The Information - James Gleick [114]
“They are growing with fearful speed,” declared Time in its year-end issue. “They started by solving mathematical equations with flash-of-lightning rapidity. Now they are beginning to act like genuine mechanical brains.”♦ Wiener encouraged the speculation, if not the wild imagery:
Dr. Wiener sees no reason why they can’t learn from experience, like monstrous and precocious children racing through grammar school. One such mechanical brain, ripe with stored experience, might run a whole industry, replacing not only mechanics and clerks but many of the executives too.…
As men construct better calculating machines, explains Wiener, and as they explore their own brains, the two seem more & more alike. Man, he thinks, is recreating himself, monstrously magnified, in his own image.
Much of the success of his book, abstruse and ungainly as it was, lay in Wiener’s always returning his focus to the human, not the machine. He was not as interested in shedding light on the rise of computing—to which, in any case, his connections were peripheral—as in how computing might shed light on humanity. He cared profoundly, it turned out, about understanding mental disorders; about mechanical prostheses; and about the social dislocations that might follow the rise of smart machinery. He worried that it would devalue the human brain as factory machinery had devalued the human hand.
He developed the human-machine parallels in a chapter titled “Computing Machines and the Nervous System.” First he laid out a distinction between two types of computing machines: analog and digital, though he did not yet use those words. The first type, like the Bush Differential Analyzer, represented numbers as measurements on a continuous scale; they were analogy machines. The other kind, which he called numerical machines, represented numbers directly and exactly, as desk calculators did. Ideally, these devices would use the binary number system for simplicity. For advanced calculations they would need to employ a form of logic. What form? Shannon had answered that question in his master’s thesis of 1937, and Wiener offered the same answer:
the algebra of logic par excellence, or the Boolean algebra. This algorithm, like the binary arithmetic, is based on the dichotomy, the choice between yes and no, the choice between being in a class and outside.♦
The brain, too, he argued, is at least partly a logical machine. Where computers employ relays—mechanical, or electromechanical, or purely electrical—the brain has neurons. These cells tend to be in one of two states at any given moment: active (firing) or at rest (in repose). So they may be considered relays with two states. They are connected to one another in vast arrays, at points of contact known as synapses. They transmit messages. To store the messages, brains have memory; computing machines, too, need physical storage that can be called memory. (He knew well that this was a simplified picture of a complex system, that other sorts of messages, more analog than digital, seemed to be carried chemically by hormones.) Wiener suggested, too, that functional disorders such as “nervous breakdowns” might have cousins in electronics. Designers of computing machines might need to plan for untimely floods of data—perhaps the equivalent of “traffic problems and overloading in the nervous system.”♦
Brains and electronic computers both use quantities of energy in performing their