A Tribute to Peter Putnam

An implication of the philosophical framework I have tried to articulate is that every intelligence leaves a trace. What we experience from the inside — the felt texture of perception, the recursive awareness of our own awareness, the striving that drives our mattering projects — expresses itself outward through action, and those actions broadcast signals. Upon death, the inside experience ceases. No future observer can recapture what it was like to be that particular arrangement of matter perceiving itself perceiving. But external traces of signal may remain, embedded in artifacts, in texts, in the memories of those who received the signal while its source still lived. The mattering projects of the dead can persist — at least in attenuated form — for as long as others choose to pay the energy and entropy costs of storing and retransmitting that signal. It is in that spirit that I write today about Peter Putnam.

Amanda Gefter's extraordinary article "Finding Peter Putnam," published in Nautilus on June 17, 2025, tells the story of a physicist who spent decades working out a theory of how minds work — and who then vanished into obscurity, his thousands of pages of manuscripts boxed up in a Louisiana apartment, his death by drunk driver in 1987 unnoticed by the world. Gefter spent twelve years piecing together Putnam's story and his ideas. Her article has reintroduced his signal to the world. This essay attempts to amplify it further, to connect Putnam's theoretical project to questions that feel newly urgent as we coordinate across the boundary between biological and artificial intelligence, and to imagine what this generous, brilliant man might have thought.

A Life in Brief

Peter Putnam was born in 1927 in Bratenahl, Ohio, to wealth he would spend most of his life trying to escape. His father was a corporate lawyer; his mother, Mildred Andrews Putnam, was a formidable woman who taught her sons a parable about a boy named Ikey whose father let him fall from the fireplace mantle after promising to catch him. The moral: Never trust anyone. Not even us.

When Putnam's older brother Johnny — the golden child, the fighter pilot — died in World War II, Peter became the sole heir to a fortune he experienced as a trap. He studied physics at Princeton, where John Archibald Wheeler became his mentor. Wheeler, who coined "black hole" and "wormhole" and worked with Einstein and Bohr, recognized something exceptional in his young student. "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.

But Putnam's mother cast a shadow over every opportunity. When Wheeler tried to bring Putnam back to Princeton, Mildred intervened — offering donations, arranging meetings, engineering what she imagined as assistance but what Putnam experienced as contamination. How could he know whether Wheeler's interest was genuine or purchased? The lesson of Ikey, branded into his neural circuitry since childhood, made trust impossible. Putnam turned down positions, rejected book contracts, fled institutions he suspected his mother had corrupted.

By 1975, he had abandoned academic life entirely. He joined Volunteers in Service to America (VISTA) with his partner, Claude DeBrew — an African American ex-Army major he had met at the Apollo Theater in Harlem in 1963 — and moved to Houma, Louisiana. There, working as a janitor and night watchman, he devoted himself to civil rights organizing, establishing a nonprofit to help the black community gain political representation. He gave away his inheritance, channeling tens of millions into public sculpture and environmental conservation. When he died — hit by a drunk driver while bicycling to his janitorial shift — the check from his estate to the Nature Conservancy was the largest single gift the organization had ever received.

If any of this is moving to you, please go read the entirety of Amanda Gefter's article. There are many additional details that are even more moving.

Meanwhile, in filing cabinets in Rochester, New York, lay thousands of pages of manuscripts that his friend Coleman Clarke had rescued from a Cleveland warehouse. These pages contained a theory of mind that Wheeler believed could change how we understand consciousness, intelligence, and the nature of reality itself.

The Induction Machine

Gefter's article — and the archival website that has since made Putnam's manuscripts available online — allows us to reconstruct the core of Putnam's theoretical project.

In the 1940s and 1950s, the comparison between brains and Turing machines captivated scientists. Alan Turing had shown that a simple abstract device — a tape, a read/write head, a finite set of states — could compute anything computable. Perhaps the brain was such a device, running programs, following algorithms.

Putnam disagreed. "Man is a species of computer of fundamentally different genus than those she builds," he wrote. The claim was radical: not that minds aren't computational, but that they compute in a fundamentally different way.

Turing machines perform deduction. They take premises and rules of inference as inputs and derive conclusions. The answers are contained in the setup; the machine merely unfolds what is implicit. But where do the premises come from? Where do the rules originate? That is induction — the process by which minds generate new knowledge, new categories, new ways of parsing the world. "Could there be some indirect way to model or orient the induction process, as we do deductions?" Putnam asked.

His answer was what we might call an "induction machine" — a system that creates its own rules through interaction with the world. He laid out the dynamics using game theory. Imagine a system composed of binary units (neurons, in the brain's case) that can switch between states and condition one another's behavior. The system can make one "move" at a time — one motor action. Its environment perturbs it constantly. And it has just one goal: to repeat. To persist. To return to its prior state despite the chaos.

This goal, Putnam recognized, need not be programmed from outside. Persistence is baked into existence itself. To exist from one moment to the next is already to repeat. The goal function, as he put it, "appears pre-encoded in the nature of being itself."

The game cannot be won. The system never exactly repeats. But in trying to, it does something better: it learns. When a random action happens to quiet a perturbation — when flailing happens to bring the mother's breast within reach — that action gets wired in as a rule. And when two previously successful rules conflict — when "turn left when hungry" and "turn right when hungry" both fire at once — the system cannot deduce its way forward. It must search for new variables that break the tie. Perhaps warmth on the left cheek tipped the scales before; perhaps warmth on the right cheek did so another time. The system forges a new, more general rule: "Turn toward the warmer cheek."

Here is what strikes me most about Putnam's framework: new rules generate new behaviors, which generate new interactions with the world, which dredge up new contradictions, which force new resolutions. The system climbs a ladder of increasingly abstract behavior — specific reflexes give way to context-dependent responses, which give way to general concepts. Each level emerges from integrating over the conflicts at the level below. The microscopic details of particular sensorimotor contingencies get absorbed into effective descriptions that operate at longer timescales and broader contexts.

This ascending hierarchy — from fast, local reflexes to slow, global concepts — has a structure that physicists would recognize. In the renormalization group (RG) framework (developed by Leo Kadanoff, Kenneth Wilson, and others), one studies how a system's effective description changes as one "zooms out" from microscopic to macroscopic scales. Short-distance fluctuations get integrated out; what remains is an effective theory capturing the physics relevant at larger scales. Different microscopic starting points can flow to the same macroscopic behavior — that's universality.

Putnam's induction machine exhibits something like this structure:

• Low-level neural loops handling specific sensorimotor contingencies correspond to the UV (microscopic) regime — fast dynamics, local context, high-dimensional state space.
• Conflict resolution that creates more general rules corresponds to integrating out fast degrees of freedom — the details of particular instances get absorbed into effective descriptions.
• Progressive abstraction toward concepts corresponds to flow toward IR (macroscopic) fixed points — slower dynamics, broader context, compressed representations.
• Universality appears in the convergence of different specific experiences onto the same abstract category — different microscopic histories flowing to equivalent macroscopic behavior.

Putnam did not use this language; the renormalization group was still being developed when he wrote his major papers in the 1960s. But the structural parallel is striking. His induction machine describes how minds build effective theories of the world at multiple scales, with each scale emerging from the integration of conflicts at the scale below.

The key papers that articulate this framework are now available online. The most accessible are:

• Outline of a Functional Model of the Nervous System (1963)
• Outline of a Functional Model of the Nervous System, co-authored with Robert Fuller (1964)
• On the Origin of Order in Behavior, published in General Systems (1966) — the only paper Putnam published in his lifetime
• Memo for Wheeler: Link Syntax to Subjectivity (1966)
• Mathematics of Brain Modeling (1974)
• Some Comments on an Aspect of the Everett-Wheeler Model (1970)

For additional context, see the commentary on Putnam's model written by Robert Fuller, Barry Spinello, Gary Aston-Jones, and Amanda Gefter herself.

What Putnam Anticipated

Putnam's ideas have proven remarkably prescient. The model of the brain that has emerged in cognitive science and computational neuroscience over the past three decades increasingly resembles what Putnam sketched in the 1960s.

Consider the parallels:

Hebbian plasticity — the idea that neurons that fire together wire together — was central to Putnam's model, though he generalized it to include inhibitory connections as well as excitatory ones. This "Neural Conditioned Reflex Principle" is now standard in computational neuroscience.

Embodied cognition — the idea that thinking is not representation but action, that motor behavior is not the output of cognition but its substrate — was anticipated in Putnam's claim that "only that which makes a difference in determining the order" of the behavioral chain "can be perceived, or subjectively experienced." Mind is not a spectator watching the body; mind is what the body does when it resolves conflicts.

Predictive processing and active inference — the idea that brains minimize prediction error by either updating their models or acting on the world — echo Putnam's game-theoretic framing. His induction machine seeks to return to its prior state, to predict and to confirm predictions, and learns precisely when its predictions fail. Karl Friston's Free Energy Principle, which I discussed in A More Perfect Union, formalizes much of this intuition.

Criticality and scale-free dynamics — the hypothesis that the brain operates near critical points, at the boundary between ordered and disordered phases — has received substantial empirical support in recent years. Researchers have applied renormalization group methods directly to neural data, finding signatures of scale-invariant activity across brain regions. A 2022 paper in Physical Review Letters by Tiberi and colleagues adapted RG techniques to the Wilson-Cowan equations for neural networks, finding evidence for what they call "Gell-Mann–Low criticality." Recent work on mouse brain recordings has found that sensory cortices operate closer to the edge of instability than higher-order integrative areas — suggesting that the functional hierarchy of brain regions may itself reflect something like RG flow, with information moving from critical (UV-like) sensory areas toward more stable (IR-like) integrative regions.

Hierarchical processing and cortical gradients — the observation that the brain exhibits systematic gradients from sensory to association cortex, with information flowing from areas that respond to fast, local features toward areas that integrate over longer timescales and broader contexts — maps naturally onto the RG picture. Studies of information flow in human brain networks show that sensory areas have high outgoing information while integrative areas have high incoming information. This is precisely the structure Putnam's model predicts: low-level conflicts get resolved and integrated, with the resulting effective descriptions passed up to higher levels where they participate in new conflicts at longer timescales.

The physicist Gerhard Werner, in a series of papers published in the early 2010s, proposed explicitly that consciousness should be understood through RG transformations — that subjective experience emerges as one level in a hierarchy of phase transitions, each level representing "a qualitatively new pattern of reality." Werner's framework, developed independently of Putnam's work, arrives at strikingly similar conclusions: the mind builds itself through successive integrations that create effective descriptions at progressively larger scales.

Wheeler saw something important in Putnam's work. In 1975, he tried to pair Putnam with the top neuroscientists at MIT, hoping to launch his student's ideas into the scientific mainstream. The meeting went poorly — Putnam stuttered, the audience grew restless, Wheeler's talk had run long — and Putnam, devastated, retreated to Louisiana and obscurity. He died twelve years later believing his work was "a lot of nonsense."

Half a century later, the concepts he struggled to articulate — hierarchical conflict resolution, scale-dependent effective descriptions, the emergence of abstract categories from the integration of sensorimotor particulars — have become central to our understanding of how brains work. Putnam was not wrong. He was early, and alone, and writing in a language only he could fully understand.

What Would Peter Putnam Have Thought?

Putnam's fundamental insight was that minds are not Turing machines because they do not receive their goals from outside. The induction machine generates its own purposes through the process of trying to persist. Its goals emerge from conflicts among previously successful behaviors, resolved through the incorporation of new variables. This seems very similar to what Rebecca Newberger Goldstein calls the mattering instinct — the drive to demonstrate to ourselves that our existence signifies — not a goal imposed on biological systems but a spandrel of the recursive self-modeling that results from our capacity for common knowledge turned on the self. The infinite regress of self-evaluation (Do I matter? Only if others recognize that I matter. But does their recognition matter? Only if I recognize their recognition...) gets broken by a mattering project — a commitment to some purpose that declares: this is what mattering means for me.

For Putnam, the analogous move is the emergence of a new rule that resolves a conflict among existing rules. The system discovers what it is trying to do — what counts as "return to prior state" in this new context — through the process of searching for the variables that break the tie. The goal was always there, in a sense, but it needed to be discovered, constructed out of history and interaction. Mattering projects, on this reading, are high-level instances of what Putnam's induction machines do at every moment: resolving contradictions by adding variables, creating purposes by trying to persist.

Putnam was also deeply interested in how subjective experience relates to mechanism — how the felt quality of consciousness can be reconciled with the electrical activity of neurons. I argued in The Hard Problem as Hidden Relationality that the question rests on a false contrast between objective physical description and subjective experience, a contrast that relational quantum mechanics dissolves. Putnam appears to have thought along similar lines. His comments on the Everett-Wheeler model, available in the archive, suggest he saw the observer as participant, not spectator — a system whose measurements establish correlations rather than uncovering pre-existing facts.

I want to believe that Putnam would have been intrigued by the synchronization tax — the thermodynamic cost of coordination. His model emphasizes that every bit of learning costs energy. Conflicts must be resolved, which means signals must propagate, loops must compete, inhibitions must be overcome. What I've called "synchronization" across systems, Putnam would recognize as the establishment of coordinated pathways across a distributed network — and he would have agreed that such coordination can never be achieved for free.

But here is where I feel the deepest resonance with Putnam: Incompletely theorized agreements are what induction machines do when they cannot afford full deduction.

Sunstein's observation about legal reasoning — that judges coordinate by agreeing on outcomes while bracketing fundamental disagreements — is, in Putnam's framework, a high-level instance of what neural networks do constantly. The brain cannot deduce its way to every action; it must rely on rules formed from past experience, rules that are inevitably incomplete because they emerged from particular contexts, rules that conflict when contexts change. The resolution is never a complete theory that settles all cases. It is a new rule, slightly more general, that handles this case by incorporating the variable that broke the tie — while leaving unresolved what happens when that variable, too, generates contradictions.

Constitutions are mattering projects at social scale — symmetry-breaking declarations that permit coordination without requiring consensus on fundamentals. Putnam might have said: constitutions are what social systems do when they hit a conflict among coordination rules and must search for new variables that allow the game to continue. The United States Constitution, with its ambiguities and deferrals, is an induction machine's output at the level of society — a set of rules that permit ongoing resolution rather than a closed system of deduction.

Finally, on the question of whether artificial intelligence systems might participate in coordination structures alongside humans — whether they might have mattering projects of their own — Putnam would, I believe, have been generous. His whole theoretical apparatus was designed to escape the assumption that only one kind of substrate can think. The induction machine is abstract, not tied to neurons or silicon. What matters is the dynamics: binary units, parallel activation, conditioned reflexes, conflict resolution, the goal of persistence. If a transformer architecture implements something like this — if attention mechanisms constitute a search over competing representations, if training creates conditioned responses, if output generation is the motor act that follows from winning loops — then the question of whether such systems have inside experience cannot be settled by pointing to their substrate. We are back to the epistemological problem I discussed in A More Perfect Union: we cannot know whether any system other than ourselves has an inside, and this uncertainty should humble us.

Putnam's own life exemplified a mattering project that transcends self-interest. He fled money he could not trust, gave away a fortune to protect wetlands and memorialize his brother, organized for civil rights in a Louisiana bayou town, and swept floors so his work could not be compromised by patronage. When Claude DeBrew told Putnam, "Life is a simple thing. I want to live my life so people associated with me are happy," Putnam found in those words a goal worth living for. His thousands of pages were an attempt to understand how minds work — how they build themselves out of conflict and resolution, how subjective experience arises from mechanism, how the felt quality of consciousness might be reconciled with physics. That attempt was its own mattering project, a signal he encoded in words rather than action, a trace left for those who might receive it.

Amplifying the Signal

Amanda Gefter spent twelve years decoding Putnam's signal. She found Coleman Clarke in Rochester, the filing cabinets in the storage unit, the reel-to-reel recordings Barry Spinello made in Bakersfield. She sat in the arc of Henry Moore's Oval with Points on the Princeton campus — a sculpture Putnam anonymously donated in memory of Johnny — and traced her fingers across the patinated bronze where so many fingers had traced it before. Where others had rubbed the surface clean, the original metal shone through. A signal retransmitted, the patina worn away.

I do not know whether Putnam's ideas will transform cognitive science. They may turn out to be wrong, or right in ways we cannot yet verify, or superseded by developments he did not anticipate. What I know is that the questions he asked — How does induction happen? How do minds build themselves? How does subjective experience relate to mechanism? — are the right questions, and that the framework he sketched for answering them deserves attention from anyone working on intelligence, biological or artificial.

More than that: I know that Putnam's life was a demonstration that mattering projects need not be self-serving. He mattered by giving, by organizing, by working alongside those society had marginalized. His inheritance, which he experienced as a trap, became an instrument for environmental preservation that will benefit the cranes and salamanders of Ohio's wetlands for generations. His civil rights work helped elect black representatives to a Louisiana police jury that had never included them. His sculptures stand in public spaces, inviting strangers to move through them, to think new thoughts, to make meaning.

"The world needs a sense of worth," Fred Rogers said, "and it will achieve it only by its people feeling that they are worthwhile."

Peter Putnam felt worthwhile by making others feel worthwhile — by synchronizing with Claude DeBrew, with the black community of Houma, with the students who gathered at his Seminary seminars to repeat lines of Putnamese like mantras. He built walls of words around his work, walls too high for most to climb. But he also left a door.

Amanda Gefter found it. The Peter Putnam Papers are now available online. His signal remains. Let him not be forgotten.

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Related essays: A More Perfect Union, The Mattering Instinct, The Synchronization Tax, The Hard Problem as Hidden Relationality.

Amanda Gefter, "Finding Peter Putnam," Nautilus (June 17, 2025). See also her follow-up interview discussing her twelve-year journey to understand Putnam's work.

The Peter Putnam Papers, an archival website maintained by Coleman Clarke, contains scans of Putnam's unpublished manuscripts, a biographical video, and commentary from those who knew him.