Read The Idea Factory: Bell Labs and the Great Age of American Innovation Online
Authors: Jon Gertner
In the 1940s and 1950s, the members of Bell Labs’ math department liked to play a game after lunch. “I don’t know who invented this,” Brock McMillan recalls, “but it was called ‘Convergence in Webster.’ Someone was supposed to compose in his head a four-word sentence. And people would try to guess letters and words.” As the men would guess, the creator of the mystery sentence would stand before a blackboard filling in blank spaces (as in Hangman) and telling them whether their guesses fell alphabetically before or after his words. Thus they would gradually converge on the right words, as one might home in on a word he was seeking in
Webster’s Dictionary
. Fifty years later, the men could still recall their favorites. One time a supervisor dropped in, offered to take a turn as the leader, and drew blanks on the blackboard for what eventually turned out to be
You Are All Fired
.
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The mathematicians thought it hilarious.
Shannon was in this world but not of it. Just as he had stood in the doorway when he met Norma at the college party—the one where she had thrown popcorn at him to get his attention, but rather than enter her life he had brought her back to his—he would wander by his colleagues’ offices some afternoons after lunch, and if he saw “Convergence in Webster” in progress, he would lean against the doorjamb and watch.
In a math department that thrived on its collective intelligence—where members of the staff were encouraged to work on papers together rather than alone—this set him apart. But in some respects his solitude was interesting, too, for it had become a matter of some consideration
at the Labs whether the key to invention was a matter of individual genius or collaboration. To those trying to routinize the process of innovation—the lifelong goal of Mervin Kelly, the Labs’ leader—there was evidence both for and against the primacy of the group. So many of the wartime and postwar breakthroughs—the Manhattan Project, radar, the transistor—were clearly group efforts, a compilation of the ideas and inventions of individuals bound together with common purposes and complementary talents. And the phone system, with its almost unfathomable complexity, was by definition a group effort. It was also the case, as Shockley would later point out, that by the middle of the twentieth century the process of innovation in electronics had progressed to the point that a vast amount of multidisciplinary expertise was needed to bring any given project to fruition. “Things are much more complex than they were probably when Mendel was breeding peas, in which case you would put them in a pot and collect the fruits, and then cover up the blossoms and have that suffice,” Shockley said, referring to the nineteenth-century scientist whose work provided the foundation for modern genetics. An effective solid-state group, for example, required researchers with material processing skills, chemical skills, electrical measurement skills, theoretical physics skills, and so forth. It was exceedingly unlikely to find all those talents in a single person.
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And yet Kelly would say at one point, “With all the needed emphasis on leadership, organization and teamwork, the individual has remained supreme—of paramount importance. It is in the mind of a single person that creative ideas and concepts are born.”
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There was an essential truth to this, too—John Bardeen suddenly suggesting to the solid-state group that they should consider working on the hard-to-penetrate surface states on semiconductors, for instance. Or Shockley, mad with envy, sitting in his Chicago hotel room and laying the groundwork for the junction transistor. Or Bill Pfann, who took a nap after lunch and awoke, as if from an edifying dream, with a new method for purifying germanium.
Of course, these two philosophies—that individuals as well as groups were necessary for innovation—weren’t mutually exclusive. It was the individual from which all ideas originated, and the group (or the multiple
groups) to which the ideas, and eventually the innovation responsibilities, were transferred. The handoffs often proceeded in logical progression: from the scientist pursuing with his colleagues a basic understanding in the research department, to the applied scientist working with a team in the development side, to a group of engineers working on production at Western Electric. What’s more, in the right environment, a group or wise colleague could provoke an individual toward an insight, too. In the midst of Shannon’s career, some lawyers in the patent department at Bell Labs decided to study whether there was an organizing principle that could explain why certain individuals at the Labs were more productive than others. They discerned only one common thread: Workers with the most patents often shared lunch or breakfast with a Bell Labs electrical engineer named Harry Nyquist. It wasn’t the case that Nyquist gave them specific ideas. Rather, as one scientist recalled, “he drew people out, got them thinking.” More than anything, Nyquist asked good questions.
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Shannon knew Nyquist, too. And though Shannon worked alone, he would later tell an interviewer that the institution of Bell Labs (its intellectual environment, its people, its freedom, and, most important, the Bell System’s myriad technical challenges) deserved a fair amount of credit for his information theory.
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What the Labs couldn’t take credit for, though, was how Shannon, whether by provocation or intuition, seemed to anticipate a different era altogether. His genius was roughly equivalent with prescience. There was little doubt, even by the transistor’s inventors, that if Shockley’s team at Bell Labs had not gotten to the transistor first, someone else in the United States or in Europe would have soon after. A couple of years, at most.
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With Shannon’s startling ideas on information, it was one of the rare moments in history, an academic would later point out, “where somebody founded a field, stated all the major results, and proved most of them all pretty much at once.”
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Eventually, mathematicians would debate not whether Shannon was ahead of his contemporaries. They would debate whether he was twenty, or thirty, or fifty years ahead.
E
arly in his Bell Labs career, Shannon had begun to conceive of his employer’s system—especially its vast arrangement of relays and switches that automatically connected callers—as more than a communications network. He saw it as an immense computer that was transforming and organizing society. This was not yet a conventional view, though it was one that Shockley, too, would soon adopt. As Shannon put it, the system and its automatic switching mechanisms was “a really beautiful example of a highly complex machine. This is in many ways the most complex machine that man has ever attempted, and in many ways also a most reliable one.” He was also intrigued by the fact that the phone system was built to be efficient and tremendously broad in its sweep but was not built to think in depth. In connecting callers, it did innumerable simple tasks over and over and over again. But he knew that other machines could be built for a contrary purpose, to be deep rather than broad, and he began thinking about how to do so. Soon after Shannon’s information theory was published, he started working on a computer program and a scientific paper for playing chess. “He was a very good chess player,” Shannon’s colleague Brock McMillan recalls. “He clobbered all the rest of us.” But there seemed little point in studying chess at an industrial lab for communications. While preparing for a radio interview
at around that time in Morristown, New Jersey—the town where Shannon and Betty had just moved to an apartment—he scribbled down some responses to the questioner:
Q: You do other things besides analyze communications, though, don’t you, Dr. Shannon? Didn’t I see an article in
Scientific American
by you about a chess-playing machine? Don’t tell me the Laboratories is interested in
chess.
Shannon: No—but interested in potentiality of computer machines. They can solve complex problems in a few minutes.
Q: But how does chess fit into the picture?
Shannon: A test to see what we can do with computing machines.
Q: Would a chess-playing machine of the type you are talking about play perfect
chess?
Shannon: No, make same kind of errors as human players….
Q: Would you say that these computing machines are capable of “thinking”?
Shannon: Depends on how you define “thinking”—memory, decisions, but must all be programmed into the machine.
Q: What sort of things will the Telephone Company use the computers
for?
Shannon: The telephone exchange itself is a type of computer.
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At the time, Shannon hadn’t yet built a machine; computers of the era, even the simplest ones, were bulky and complex, and so he admitted it would be too expensive to use a computer for “so trivial a problem” as chess. But it’s unlikely he actually believed the problem to be trivial, and
not long afterward he did in fact build a primitive chess computer. Shannon’s first paper on the subject—the one from which
Scientific American
adapted an article—happened to be the first paper ever written on chess programming. Much like his work on cryptography and information, it combined philosophical and mathematical elements, exploring the purpose of a chess machine as well as the logical theory behind its possible mechanisms. It also contained something unusual: an explanation that was meant to clarify why computer chess, a radical notion in 1949, could prove useful. “It is hoped that a satisfactory solution of this problem will act as a wedge in attacking other problems of a similar nature and of greater significance.”
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If you could get a computer to play chess, in other words, you could conceivably get it to route phone calls, or translate a language, or make strategic decisions in military situations. You could build “machines capable of orchestrating a melody,” he suggested. And you might be able to construct “machines capable of logical deduction.” Such machines could be useful as well as economical, he offered; they could ultimately replace humans in certain automated tasks.
Almost surely, these justifications for the chess program would have placated his bosses at the Labs, worried as they were that some of their researchers could stray too far from the subject of communications. Regulatory anxiety created a background hum for the top managers at Bell Labs: What if government officials became alert to the fact that the phone monopoly was using its customers’ dollars to fund the research of a game-playing eccentric? Shannon’s offering—a few crumbs of justification—were about as much as he would give. He would acknowledge that building devices like chess-playing machines “might seem a ridiculous waste of time and money. But I think the history of science has shown that valuable consequences often proliferate from simple curiosity.”
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“He never argued his ideas,” Brock McMillan says of Shannon. “If people didn’t believe in them, he ignored those people.”
“W
HAT DO YOU GIVE A GUY
like Claude for Christmas?” his wife, Betty, asks. “He liked Erector Sets, and so I bought the biggest Erector Set I
could find and it was 50 bucks.”
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At first, Shannon began to stay up all night with the Erector Set building small machines. “He built a little turtle that walked around the house,” Betty says. “It would bump into something and back off and walk the other way. And then he built the mouse.” The mouse was named Theseus. It was a small object, built of wood with copper wire whiskers, which was intended to search for a piece of electronic “cheese” within a maze that Shannon also built. Theseus was named in winking recognition of the mythical Greek hero who found a way to navigate a labyrinth ruled by a deadly minotaur.
Shannon did the project at home—just as he had the information paper—thus making it a surprise to almost everyone on the Labs staff when he brought it in.
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But in fact the mouse was far less ingenious than the maze, which was about the size of a small kitchen table and which Shannon had fitted with sliding aluminum panels so its pattern could be easily reconfigured. “I decided that my mouse would be basically a bar magnet, moved by means of an electromagnet under the floor of the maze,” Shannon explained. “The bar magnet, covered by a mouse-like shell, could be turned, and when it hit a wall of the maze could signal a computing circuit. The computer would then cause the mouse to try a different direction.”
Watching the mouse trot through the maze in its first run-through wasn’t exactly breathtaking. Theseus would move slowly through the labyrinth until he hit a wall; he would bump against the wall and then turn in various directions until he finally found an open route. He didn’t move quickly. But he was unerring in ultimately calculating which way to go. What was interesting about Theseus was not that he could successfully navigate the aluminum labyrinth. What was interesting was that he (or, more precisely, the relays underneath the floor of the maze) could learn while he navigated the maze, and could likewise
remember
the location of walls and routes and whether it made sense to turn north, east, west, or south. Therefore, on his second try, Theseus could make it through the maze much more quickly—perhaps in as little as fifteen seconds. Or Shannon could actually pick up Theseus and place him anywhere in the maze and he could find his way out.
Among the researchers at the Labs the mouse was wildly popular. The legal department was less enthusiastic, seeing little value in the patent they obtained for Shannon on the gadget’s circuitry.
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This was, after all, a communications company—and one that was limited by the federal government to the telecommunications business. But complaints aside, Theseus was a boon for the Labs in making Shannon a minor celebrity in a way that information theory never had. The Labs produced a short movie about the maze and the mouse, hosted by a thin and dapper Shannon, who narrated in his folksy midwestern manner. And soon
Time
magazine came calling, too. “Theseus Mouse is cleverer than Theseus the Greek,” the magazine’s writer noted, “who could not trust his memory but had to unwind a ball of string to guide him out of the labyrinth.”
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In large part, this observation matched Shannon’s intuition that machines would someday be smarter than men in some respects. Shannon often rhapsodized about the human brain and the inimitable processing power of its billions of neurons. But he believed without question that machines had the potential to do calculations and perform logical operations and store numbers with a speed, efficiency, and accuracy that would soon dwarf our own. It was only a matter of time. Often, he said, he was rooting for the machines.