How do machines think? Norbert Wiener answers

He was among the first to formalize the idea that intelligent behavior results from feedback mechanisms that can be modeled by machines. His 1948 book, Cybernetics: Or Control and Communication in the Animal and the Machine, from which the quotes in this article are taken, remains a foundational work in computer science and artificial intelligence theory.

• Since Leibniz there has perhaps been no man who has had a full command of all the intellectual activity of his day. Since that time, science has been increasingly the task of specialists, in fields which show a tendency to grow progressively narrower. A century ago there may have been no Leibniz, but there was a Gauss, a Faraday, and a Darwin. Today there are few scholars who can call themselves mathematicians or physicists or biologists without restriction. A man may be a topologist or an acoustician or a coleopterist. He will be filled with the jargon of his field, and will know all its literature and all its ramifications, but, more frequently than not, he will regard the next subject as something belonging to his colleague three doors down the corridor, and will consider any interest in it on his own part as an unwarrantable breach of privacy.

The issue raised in this quote remains relevant today. Wiener himself saw a practical solution in creating multidisciplinary teams made up of specialists from different fields who thoroughly study the principles and terminology of their colleagues’ sciences. However, it’s also worth noting that one possible way to overcome the limitations of narrow specialization is artificial intelligence. AI can become the very tool that helps specialists quickly and effectively consult on any question beyond their expertise. While Norbert Wiener didn’t state this explicitly, it’s quite possible that the problem of narrow specialization in science was one of the inspirations that led him to delve into computer science and cybernetics.

• If I were to choose a patron saint for cybernetics out of the history of science, I should have to choose Leibniz. The philosophy of Leibniz centers about two closely related concepts —­ that of a universal symbolism and that of a calculus of reasoning. From these are descended the mathematical notation and the symbolic logic of the present day. Now, just as the calculus of arithmetic lends itself to a mechanization progressing through the abacus and the desk computing machine to the ultrarapid computing machines of the present day, so the calculus ratiocinator of Leibniz contains the germs of the machina ratiocinatrix, the reasoning machine. Indeed, Leibniz himself, like his predecessor Pascal, was interested in the construction of computing machines in the metal. It is therefore not in the least surprising that the same intellectual impulse which has led to the development of mathematical logic has at the same time led to the ideal or actual mechanization of processes of thought.

We believe Norbert Wiener’s reflections serve as strong evidence that the idea of creating artificial intelligence has deep scientific roots, rather than being merely a product of 20th-century science fiction.

1. That the central adding and multiplying apparatus of the computing machine should be numerical, as in an ordinary adding machine, rather than on a basis of measurement, as in the Bush differential analyzer.
2. That these mechanisms, which are essentially switching devices, should depend on electronic tubes rather than on gears or mechanical relays, in order to secure quicker action.
3. That, in accordance with the policy adopted in some existing apparatus of the Bell Telephone Laboratories, it would probably be more economical in apparatus to adopt the scale of two for addition and multiplication, rather than the scale of ten.
4. That the entire sequence of operations be laid out on the machine itself so that there should be no human intervention from the time the data were entered until the final results should be taken off, and that all logical decisions necessary for this should be built into the machine itself.
5. That the machine contain an apparatus for the storage of data which should record them quickly, hold them firmly until erasure, read them quickly, erase them quickly, and then be immediately available for the storage of new material.

The five principles of computer design mentioned above were formulated by Wiener shortly before the United States entered World War II. Although Wiener himself never claimed priority for defining the principles of the modern computer, in essence, that is exactly what he did. With updates reflecting technological progress, Wiener’s five principles are still in use today.

• In any combined use of means of computation, as in any combination of chemical reactions, it is the slowest which gives the order of magnitude of the time constants of the entire system. It is thus advantageous, as far as possible, to remove the human element from any elaborate chain of computation and to introduce it only where it is absolutely unavoidable, at the very beginning and the very end. Under these conditions, it pays to have an instrument for the change of the scale of notation, to be used initially and finally in the chain of computations, and to perform all intermediate processes on the binary scale. The ideal computing machine must then have all its data inserted at the beginning, and must be as free as possible from human interference to the very end.

One could say that Norbert Wiener’s words above serve as a guiding beacon for AI developers. Among other goals, they strive to make human interaction with AI as simple as possible, teaching machines to understand even the most vague and imprecise queries.

• It is a noteworthy fact that the human and animal nervous systems, which are known to be capable of the work of a computation system, contain elements which are ideally suited to act as relays. These elements are the so-called neurons or nerve cells. While they show rather complicated properties under the influence of electrical currents, in their ordinary physiological action they conform very nearly to the “all-­ or-­ none” principle; that is, they are either at rest, or when they “fire” they go through a series of changes almost independent of the nature and intensity of the stimulus. There is first an active phase, transmitted from one end to the other of the neuron with a definite velocity, to which there succeeds a refractory period during which the neuron is either incapable of being stimulated, or at any rate is not capable of being stimulated by any normal, physiological process. At the end of this effective refractory period, the nerve remains inactive, but may be stimulated again into activity. Thus the nerve may be taken to be a relay with essentially two states of activity: firing and repose.

One of the big breakthroughs by Norbert Wiener and the pioneers of cybernetics was showing how the human nervous system and computers are actually quite similar in how they’re structured. Today, many developers of advanced “thinking” machines and AI look to nature for inspiration, trying to mimic the way natural intelligence works when designing their systems.

• Let it be remarked parenthetically that an important difference between the way in which we use the brain and the machine is that the machine is intended for many successive runs, either with no reference to each other, or with a minimal, limited reference, and that it can be cleared between such runs; while the brain, in the course of nature, never even approximately clears out its past records. Thus the brain, under normal circumstances, is not the complete analogue of the computing machine but rather the analogue of a single run on such a machine.

Building on the idea mentioned earlier, it’s clear that Norbert Wiener was well aware of the limitations in comparing the human brain to a computing machine. In fact, as this quote shows, he warned against trying to simply copy these “natural computers” without considering their complexity.

• It has long been clear to me that the modern ultra-rapid computing machine was in principle an ideal central nervous system to an apparatus for automatic control; and that its input and output need not be in the form of numbers or diagrams but might very well be, respectively, the readings of artificial sense organs, such as photoelectric cells or thermometers, and the performance of motors or solenoids. With the aid of strain gauges or similar agencies to read the performance of these motor organs and to report, to “feed back,” to the central control system as an artificial kinesthetic sense, we are already in a position to construct artificial machines of almost any degree of elaborateness of performance. Long before Nagasaki and the public awareness of the atomic bomb, it had occurred to me that we were here in the presence of another social potentiality of unheard of importance for good and for evil. The automatic factory and the assembly line without human agents are only so far ahead of us as is limited by our willingness to put such a degree of effort into their engineering as was spent, for example, in the development of the technique of radar in the Second World War. I have said that this new development has unbounded possibilities for good and for evil… It gives the human race a new and most effective collection of mechanical slaves to perform its labor. Such mechanical labor has most of the economic properties of slave labor, although, unlike slave labor, it does not involve the direct demoralizing effects of human cruelty. However, any labor that accepts the conditions of competition with slave labor accepts the conditions of slave labor, and is essentially slave labor. The key word of this statement is competition. It may very well be a good thing for humanity to have the machine remove from it the need of menial and disagreeable tasks, or it may not. I do not know. It cannot be good for these new potentialities to be assessed in the terms of the market, of the money they save… Perhaps I may clarify the historical background of the present situation if I say that the first industrial revolution, the revolution of the “dark satanic mills,” was the devaluation of the human arm by the competition of machinery. There is no rate of pay at which a United States pick-­ and-­ shovel laborer can live which is low enough to compete with the work of a steam shovel as an excavator. The modern industrial revolution is similarly bound to devalue the human brain, at least in its simpler and more routine decisions. Of course, just as the skilled carpenter, the skilled mechanic, the skilled dressmaker have in some degree survived the first industrial revolution, so the skilled scientist and the skilled administrator may survive the second. However, taking the second revolution as accomplished, the average human being of mediocre attainments or less has nothing to sell that it is worth anyone’s money to buy.

As we can see, Norbert Wiener believed that by the mid-20th century, humanity had reached a level where it could create machines that fit the definition of specialized artificial intelligence—machines capable of freeing people almost entirely from physical labor. The only real question was the amount of resources invested in the project. Of course, with the benefit of hindsight, Wiener’s view might seem overly optimistic. But if we consider it as a forecast, it’s clear we’re now very close to making that vision a reality. And since the “father of cybernetics” proved to be a technical visionary, it’s worth paying attention to his call to carefully consider the social and economic consequences of the widespread introduction of these “thinking machines.”

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