, but there is still sufficient variation to make it humanly impossible to check all of them and close a firing switch in the split second the control center can allow.

The answer lies in putting Boolean algebra on the job, with a system of gates and inverters capable of juggling the multiplicity of combinations. Then when the word comes requesting a missile launch, the computer handles the job in microseconds without straining itself unduly.

Just as Shannon pointed out twenty-five years ago, switching philosophy can be explained best by Boolean logic, and the method can be used not only to implement a particular circuit, but also to actually design the circuit in the first place. A simple example of this can be shown with the easy-to-understand AND and OR gates. A technician experimenting with an AND gate finds that if he simply reverses the direction of current, he changes the gate into an OR gate. This might come as a surprise to him if he is unfamiliar with Boolean logic, but a logician with no understanding of electrical circuits could predict the result simply by studying the truth tables for AND and OR.

Reversing the polarity is equivalent to changing a 1 to a 0 and vice versa. If we do this in the AND gate table, we should not be surprised to find that the result looks exactly like the OR table! It acts like it too, as the technician found out.

Boolean logic techniques can be applied to existing circuits to improve and/or simplify them. Problems as simple as wiring a light so that it can be turned on and off from two or more locations, and those as complex as automating a factory, yield readily to the simple rules George Boole laid down more than a hundred years ago.

Watching a high-speed electronic digital computer solve mathematical problems, or operate an industrial control system with speed and accuracy impossible for human monitors, it is difficult to believe that the whole thing hinges on something as simple as switches that must be either open or closed. If Leibnitz were alive, he could well take this as proof of his contention that there was cosmological significance in the concept of 1 and 0. Maybe there is, after all!

Industrial Electronic Engineering & Maintenance

“Luckily I brought along a ‘loaner’ for you to use while I repair your computer.” ]

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“Whatever that be which thinks, understands, wills, and acts, it is something celestial and divine.”

—Cicero

6: The Electronic Brain

The idea of a man-made “brain” is far from being new. Back in 1851, Dr. Alfred Smee of England proposed a machine made up of logic circuits and memory devices which would be able to answer any questions it was asked. Doctor Smee was a surgeon, keenly interested in the processes of the mind. Another Britisher, H. G. Wells, wrote a book called Giant Brain in 1938 which proposed much the same thing: a machine with all knowledge pumped into it, and capable of feeding back answers to all problems.

If it was logical to credit “human” characteristics to the machines man contrived, the next step then was to endow the machine with the worst of these attributes. In works including Butler’s Erewhon, the diabolical aspects of an intelligent machine are discussed. The Lionel Britton play, Brain, produced in 1930, shows the machine gradually becoming the master of the race. A more physical danger from the artificial brain is the natural result of giving it a body as well. We have already mentioned Čapek’s R.U.R. and the Ambrose Bierce story about a chess-playing robot without a built-in sense of humor, who strangles the human being who beats him at a game. With these stories as models, other writers have turned out huge quantities of work involving mechanical brains capable of all sorts of mischief. Most of these authors were not as well-grounded scientifically as the pioneering Dr. Smee who admitted sadly that his “brain” would indeed be a giant, covering an area about the size of London!

The idea of the giant brain was given new lease by the early electronic computers that began appearing in the 1940’s. These vacuum-tube and mechanical-relay machines with their rows of cabinets and countless winking lights were seized on gleefully by contemporary writers, and the “brain” stories multiplied gaudily.

Many of the acts of these fictional machines were monstrous, and most of the stories were calculated to make scientists ill. Many of these gentlemen said the only correct part of the name “giant brain” was the adjective; that actually the machine was an idiot savant, a sort of high-speed moron. This opinion notwithstanding, the name stuck. One scholar says that while it is regrettable that such a vulgar term has become so popular, it is hardly worth while campaigning against its use.

An amusing contemporary fiction story describes an angry crowd storming a laboratory housing a “giant brain,” only to be placated by a calm, sensibly arguing scientist. The mob dispersed, he goes back inside and reports his success to the machine. The “brain” is pleased, and issues him his next order.

“Nonsense!” scoff most computer people. A recent text on operation of the digital computer says, “Where performance comparable with that of the human brain is concerned, man need have little fear that he will ever be replaced by this machine. It cannot think in any way comparable to a human being.” Note the cautious use of “little,” however.

Another authority admits that the logic machines of the monk Ramón Lull were very clever in their proof of God’s existence, but points out that the monk who invented them was far cleverer since no computer has ever invented a monk who could prove anything at all!

The first wave of ridiculous predictions has run its course and been followed by loud refutations. Now there is a third period of calmer and more sensible approach. A growing proportion of scientists take a middle-of-the-stream attitude, weighing both sides of the case for the computer, yet some read like science fiction.

Cyberneticist Norbert Wiener, more scientist than fictioneer, professes to foresee computerized robots taking over from their masters, much as a Greek slave once did. Mathematician John Williams of the Rand Corporation thinks that computers can, and possibly will, become more intelligent than men.

Equally reputable scientists take the opposite view. Neuro-physiologist Gerhard Werner of Cornell Medical College doubts that computers can ever match the creativity of man. He seems to share the majority view today, though many who agree will add, tongue in cheek, that perhaps we’d better keep one hand on the wall plug just in case.

Thinking Defined

The first step in deciding whether or not the computer thinks is to define thinking. Far from being a simple task, this definition turns out to be a slippery thing. In fact, if the computer has done no more than demand this sort of reappraisal of the human brain’s working, it has justified its existence. Webster lists meanings for “think” under two headings, for the transitive and intransitive forms of the verb. These meanings, respectively, start out with “To form in the mind,” and “To exercise the powers of judgment ... to reflect for the purpose of reaching a conclusion.”

Even a fairly simple computer would seem to qualify as a thinker by these yardsticks. The storing of data in a computer memory may be analogous to forming in the mind, and manipulating numbers to find a square root certainly calls for some sort of judgment. Learning is a part of thinking, and computers are proving that they can learn—or at least be taught. Recall of this learning from the memory to solve problems is also a part of the thinking process, and again the computer demonstrates this capability.

One early psychological approach to the man-versus-machine debate was that of classifying living and nonliving things. In Outline of Psychology, the Englishman William McDougall lists seven attributes of life. Six of these describe “goal-seeking” qualities; the seventh refers to the ability to learn. In general, psychologist McDougall felt that purposive behavior was the key to the living organism. Thus any computer that is purposive—and any commercial model had better be!—is alive, in McDougall’s view. A restating of the division between man and machine is obviously in order.

Dr. W. Ross Ashby, a British scientist now working at the University of Illinois, defines intelligence as “appropriate selection” and goal-seeking as the intelligent process par excellence, whether the selecting is done by a human being or by a machine. Ashby does split off the “non goal-seeking” processes occurring in the human brain as a distinct class: “natural” processes neither good nor bad in themselves and resulting from man’s environment and his evolution.

Intelligence, to Ashby, who long ago demonstrated a mechanical “homeostat” which showed purposive behavior, is the utilization of information by highly efficient processing to achieve a high intensity of appropriate selection. Intelligent is as intelligent does, no distinction being made as to man or machine. Humanoid and artificial would thus be meaningless words for describing a computer. Ashby makes another important point in that the intelligence of a brain or a machine cannot exceed what has been put into it, unless we admit the workings of magic. Ashby’s beliefs are echoed in a way by scientist Oliver Selfridge of Lincoln Laboratory. Asked if a machine can think, Selfridge says, “Certainly; although the machine’s intelligence has an elusive, unnatural quality.”