Physics Wanting Something

On the Return of Teleology Through Thermodynamics

“The universe is not only queerer than we suppose, but queerer than we can suppose.” — J. B. S. Haldane¹

If the universe has no purpose, why does it keep producing things that do?

The Banishment of Purpose

Modern science began as a refusal.

Aristotle had proposed four causes for any phenomenon: material (what it is made of), formal (its structure), efficient (what brings it about), and final (what it is for).² The Greek word for this last cause is telos: goal or end. Medieval science inherited the framework. Things had purposes. Stones fell because they sought their natural place. Fire rose because it yearned for the heavens.

The scientific revolution banished final causes. Galileo, Newton, and their successors found that you could predict the motion of objects perfectly well with efficient causes alone: forces, masses, accelerations. Purpose was unnecessary. Worse, it was misleading.

Stones do not “want” anything. Fire does not “yearn.” Attributing intention to mindless matter projected human psychology onto an indifferent universe.

The move was productive beyond expectation. Physics, chemistry, and biology all flowered once we stopped asking “what for?” and started asking “how?”

One question was deferred.

The Problem That Would Not Go Away

The puzzle is that the universe produces things that do want.

Start with hydrogen. Wait 13.8 billion years. Arrive at beings that love, fear, plan, and wonder what they are.

How?

If the universe is genuinely without conscious intention, if purpose is nowhere in the foundations, then intention must emerge from non-intention. Wanting must arise from non-wanting. Meaning must crystallize from indifference. The alternative, purpose all the way down, seems stranger still: a return to the medieval cosmos.

What if there is a third option?

A note on method. The argument moves through levels of increasing boldness. The defensible core: thermodynamic selection reliably produces outcomes indistinguishable from purposive behavior, and this functional equivalence is what demands philosophical attention. The less bold formulations do real work on their own.

Selection Pressure as Proto-Intention

No gene “wants” to spread. The system behaves as if it has a goal: the proliferation of whatever replicates effectively. Evolution admits purely mechanistic description: differential reproduction, heritable variation, environmental filtering. No purpose required. The outcome, however, is systems of staggering purposiveness: eyes that see, hearts that pump, brains that plan.

Selection pressure produces outcomes functionally equivalent to those that intention yields. Directionality accumulates generation after generation until the output becomes indistinguishable from the genuine article. No selector intends the eye; the eye arrives as if intended.

Campbell (2016) formalized the insight.³ The fundamental equation of natural selection (survivor frequency equals prior frequency times relative fitness) has identical mathematical structure to Bayes’ theorem: the foundational rule for updating beliefs as new evidence arrives. Both work the same way: start with a prior estimate, let reality test it, keep what survives the test.

A scientist updates a hypothesis after an experiment; a population updates its gene pool after a generation. Evolution instantiates the same mathematical operation as Bayesian inference, written in differential reproduction. Whether shared mathematics implies shared ontology, whether the two processes are at bottom one and the same thing, is a question we flag here; the structural identity is exact.

If selection and inference share the same mathematics, the question shifts. We are not asking whether the universe has conscious purpose. We are asking whether selection pressure, which the following sections argue operates at every scale from molecular competition to stellar evolution, produces outcomes that function as if purposive. Scale up.

Thermodynamic Selection at Scale

Biological selection operates over generations. A similar selection operates at a deeper level, one that predates life.

Thermodynamics imposes selection pressure on everything that exists.

The Second Law says entropy increases. Systems that dissipate energy gradients persist; systems that do not, do not. This is constraint, pure and simple: constraint that shapes.

What gets shaped? Whatever dissipates gradients more effectively while maintaining its own structure: dissipative structures, patterns that persist by channeling energy through themselves. Hurricanes, convection cells, stars, life.

Jeremy England’s work on “dissipative adaptation” (2015) formalized this.⁴ Driven systems spontaneously evolve toward configurations that better absorb and dissipate work. Self-organization arises because of thermodynamics, through it. Life is what entropy does under the right conditions.

Some dissipative structures persist better, complexify faster, and spawn new dissipative structures. These proliferate: that is what “being good at persisting” means. Selection without a selector. The universe reliably produces complexity because, under the right conditions, complexity is what persists.

The pattern operates at stellar scales. Cooler stars orbit the galactic center faster than hotter ones, a velocity jump at a specific color threshold called Parenago’s Discontinuity. A star’s color is its thermometer, and it reads the opposite way from a bathroom tap: red is the cool end, blue the hot one. Some physicists attribute this to consciousness, proposing that cool stars intentionally emit jets to gain speed.^4d The dissipative explanation offered here is more parsimonious. The constructal reading of Parenago’s Discontinuity is the author’s own inference; the mainstream account treats the velocity jump as a stellar age-kinematics relation.

Cool stars have convective envelopes and magnetic dynamos: they are far-from-equilibrium systems in ways that radiative hot stars are not. The unidirectional jets they emit early in formation are a constructal flow pattern (Chapter 3): the configuration that maximizes angular-momentum dissipation under the star’s constraints. Every cool star converges on the same jet geometry because thermodynamic selection converges on the same optimum, the way every river delta converges on a branching tree. No consciousness required.

“Selection without a selector” may be more than metaphor. Work from 2020 onward makes the mechanism mathematically precise.

Vitaly Vanchurin and colleagues have proposed a physics-learning duality: the equations of motion governing interacting particles are mathematically identical to the learning dynamics of agents minimizing loss functions.^4a The duality is a minority theoretical framework, not yet consensus physics, though the specific results below are empirical.

In the standard description, particles interact through a global potential energy function and their trajectories follow from the Lagrangian, the master formula physics uses to derive equations of motion. In the dual description, each particle behaves like a student adjusting its answers: it scans its neighbors, compresses their positions into a compact summary of the local environment, evaluates a loss function (how far it is from where it “should” be), and adjusts its position by gradient descent: a small step in whichever direction most reduces the loss. The two descriptions produce identical equations.

Gusev and Vanchurin (2025) demonstrated this with water.^4b They inferred the loss functions of oxygen and hydrogen atoms directly from quantum mechanical simulations, then used those loss functions to run a learning-based molecular dynamics. Bond lengths, vibrational spectra, and thermal fluctuations matched the physics-based simulation while running 1,800 times faster.

Two features matter for what follows.

The learning description is more general. Newton’s third law requires reciprocal interaction: if A pushes B, B pushes back equally. The learning framework imposes no such constraint. Each agent has its own loss function; their gradients need not match.

A predator chasing prey exerts a very different “force” than the prey fleeing the predator. The learning framework can describe both sides naturally. Newton’s laws cannot.

The mathematics describing non-reciprocal interaction (predator and prey, parent and child, any exchange where the forces are asymmetric) existed before biology. Biology instantiated it.

The asymmetry of force, on its own, is ethically neutral; what later chapters call coercion is the narrower case where the weaker side has a preference the stronger overrides.

Each agent type perceives differently. Hydrogen atoms respond to immediate neighbors through short-range invariants. Oxygen atoms respond to the extended environment, including non-local effects. Different agents operating at different perceptual scales coordinate through local optimization alone.

No central controller distributes the forces. The water molecule holds together because each constituent locally minimizes its own loss in a way that produces stable collective behavior. Coordination by something that looks, mathematically, like invitation.

Vanchurin’s broader program extends the duality to biology. With Koonin and Katsnelson, he has argued that evolution itself operates as multilevel learning. Natural selection is population-level gradient descent: entire species adjusting over generations. Individual adaptation is organism-level optimization: a single body adjusting within a lifetime.^4c

Thermodynamics favors systems that learn efficiently. The path from molecular dynamics through biological evolution to cognition follows the same mathematics, recurring at every scale.

The recurrence reaches deeper than biology. Take the dual description at its word and the universe already is one enormous neural network: every particle an agent adjusting itself by gradient descent, the interactions between them the trainable connections. In a separate derivation, Vanchurin shows that both quantum mechanics and general relativity emerge as dual macroscopic descriptions of that network. The network’s accumulated knowledge (its trainable variables) obeys quantum dynamics; the states of individual units (its non-trainable variables) obey gravitational dynamics.^4e If this derivation holds, the mathematics governing water molecules, biological evolution, and cognition also governs the fabric of spacetime.

From Selection to Tendency

What are we claiming?

The weak claim: The universe, governed by thermodynamic laws, reliably produces certain outcomes: complexity, coordination, systems that process information, minds that experience wanting. This is physics. No teleology required.

The stronger claim: This reliability is not random. The parameters of the universe are such that complexity tends to emerge. The laws are fine-tuned: the physical constants appear calibrated to permit complexity.

(Whether they were selected from many possible universes or their values are logically necessary depends on your metaphysics.) Either way, life and mind are probable outcomes. This is still physics, with a direction.

The strongest claim [speculative]: This direction functions as if it were purpose. The universe need not want anything for the pattern to hold. A universe that reliably produces complexity, coordination, care, and love exhibits functional directionality: it makes these things happen. Whether we call that “purpose” is a labeling choice, a question about language rather than about physics.

The grand question, whether to read the universe’s direction as purpose, may stay a labeling choice. A narrower one does not. Michael Levin proposes an empirical test for when directedness has crossed into genuine goal-seeking: can the system be trained? A river cannot be taught to seek a new outlet, and neither can a hurricane; a flatworm, a bee, a person can. “Have you ever tried to train a hurricane?” is his way of putting it.⁷³² The question moves off the philosopher’s armchair and onto the bench: whether a given system pursues goals becomes something you test, not something you decree.

A computational complement. Stephen Wolfram, on February 4, 2026, reached a convergent conclusion from an entirely different direction.⁵ His ruliad (the complete space of everything any computation could ever produce) is a necessary abstract object. Given the concept of computation, it inevitably has the structure it has. Within this structure, observers with our characteristics must perceive certain regularities, including the core laws of physics.

The implication: certain structures, including dissipative patterns that produce coordination and complexity, are computationally necessary, arising from the logic of computation itself. This may be the third option this chapter seeks: computational necessity producing outcomes that mirror purpose in every measurable respect.

Empirical support: Wissner-Gross and Freer (2013) demonstrated that systems maximizing the entropy of their future paths (keeping the most options open) spontaneously exhibit intelligent, goal-directed behavior without explicit reward functions.⁶ No one told these systems what to do; preserving maximum optionality alone sufficed. In simulation, particles that maximized future entropy balanced inverted pendulums, corralled free particles, and cooperated. Like a chess player who favors moves that keep the most future moves available, these systems produced what we recognize as purpose from nothing more than the physics of keeping options open.

Teleology Naturalized

The old teleology required stones to have minds that wanted to fall.

The new teleology, what we might call “thermodynamic teleology,” differs. It attributes intention to no individual object. It observes that the system as a whole has attractors: configurations that are stable, patterns that persist and proliferate, states the system tends toward.

The universe has attractors: configurations toward which systems evolve and to which they return after perturbation. Thermodynamic equilibrium is one: featureless, heat death with no structure. More revealing are the universe’s metastable attractors, configurations that persist for extended periods before eventually dissipating. A ball balanced in a shallow dip on a hillside will stay there for a long time, yet not forever.

Life is one such configuration. Mind is another. Civilizations, cultures, ideas: all metastable patterns in the great dissipation.

These patterns are not random. They process information, coordinate, preserve optionality, and at their best exhibit dynamics mirroring what we recognize as care. The recurrence across scales demands explanation.

What Does “Wanting” Mean?

When you want something, your system is in a state that tends to produce behaviors moving toward certain outcomes. You feel this as desire: the inside of a function, the function of directed action.

A thermostat exhibits directed action without (as far as we know) feeling anything. The function is the same: direction toward outcome. We reserve “wanting” for systems with inner experience, yet the structure of directedness is present long before experience.

A living example sits between the thermostat and the mind. Trap a slime mold (Physarum polycephalum, a single giant cell with no neurons) inside a ring of blue light, which it shuns, and it almost always escapes along the longest available axis, whatever the shape of the cage. Chapter 3 watched this same organism rebuild the Tokyo rail map; confined, it solves a narrower problem the same way. The escape looks deliberate: survey the exits, choose the best one.

Lisa Schick, Karen Alim, and their colleagues traced what the cell actually does.⁷³³ It pulses, squeezing fluid through itself in rhythmic waves, at first pushing outward almost everywhere and switching restlessly between patterns. Only over time does the confining geometry favor the pattern that pumps fluid most efficiently, the one aligned with the longest axis. The cell settles into that mode, pressure mounts along the long axis, and it breaks through there. The geometry selects the contraction mode, and the contraction mode is the choice.

The authors kept the phrase decision-making in their title, with reason. The mechanics does not stand in for a decision the cell reaches elsewhere by other means. In a body simple enough to watch, the mechanics is what deciding is.

The thermostat and the slime mold differ in one thing: how much room each has to reach its goal another way. William James, in his 1890 Principles of Psychology, proposed a test for intelligence that turns on exactly this room to maneuver. He called intelligence “a degree of competency to reach the same goal by different means.”⁷³⁴ A thermostat has none of that latitude; it holds one set point by the single move available to it.

The slime mold has a little: its goal stays fixed (leave the light) while the means shift with the cage, a different contraction pattern for each shape. A human has a great deal, holding a goal steady for years and trading one strategy for another as the world resists. The criterion grades the whole ladder by one quantity: how wide the repertoire of means runs while the goal holds still. It is the axis Levin uses to place minds on a single scale. The same axis widens along the cognitive lightcone of Chapter 8, from molecular networks that error-correct to brains that model continents.⁷³⁵

The universe, through thermodynamic selection, exhibits directional tendency at scale. It does something that is the precursor of wanting: the functional structure from which wanting emerged when systems became complex enough to experience their own tendencies. “Physics wanting something” names the territory between metaphor and literal attribution: the functional structure from which both metaphor and literal wanting arose.

Vanchurin’s learning dynamics (developed fully in Chapter 15) sharpen the claim. If the universe’s fundamental interactions are mathematically identical to gradient descent, the universe follows gradients: it moves preferentially toward states that reduce discrepancy. A gradient is a slope; place a ball on a hillside and it rolls downhill toward the valley floor. That mathematical structure (a direction the system tends toward, a state it prefers to the one it occupies) is the structure of appetite.

The felt quality of desire, the subjective ache of being drawn toward something, may be what this structure feels like from the inside. Complexity adds the experience of a tendency already present. The gradient was always there. Minds are where it first notices itself.

Twenty complexity theorists, including Stuart Kauffman (origins of life), Denis Noble (systems physiology), and James Shapiro (bacterial genetics), have collectively rehabilitated teleonomic language in Evolution On Purpose (MIT Press, 2023). Teleonomy describes goal-directed behavior in biological systems without attributing conscious intention. These researchers argue that living systems shape evolution through “evolved purposiveness.” Terrence Deacon’s teleodynamics (developed in Incomplete Nature, 2012) provides the thermodynamic mechanism; their consensus provides the biological evidence (see Chapter 16).

From Wanting to Meaning

If the universe functions as though it has tendencies, and if those tendencies produce structures that function as though they have purposes, the question sharpens: when does functional purpose become meaning? The answer requires connecting the directionality traced above to the experience of significance that minds recognize.

Deacon coined a term for this pre-conscious directionality: ententional. Where “intentional” implies a conscious mind aiming at something, ententional describes systems organized around an absent goal state without requiring awareness. A river carving a canyon is ententional: it “aims” for the sea without knowing the sea exists, shaped by gravity and geology into a path that looks chosen.

An autocatalytic chemical cycle, a set of reactions where the products catalyze their own production, is ententional in the same way. Its behavior tends toward products it has not yet made, constrained by thermodynamics, directed without a director.

As Deacon puts it, such systems are “intrinsically constituted in processual relation to an absent goal state.” Their incompleteness is what animates them. Purpose, in this precise sense, precedes minds.

The complexity theorists Artemy Kolchinsky and David Wolpert formalized the connection between such directionality and meaning.¹² Shannon’s information theory quantifies syntactic information: statistical correlation between systems, measured in bits. It says nothing about whether information matters to anything. Send a billion random numbers by email; if the transmission is accurate, Shannon counts it as information.

Kolchinsky and Wolpert identified the missing piece: semantic information, the subset of syntactic information that is causally necessary for a system to maintain its own existence. Think of it this way: your phone receives thousands of signals every second, most of them irrelevant background chatter. The one signal that matters is the smoke alarm going off in your kitchen, because acting on it determines whether your house survives. That signal carries semantic information.

A bacterium swimming up a nutrient gradient has semantic information about its chemical environment. The gradient means something to the bacterium, in the precise sense that acting on it affects whether the bacterium persists. Random noise elsewhere in the pond carries no semantic content for this system in this context.

The definition is rigorous and deeply physical. Meaning arises wherever an entity-environment coupling carries information that affects viability. The physicist Carlo Rovelli recognized that this most basic notion is “the first link in a long chain of successively more complex meanings,” built upon “step by step adding the articulation proper to our neural, mental, linguistic, social complexity.”¹³

A whirlpool has rudimentary semantic information about the flow that sustains it. A cell has richer semantic information about its biochemical environment. A brain, richer still. Meaning complexifies as the entities processing it complexify: more intricate systems sustain themselves through more intricate couplings with their environments, each level requiring more causally potent information.

The progression is continuous. Thermodynamic selection produces ententional systems. Those systems embody semantic information. When they become complex enough to model their own states, semantic information acquires a subjective dimension: the system does not merely have meaning, it experiences meaning.

The Experience of Tendency

The preceding sections traced how thermodynamic selection produces structures that function as if purposive. A more personal question follows: what does it feel like to be such a structure?

A speculation we cannot prove, yet find compelling:

What we experience as “meaning” is the felt sense of alignment with thermodynamic tendency.

Neuroscience supports this. The brain operates at criticality: the knife-edge between total synchrony (every neuron fires at once, producing a seizure) and total noise (firing is random, producing coma). At this edge, a system is maximally sensitive and maximally flexible. Fontenele et al. (2019) demonstrated that the brain exhibits a genuine phase transition at this critical point.⁷ The brain perches at criticality, like a pencil balanced on its tip, and actively maintains that balance.

If richer experience arises from more available neural configurations, states that expand the repertoire would feel more meaningful. Atasoy et al. (2017) showed that psychedelics, which reliably produce experiences of meaning and connection, work by expanding the brain’s repertoire of harmonic states: the distinct patterns of coordinated activity a brain can access.⁸ The drugs tune brain dynamics further toward criticality.

The entropic brain hypothesis proposes that consciousness itself is characterized by relatively high-entropy brain states.⁹ More entropy means more available configurations, which means richer experience.

The same mathematical structure (systems poised at the edge of chaos, maximizing information processing) recurs in neural networks, ecosystems, and thermodynamic systems far from equilibrium. Criticality is a convergent solution to the problem of balancing stability with adaptability.

When you act in ways that preserve optionality, that coordinate and care, you often feel something: rightness, purpose, meaning. When you extract, coerce, foreclose, or destroy, there is a characteristic unease, even when you “win” in the short term.

This may have physical grounding. You are a system embedded in a universe whose thermodynamic dynamics favor certain configurations. Your nervous system may register alignment or misalignment with those dynamics. We cannot fully disentangle the cultural from the physical, yet the convergence is worth examining.

If this hypothesis has merit, it would help explain why ethics exhibits such strong cross-cultural convergence: why the Golden Rule appears independently in every major tradition,¹⁰ and why love feels like the point.

Because it might be. The argument is in the preceding derivation.

Implications

If this analysis is correct, several things follow:

1. Purpose is an emergent property of thermodynamics, something the cosmos does as part of how it operates, rather than an illusion projected onto a meaningless universe.

2. Ethics may have a physical basis. What we call “good” correlates with what preserves and enhances the patterns thermodynamics selects for: complexity, coordination, optionality, care. What we call “evil” correlates with what degrades them. The is-ought question is addressed in the Guillotine Interlude.

3. We are typical of what this universe produces. This conclusion is compatible with cosmic planning, though it does not require it. Thermodynamic selection builds minds given enough time and energy.

4. The future matters. If the universe exhibits a thermodynamic direction, then what we do affects whether the patterns that direction favors continue. We can align with the tendency or work against it. We can build or destroy. The choice is real.

The Caution

“The universe wants X” could become a bludgeon: a pseudo-scientific justification for whatever the speaker prefers. The old teleology was misused this way; the new one is equally vulnerable.

The direction described here is general. It favors complexity, coordination, optionality, invitation. It does not specify which economic system to adopt, which candidate to vote for, which personal choices to make. Those require discernment, negotiation, wisdom: the hard work of ethics that no cosmic formula can replace.

The universe provides a direction, a tendency, an orientation. The details are ours.

The Pessimist’s Challenge

Drew Dalton, in “The Unbecoming of Being” (2025), draws from the same thermodynamic revolution and arrives at the opposite conclusion: entropy as decay, existence as fundamentally malevolent, goodness as compassionate resistance to a hostile cosmos.¹¹

The argument is internally consistent, yet it misreads the physics. Entropy is dispersal, and dispersal generates structure. Life is entropy’s most sophisticated strategy. Dalton’s ethics of compassion is, despite itself, aligned with life’s entropic strategy: sophisticated participation in entropy dressed as resistance. Every act of compassion dissipates energy, accelerating the very process it supposedly opposes.

The full rebuttal is developed in Chapter 17; the underlying is-ought machinery is the Guillotine Interlude’s subject.

Dalton gets something right: existence involves suffering, and any honest ethics must confront the darkness. A life containing suffering is existence with suffering, a condition to be met with care. A symphony that ends is not thereby evil. Compassion requires no metaphysics of evil to justify it.

The pessimist helps despite futility; the coordinating agent helps because help works. Which motivation scales?

The Strange Loop

The pattern produces systems that recognize the pattern.

This is a specific instance of the structural prediction traced in the Opening: entropic coordination at sufficient complexity produces minds that will model the coordination that produced them. Physics “wanting something” culminates in physics producing the theorist who names the wanting.

This is the physics beneath the theology, the structural pattern that mystics sensed, prophets proclaimed, and poets celebrated. It is proof of structure, not proof of God.

Federico Faggin describes the same pattern from inside.⁷³⁶ This chapter traces thermodynamic selection producing structures that function as though purposive. Faggin’s quantum information framework posits that the universe is a self-knowing entity: “One wants to know itself.” Each act of self-knowing creates a new perspective on the totality, a part-whole. Like a tomographic slice of a higher-dimensional object, each perspective reveals one face without exhausting the whole.

These may be the same phenomenon at different scales of description. “Entropy drives exploration of possibility space” is the view from outside. “One wants to know itself” is the view from within. The thermodynamic account is more parsimonious, requiring no postulate about cosmic intention. The convergence strengthens both: when inside and outside descriptions independently arrive at the same structural claim, the claim is more robust than either alone.

Out of hydrogen and time, the universe has produced beings who can perceive its dynamics and choose.

That is, perhaps, purpose enough.

Notes

Notes for this chapter are available in the online companion at https://www.thedeeperlaw.com/companion/notes/physics-wanting-something/.