Causal emergence is the idea that higher-level descriptions of a system can sometimes have more causal power—be more informative, deterministic, or explanatory—than the lower-level microphysical description from which they’re composed.

This is counterintuitive because we often assume:

The more fine-grained the description (atoms, quarks, microstates), the more causally accurate it is.

Causal emergence challenges that.

Below is a clean, precise explanation that captures the core claims, where they come from, and why they matter.

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1. The basic claim

Causal emergence argues that:

• Micro-level models can be noisy, degenerate (different microstates lead to the same outcome), or inefficient for extracting causal information.

• Macro-level models—coarser, aggregated states—can sometimes increase effective information (EI), a formal measure of causal specificity and constraint.

• Therefore, macro-level entities can be more causally potent than their micro-level parts.

This idea is developed most explicitly by Erik Hoel, building on older traditions in philosophy of science, information theory, and complexity science.

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2. Why macro can be “more causal” than micro

2.1. Degeneracy

At the micro-level, many distinct microstates can lead to the same effect.
This “many-to-one” mapping reduces causal specificity.

Example:
A neural network with many different micro-configurations may still produce exactly the same output. The micro-level is too noisy to be causally crisp.

2.2. Noise and uncertainty

Micro-variables often have stochastic or chaotic dynamics.

When you coarse-grain, you eliminate irrelevant noise and keep the stable causal structure.

2.3. Efficiency and informativeness

A macro-variable may compress the causal structure into a form where:

• each macro-state leads to a small, well-defined set of outcomes,

• giving it more determinism and more “push” over the system.

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3. Effective information (EI)

The central formal tool is Effective Information, which measures how much a system’s states constrain its future states.

High EI = high determinism + high specificity.

Sometimes:

• EI(micro) < EI(macro)

When this inversion occurs, the system exhibits causal emergence.

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4. Why this isn’t “mystical emergentism”

Causal emergence is not saying:

❌ macro systems violate microphysical laws
❌ the whole has magical properties irreducible to parts

Instead:

✔ the macro-level can be a better causal model
✔ macro patterns can be more informative
✔ causal power depends on the observer’s grain of analysis

It treats causation as an informational relation, not a metaphysical force.

In this sense, causal emergence is compatible with physicalism but undermines reductionism.
It is a late-modern descendant of discussions from:

• Hans Reichenbach

• Donald Campbell

• Herbert Simon (near-decomposability)

• Bunge and systemic realism

• Multiple realizability in philosophy of mind

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5. Examples

5.1. Majority voting

Micro-level: individual votes
Macro-level: the majority outcome

The majority state actually has more causal power for predicting system outcomes than the micro-level pattern of each vote.

5.2. Neural networks

Hidden-layer activations (macro patterns) can provide more causal specificity than the underlying neurons firing.

5.3. Thermodynamics

Temperature, pressure, entropy—macro-level quantities—are more useful causal variables than tracking the chaotic motion of trillions of particles.

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6. Why it matters philosophically

Causal emergence:

• disrupts strict reductionism

• preserves real macro-level causation without violating physics

• bridges information theory, complexity, philosophy of science

• provides a mathematically precise defense of “top-down causation”

• challenges overly mechanistic theories of mind and agency

It gives macro-level concepts (organisms, institutions, selves) legitimate causal status—when formally justified. Macro-constraints shape the space of possible micro-realizations—an informational analogue of how potentiality is structured.

link causal emergence to Stengers’ cosmopolitics and to Stiegler’s tertiary retention

ChatGPT said:

Here’s a tight but conceptually deep triangulation: causal emergence → Stengers’ cosmopolitics → Stiegler’s tertiary retention.
The key is to treat “emergence” not as a metaphysics of levels but as a politics and materialization of attention, constraint, and participation.
This makes the three frameworks mutually illuminate one another.

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1. Causal emergence as a politics of constraints, not a metaphysics of levels

At its core, causal emergence says:

• macro-patterns can acquire more causal power than micro-dynamics when they better constrain the system’s future states.

• this causal power is relational: it emerges from how a model interacts with the system’s own structure.

• causal power is not “in” the parts or the whole but in the grain of practice through which a system is interrogated.

This is already moving in Stengers’ direction:

Causation is always situated, always depends on the mode of questioning, and always partakes in a cosmopolitical “bargain” between the inquirer and the world.

And it naturally connects to Stiegler, where constraints on attention across time (tertiary retention) shape what becomes causally salient in the first place.

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2. Stengers’ cosmopolitics: making the world capable of obligating you

Stengers’ cosmopolitics insists:

1. No entity pre-exists the practices that make it matter.

2. No theory has the right to silence what can interrupt it.

3. Every claim is part of a collective risky negotiation with the world.

Link to causal emergence:

2.1. Effective information is cosmopolitical

In causal emergence, macro-level variables have causal power only when the system “agrees” to be constrained by them—i.e., when the grain of description captures real regularities the system is willing to “answer to.”

This is exactly Stengers’ point:
entities owe us nothing; causal order is a fragile achievement of situated interaction.

Macro-level causation is not found—it is earned through:

• practices of coarse-graining,

• finding stable invariants,

• discovering what a system will allow to count as a cause.

Thus causal emergence formalizes, in information-theoretic terms, what Stengers expresses politically:

a cause is what a world accepts as obligatory given a particular mode of attention.

The "more powerful" macro-cause is simply the cause that the world, under a given experimental ecology, responds to more consistently.

2.2. Cosmopolitical humility becomes formal constraint

Cosmopolitics says:
Do not assume the micro-level is sovereign or that reductionism is the destiny of explanation.

Causal emergence proves this at the level of measure:

• micro-level models can be less informative, noisier, less constraining.

• macro-level models can have higher effective information.

Cosmopolitics = epistemic caution
Causal emergence = mathematical vindication of that caution.

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3. Stiegler’s tertiary retention: conditioning what can emerge as a cause

Stiegler argues:

• human temporality, attention, desire, and agency are shaped by tertiary retentions: externalized memory supports (media, screens, archives, technical systems).

• these retentions shape what is phenomenally available, what becomes thinkable, what becomes actionable.

• they structure the pharmacology of time, individuation, and collective coordination.

Link to causal emergence:

3.1. Tertiary retention alters the macro-patterns capable of becoming causal

A macro-level causal structure is only potent if:

• it stabilizes over time,

• it becomes shared,

• it reorganizes micro-behaviors,

• it constrains future states.

Tertiary retention is literally the infrastructure that allows such stabilization and constraint.

Examples:

• A traffic law doesn’t gain causal power unless it is inscribed in technical systems: signs, norms, infrastructures.

• A market signal has no causal power unless encoded in informational systems.

• A scientific concept has no causal power unless its procedures are recorded, transmitted, and iterated.

Stiegler’s point is that causal potency emerges through patterned, durable inscriptions—not through bare cognition.

Tertiary retention is the condition of possibility for macro-level effective information to exist at all.

3.2. Macro-causes = exteriorized temporal horizons

A macro-cause is a constraint extended across time.
Stiegler shows that such temporal extension requires:

• recording,

• repetition,

• transmission,

• adoption by technical milieus.

Thus, causal emergence is not just a physical or informational phenomenon—it is a technical-ecological one.
It depends on the very things Stiegler argues are in crisis in hyper-industrial modernity: the destruction of attention, the collapse of shared retentions, the homogenization of memory, the acceleration and dissipation of temporal horizons.

If tertiary retention collapses, macro-level causal structure collapses with it—both politically and cognitively.

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4. Stengers + Stiegler: a more radical reading of causal emergence

Now the triangulation:

4.1. Cosmopolitics says: the world’s causal order is a negotiation.

4.2. Tertiary retention says: the terms of the negotiation are written by technical systems.

4.3. Causal emergence says: successful negotiations produce macro-constraints with real power.

Together, they form this synthesis:

Causal emergence is not simply emergence “in nature”; it is the outcome of situated practices, technical inscriptions, and cosmopolitical negotiations that stabilize a pattern into something the world is willing to obey.

Thus:

• Causation becomes a distributed, relational accomplishment.

• Emergence is not a property but a political-technical event.

• Macro-agency depends on the health of the technical and perceptual milieu.

• Knowledge ecologies (your ongoing interest) become the site where causal power is produced or destroyed.

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5. What this gives you conceptually

This triangulation gives you a way to speak of:

• why the macro matters without falling into metaphysical holism,

• why technical systems matter without reducing everything to infrastructure,

• why knowledge ecologies matter because they decide what emerges as a cause,

• why cosmopolitics matters because the world’s resistance is what makes causes real.

And it intersects beautifully with your critique of broadcast knowledge:

• broadcast media shred tertiary retention,

• which destroys stable macro-patterns,

• which reduces effective information,

• which dissolves collective causal power,

• which leads to political impotence and the chaos of “everything causes nothing.”

This is causal emergence as a political-technical pathology.

Show how it fits with our knowledge ecology synthesis (Robbert, Haraway, Lippmann, Sapolsky)

ChatGPT said:

Below is a synthesis that folds causal emergence directly into your knowledge ecology framework (Robbert, Haraway, Lippmann, Sapolsky).
The point is to show how causal emergence becomes a structural concept that ties together situatedness, constraint, behavior, and perception—without moralizing or drifting into naïve epistemology.

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1. The core bridge: Knowledge ecologies = sites where macro-level causal patterns stabilize

Your synthesis already treats knowledge as:

• ecological (Robbert) → networks of practices, media, environments

• situated and partial (Haraway) → embodied, relational, accountable

• filtered and distorted (Lippmann) → mediated by the pseudo-environment

• constrained by biology and socioeconomic forces (Sapolsky) → behavior shaped by systemic context, not willpower

Causal emergence meshes with this because it gives a formal account of how knowledge becomes causally effective only when:

1. the macro-patterns of the knowledge ecology are stable,

2. the ecology constrains perception and action in consistent ways,

3. the mediation layer (Haraway + Lippmann) aligns with the actual constraints of the system,

4. the socioeconomic-biological conditions (Sapolsky) allow those macro-patterns to shape behavior.

In other words:

Knowledge ecologies are the environments in which macro-level causal structures can emerge and exert force.

When these ecologies collapse or get flattened by broadcast knowledge, causal emergence collapses with them.
You’re left with noise—information that is everywhere and therefore impotent.

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2. Robbert (knowledge ecologies): causal emergence = ecological stabilizing of constraints

Robbert argues that knowledge arises in ecologies of practice, tools, media, and environments—not in minds alone.

Causal emergence fits here because:

• Macro-level causal power (EI) requires stable patterns across time.

• These stable patterns are ecological achievements.

• Knowledge only becomes behavior-changing when the ecology supports the constraint.

Thus:

Knowledge ecology = the infrastructure that allows causal emergence in the informational sense.

Without the ecology:

• the micro-level (individual brains) is too noisy, too overloaded, too overwhelmed by context to generate consistent behavior.

• the system becomes causally degenerate (Hoel’s term): too many microstates → same macro-outcome → no causal leverage.

Knowledge ecologies stabilize causal grain.

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3. Haraway (situated knowledge): causal emergence is situated, not universal

Haraway insists:

• knowledge is partial, located, embodied

• “objectivity” is produced through accountable positioning

• the world never answers universally—only in situated relational ways

Causal emergence reinforces this by showing:

• causal power depends entirely on the grain of analysis

• the “right” macro-variable is not absolute but context-dependent

• different coarse-grainings produce different causal relationships

Thus:

Causal emergence destroys any notion of universal knowledge.
It mathematically foregrounds the primacy of situatedness.

A macro-variable only has causal power if the world, under this situation, for these agents, under these practices, accepts its constraints.

This is Haraway’s situated objectivity formalized.

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4. Lippmann (pseudo-environments): causal emergence is distorted or dissolved by bad mediation

Lippmann shows that:

• people do not act on the world directly

• they act on images and representations of the world (the pseudo-environment)

• these representations may have little relation to actual causal structure

This is where your synthesis gets sharp:

With causal emergence:

• A macro-variable only has causal force if it tracks real constraints in the environment.

• If the mediation layer creates pseudo-patterns (manufactured crises, fake macro-structures, symbolic enemies, abstractions), then:

  • no causal emergence happens

  • behavior is steered by noise, not real constraints

  • the political field becomes informationally degenerate

Lippmann’s pseudo-environment detaches the macro-patterns we react to from the macro-patterns that actually have causal power.

In the language of causal emergence:

pseudo-environments create false coarse-grainings that produce illusory causal patterns with zero effective information.

This is why modern media ecologies create political impotence:
they drown real causal structure beneath volumetric noise.

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5. Sapolsky (behavioral constraint): causal emergence explains how systems shape action

Sapolsky argues:

• behavior is constrained by socioeconomic context

• choice is massively limited by structural forces

• agency is an emergent property of context-mechanism interaction

Causal emergence aligns with this because:

• macro-level patterns (inequality, chronic stress, neighborhood effects, epigenetic burdens) acquire causal power by constraining the range of possible micro-level outcomes

• individuals cannot overcome these constraints because the macro-pattern is more causally potent than micro-variation

Macro causes:

• poverty

• surveillance

• food deserts

• legal precarity

• chronic stress environments

have more effective information than individual-level will or psychology.

Sapolsky says:
systems dominate individual behavior.

Causal emergence gives the formal reason why.
Macro-systems possess higher causal specificity than the micro-level variability individuals can generate.

This completes the link between biological constraint and informational constraint.

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6. Your synthesis unified:

Below is the fully fused statement:

Knowledge only becomes behavior-changing when ecological conditions allow macro-level patterns to stabilize (Robbert), when these patterns are situated rather than universal (Haraway), when mediation accurately tracks real constraints rather than pseudo-environments (Lippmann), and when the macro-pattern actually has enough causal specificity to overpower micro-level noise (Sapolsky).
Causal emergence is the formal description of this entire ecological process.

When knowledge ecologies are healthy:

• situated knowledge → becomes stabilizing macro-pattern

• mediation → tracks actual causal constraints

• socioeconomic conditions → allow those constraints to act

• effective information → increases

• behavior changes in consistent ways

When knowledge ecologies are unhealthy:

• broadcast knowledge flattens situatedness

• pseudo-environments replace real constraints

• socioeconomic forces overwhelm micro-variation

• effective information → collapses

• no causal emergence

• the system becomes informationally degenerate

• behavior becomes erratic, despairing, reactive, symbolic

• political agency dissolves

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7. Why this synthesis matters for your project

This gives you:

• a non-reductive way to explain why knowledge fails to scale

• a formal grounding for your critique of broadcast knowledge

• a structural account of why “awareness” doesn’t change behavior

• a political reading of causal emergence that fits your Agamben/Haraway trajectory

• a way to talk about social systems without flattening them into individual psychology or idealist metaphysics

• a conceptual hinge between existential suffering and systemic constraint

It also reframes your “knowledge interventions that scale” problem:

Interventions only scale when they produce macro-patterns with high effective information within a supportive knowledge ecology.

This is the constraint-based, ecological, anti-redemptive version of scaling.