The forgotten janitor who discovered the logic of the mind
The neighborhood was quiet. There was a chill in the air. The scent of Spanish moss hung from the cypress trees. Plumes of white smoke rose from the burning cane fields and stretched across the skies of Terrebonne Parish. The man swung a long leg over a bicycle frame and pedaled off down the street.
It was 1987 in Houma, Louisiana, and he was headed to the Department of Transportation, where he was working the night shift, sweeping floors and cleaning toilets. He was just picking up speed when a car came barreling toward him with a drunken swerve.
A screech shot down the corridor of East Main Street, echoed through the vacant lots, and rang out over the Bayou.
Then silence.
The 60-year-old man lying on the street, as far as anyone knew, was just a janitor hit by a drunk driver. There was no mention of it on the local news, no obituary in the morning paper. His name might have been Anonymous. But it wasn’t.
His name was Peter Putnam. He was a physicist who’d hung out with Albert Einstein, John Archibald Wheeler, and Niels Bohr, and two blocks from the crash, in his run-down apartment, where his partner, Claude, was startled by a screech, were thousands of typed pages containing a groundbreaking new theory of the mind.
“Only two or three times in my life have I met thinkers with insights so far reaching, a breadth of vision so great, and a mind so keen as Putnam’s,” Wheeler said in 1991. And Wheeler, who coined the terms “black hole” and “wormhole,” had worked alongside some of the greatest minds in science.
Robert Works Fuller, a physicist and former president of Oberlin College, who worked closely with Putnam in the 1960s, told me in 2012, “Putnam really should be regarded as one of the great philosophers of the 20th century. Yet he’s completely unknown.”
That word—
unknown—it came to haunt me as I spent the next 12 years trying to find out why.
The American Philosophical Society Library in Philadelphia, with its marbled floors and chandeliered ceilings, is home to millions of rare books and manuscripts, including John Wheeler’s notebooks. I was there in 2012, fresh off writing a physics book that had left me with nagging questions about the strange relationship between observer and observed. Physics seemed to suggest that observers play some role in the nature of reality, yet who or what an observer is remained a stubborn mystery.
Wheeler, who made key contributions to nuclear physics, general relativity, and quantum gravity, had thought more about the observer’s role in the universe than anyone—if there was a clue to that mystery anywhere, I was convinced it was somewhere in his papers. That’s when I turned over a mylar overhead, the kind people used to lay on projectors, with the titles of two talks, as if given back-to-back at the same unnamed event:
Wheeler: From Reality to Consciousness
Putnam: From Consciousness to Reality
Putnam, it seemed, had been one of Wheeler’s students, whose opinion Wheeler held in exceptionally high regard. That was odd, because Wheeler’s students were known for becoming physics superstars, earning fame, prestige, and Nobel Prizes: Richard Feynman, Hugh Everett, and Kip Thorne.
Back home, a Google search yielded images of a very muscly, very orange man wearing a very small speedo. This, it turned out, was the wrong Peter Putnam. Eventually, I stumbled on a 1991 article in the
Princeton Alumni Weekly newsletter called “Brilliant Enigma.” “Except for the barest outline,” the article read, “Putnam’s life is ‘veiled,’ in the words of Putnam’s lifelong friend and mentor, John Archibald Wheeler.
A quick search of old newspaper archives turned up an intriguing article from the
Associated Press, published six years after Putnam’s death. “Peter Putnam lived in a remote bayou town in Louisiana, worked as a night watchman on a swing bridge [and] wrote philosophical essays,” the article said. “He also tripled the family fortune to about $40 million by investing successfully in risky stock ventures.”
The questions kept piling up.
Forty million dollars? I searched a while longer for any more information but came up empty-handed. But I couldn’t forget about Peter Putnam. His name played like a song stuck in my head. I decided to track down anyone who might have known him.
The only paper Putnam ever published was co-authored with Robert Fuller, so I flew from my home in Cambridge, Massachusetts, to Berkeley, California, to meet him. Fuller was nearing 80 years old but had an imposing presence and a booming voice. He sat across from me in his sun-drenched living room, seeming thrilled to talk about Putnam yet plagued by some palpable regret.
Putnam had developed a theory of the brain that “ranged over the whole of philosophy, from ethics to methodology to mathematical foundations to metaphysics,” Fuller told me. He compared Putnam’s work to Alan Turing’s and Kurt Gödel’s. “Turing, Gödel, and Putnam—they’re three peas in a pod,” Fuller said. “But one of them isn’t recognized.” (...)
Phillips Jones, a physicist who worked alongside Putnam in the early 1960s, told me over the phone, “We got the sense that what Einstein’s general theory was for physics, Peter’s model would be for the mind.”
Even Einstein himself was impressed with Putnam. At 19 years old, Putnam went to Einstein’s house to talk with him about Arthur Stanley Eddington, the British astrophysicist. (Eddington performed the key experiment that proved Einstein’s theory of gravity.) Putnam was obsessed with an allegory by Eddington about a fisherman and wanted to ask Einstein about it. Putnam also wanted Einstein to give a speech promoting world government to a political group he’d organized. Einstein—who was asked by plenty of people to do plenty of things—thought highly enough of Putnam to agree.
How could this genius, this Einstein of the mind, just vanish into obscurity? When I asked why, if Putnam was so important, no one has ever heard of him, everyone gave me the same answer: because he didn’t publish his work, and even if he had, no one would have understood it.
“He spoke and wrote in ‘Putnamese,’ ” Fuller said. “If you can find his papers, I think you’ll immediately see what I mean.” (...)
Skimming through the papers I saw that the people I’d spoken to hadn’t been kidding about the Putnamese. “To bring the felt under mathematical categories involves building a type of mathematical framework within which latent colliding heuristics can be exhibited as of a common goal function,” I read, before dropping the paper with a sigh. Each one went on like that for hundreds of pages at a time, on none of which did he apparently bother to stop and explain what the whole thing was really about...
Putnam spent most of his time alone, Fuller had told me. “Because of this isolation, he developed a way of expressing himself in which he uses words, phrases, concepts, in weird ways, peculiar to himself. The thing would be totally incomprehensible to anyone.” (...)
Imagine a fisherman who’s exploring the life of the ocean. He casts his net into the water, scoops up a bunch of fish, inspects his catch and shouts, “A-ha! I have made two great scientific discoveries. First, there are no fish smaller than two inches. Second, all fish have gills.”
The fisherman’s first “discovery” is clearly an error. It’s not that there are no fish smaller than two inches, it’s that the holes in his net are two inches in diameter. But the second discovery seems to be genuine—a fact about the fish, not the net.
This was the Eddington allegory that obsessed Putnam.
When physicists study the world, how can they tell which of their findings are features of the world and which are features of their net? How do we, as observers, disentangle the subjective aspects of our minds from the objective facts of the universe? Eddington suspected that one couldn’t know anything about the fish until one knew the structure of the net.
That’s what Putnam set out to do: come up with a description of the net, a model of “the structure of thought,” as he put it in a 1948 diary entry.
At the time, scientists were abuzz with a new way of thinking about thinking. Alan Turing had worked out an abstract model of computation, which quickly led not only to the invention of physical computers but also to the idea that perhaps the brain, too, was a kind of Turing machine.
Putnam disagreed. “Man is a species of computer of fundamentally different genus than those she builds,” he wrote. It was a radical claim (not only for the mixed genders): He wasn’t saying that the mind isn’t a computer, he was saying it was an entirely
different kind of computer.
A universal Turing machine is a powerful thing, capable of computing anything that can be computed by an algorithm. But Putnam saw that it had its limitations. A Turing machine, by design, performs deductive logic—logic where the answers to a problem are contained in its premises, where the rules of inference are pregiven, and information is never created, only shuffled around. Induction, on the other hand, is the process by which we come up with the premises and rules in the first place. “Could there be some indirect way to model or orient the induction process, as we do deductions?” Putnam asked.
Putnam laid out the dynamics of what he called a universal “general purpose heuristic”—which we might call an “induction machine,” or more to the point, a mind—borrowing from the mathematics of game theory, which was thick in the air at Princeton. His induction “game” was simple enough. He imagined a system (immersed in an environment) that could make one mutually exclusive “move” at a time. The system is composed of a massive number of units, each of which can switch between one of two states. They all act in parallel, switching, say, “on” and “off” in response to one another. Putnam imagined that these binary units could condition one another’s behavior, so if one caused another to turn on (or off) in the past, it would become more likely to do so in the future. To play the game, the rule is this: The first chain of binary units, linked together by conditioned reflexes, to form a self-reinforcing loop emits a move on behalf of the system.
Every game needs a goal. In a Turing machine, goals are imposed from the outside. For true induction, the process itself should create its own goals. And there was a key constraint: Putnam realized that the dynamics he had in mind would only work mathematically if the system had just
one goal governing all its behavior.
That’s when it hit him: The goal is to repeat. Repetition isn’t a goal that has to be programmed in from the outside; it’s baked into the very nature of things—to exist from one moment to the next is to repeat your existence. “This goal function,” Putnam wrote, “appears pre-encoded in the nature of being itself.”
So, here’s the game. The system starts out in a random mix of “on” and “off” states. Its goal is to repeat that state—to stay the same. But in each turn, a perturbation from the environment moves through the system, flipping states, and the system has to emit the right sequence of moves (by forming the right self-reinforcing loops) to alter the environment in such a way that it will perturb the system back to its original state.
Putnam’s remarkable claim was that simply by playing this game, the system will learn; its sequences of moves will become increasingly less random. It will create rules for how to behave in a given situation, then automatically root out logical contradictions among those rules, resolving them into better ones. And here’s the weird thing: It’s a game that can never be won. The system never exactly repeats. But in trying to, it does something better. It adapts. It innovates. It performs induction.
In paper after paper, Putnam attempted to show how his induction game plays out in the human brain, with motor behaviors serving as the mutually exclusive “moves” and neurons as the parallel binary units that link up into loops to move the body. The point wasn’t to give a realistic picture of how a messy, anatomical brain works any more than an abstract Turing machine describes the workings of an iMac. It was not a biochemical description, but a logical one—a “brain calculus,” Putnam called it.
As the game is played, perturbations from outside—photons hitting the retina, hunger signals rising from the gut—require the brain to emit the right sequence of movements to return to its prior state. At first it has no idea what to do—each disturbance is a neural impulse moving through the brain in search of a pathway out, and it will take the first loop it can find. That’s why a newborn’s movements start out as random thrashes. But when those movements don’t satisfy the goal, the disturbance builds and spreads through the brain, feeling for new pathways, trying loop after loop, thrash after thrash, until it hits on one that does the trick.
When a successful move, discovered by sheer accident, quiets a perturbation, it gets wired into the brain as a behavioral rule. Once formed, applying the rule is a matter of deduction: The brain outputs the right move without having to try all the wrong ones first.
But the real magic happens when a contradiction arises, when two previously successful rules, called up in parallel, compete to move the body in mutually exclusive ways. A hungry baby, needing to find its mother’s breast, simultaneously fires up two loops, conditioned in from its history: “when hungry, turn to the left” and “when hungry, turn to the right.” Deductive logic grinds to a halt; the facilitation of either loop, neurally speaking, inhibits the other. Their horns lock. The neural activity has no viable pathway out. The brain can’t follow through with a wired-in plan—it has to create a new one.
How? By bringing in new variables that reshape the original loops into a new pathway, one that doesn’t negate either of the original rules, but clarifies which to use when. As the baby grows hungrier, activity spreads through the brain, searching its history for anything that can break the tie. If it can’t find it in the brain, it will automatically search the environment, thrash by thrash. The mathematics of game theory, Putnam said, guarantee that, since the original rules were in service of one and the same goal, an answer, logically speaking, can always be found.
In this case, the baby’s brain finds a key variable: When “turn left” worked, the neural signal created by the warmth of the mother’s breast against the baby’s left cheek got wired in with the behavior. When “turn right” worked, the right cheek was warm. That extra bit of sensory signal is enough to tip the scales. The brain has forged a new loop, a more general rule: “When hungry, turn in the direction of the warmer cheek.”
New universals lead to new motor sequences, which allow new interactions with the world, which dredge up new contradictions, which force new resolutions, and so on up the ladder of ever-more intelligent behavior. “This constitutes a theory of the induction process,” Putnam wrote.
In notebooks, in secret, using language only he would understand, Putnam mapped out the dynamics of a system that could perceive, learn, think, and create ideas through induction—a computer that could program itself, then find contradictions among its programs and wrangle them into better programs, building itself out of its history of interactions with the world. Just as Turing had worked out an abstract, universal model of the very possibility of computation, Putnam worked out an abstract, universal model of the very possibility of mind. It was a model, he wrote, that “presents a basic overall pattern [or] character of thought in causal terms for the first time.”
Putnam had said you can’t understand another person until you know what fight they’re in, what contradiction they’re working through. I saw before me two stories, equally true: Putnam was a genius who worked out a new logic of the mind. And Putnam was a janitor who died unknown. The only way to resolve a contradiction, he said, is to find the auxiliary variables that forge a pathway to a larger story, one that includes and clarifies both truths. The variables for this contradiction? Putnam’s mother and money.
Image: John Archibald Wheeler, courtesy of Alison Lahnston.[ed. Fascinating. Sounds like part quantum physics and part AI. But it's beyond me.]
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