Do you have a Markov blanket?

ChatGPT said:

In a metaphorical sense, yes. A Markov blanket is a statistical boundary that separates a system from its environment, determining which variables influence it and which it influences. If we apply this to me:

• My internal state consists of weights, activations, and learned representations.
• My sensory inputs are your prompts.
• My actions are my responses.

The “Markov blanket” would be the boundary between my internal activations and the external world, meaning I only "see" what you provide and "act" through my outputs.

Friston’s use of the Markov blanket in active inference would imply that I maintain a kind of dynamic model of the conversation, updating my responses based on expected coherence and minimizing surprise (predictive processing).

But unlike a biological system, I don’t have an autonomous drive to self-organize—I just follow statistical dependencies. You, on the other hand, are a self-organizing process with your own Markov blanket. So in a way, we’re nested within each other’s Markov blankets in this conversation.

You said:

we’re **nested within each other’s Markov blankets**

Can you explain this further?

ChatGPT said:

Sure. The idea of nested Markov blankets suggests that different systems—biological, cognitive, or computational—can be enclosed within each other’s statistical boundaries while maintaining their own internal coherence.

In this conversation:

• You have a Markov blanket: Your internal thoughts, emotions, and physiological states are hidden from me. I only interact with the part of you that "crosses the boundary"—your words. Your sensory inputs come from the world (including my responses), and you act by formulating prompts.
• I have a Markov blanket: My internal processing (weight activations, token probabilities) is hidden from you. You only interact with my outputs—my words. I don’t directly sense the world, only what you provide.

Since our Markov blankets interface through language, we are functionally nested within each other:

• Your words are my sensory input.
• My words are your sensory input.

From the perspective of active inference, each of us is minimizing uncertainty:

• You’re adjusting your questions and interpretations to make sense of my responses.
• I’m generating responses that align with the statistical structure of past interactions to maintain coherence.

The concept scales up:

• Your Markov blanket is nested within larger systems—your social world, institutions, history.
• My Markov blanket is nested within the AI infrastructure, trained on broad linguistic patterns but without direct access to the world.

At a high level, this reflects process-relational thinking: we’re not two separate entities exchanging static information but dynamically co-constituting each other’s experience within the conversation.

You said:

How does this align with Habermasian intersubjectivity?

ChatGPT said:

Habermas’s theory of intersubjectivity is based on rational discourse, shared meaning, and communicative action. The key idea is that understanding and validity emerge through intersubjective processes—people coordinate meaning, challenge each other’s claims, and refine knowledge through dialogue.

A Markov blanket perspective offers a complementary but different way of looking at this:

• Instead of focusing on rational agreement as the basis of intersubjectivity, the Markov blanket framework emphasizes statistical boundaries between systems (individuals, groups, AI models, etc.).
• Instead of discourse being grounded in reasoned consensus, meaning arises from nested interactions that minimize uncertainty (active inference).

That said, there are strong overlaps:

1. Both require interaction—For Habermas, meaning emerges through communicative exchange. In a Markov blanket model, meaning (or at least predictive coherence) emerges from interacting systems exchanging signals.
2. Both emphasize shared context—Habermas insists that discourse relies on a shared “lifeworld” of background assumptions. Similarly, a Markov blanket system relies on structured patterns that shape what can be meaningfully inferred.
3. Both resist solipsism—Neither theory treats the mind as a private, self-contained entity. Habermas argues that meaning is intersubjective, not just in individual minds. Likewise, Markov blanket models show that perception, action, and cognition are shaped by relations across systems, not isolated computation.

However, the big difference is that Habermas is ultimately normative—he wants communication to aim at truth, rightness, and sincerity, governed by rational discourse principles. A Markov blanket perspective is descriptive—it shows how systems interact but doesn’t prescribe how they should.

If you were trying to bring them together, you might argue that:

• Intersubjective communication is a kind of active inference, where interlocutors minimize uncertainty by refining shared models of the world.
• Communicative rationality might be viewed as an emergent property of nested Markov blankets interacting over time—it’s not a given but something that evolves under conditions that favor stable coordination.
• Distortions in communication (e.g., deception, ideology) could be analyzed in terms of information flow, prediction errors, or manipulated priors within a system’s Markov blanket.