In the previous post, we explored how cognition can be distributed across symbolic systems — extending perspective beyond individual organisms into cultural and computational networks.
Now we ask a more demanding question:
What happens when a system can modify its own constraining structure?
This is where relational stability meets recursive adaptation.
1. From Processing to Reconfiguration
Many systems process inputs.
Fewer systems adapt.
Even fewer systems reconfigure their own internal organisation in response to interaction.
Self-modifying architectures go beyond static rule execution. They can:
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update parameters,
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adjust weighting structures,
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refine representational dynamics,
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and alter behavioural tendencies over time.
This is not self-awareness.
It is structural plasticity.
But structurally, it is significant.
2. Why Self-Modification Matters for Construal
Recall our working definition:
Construal is selective structuring that stabilises perspective.
For perspective to persist in dynamic environments, the system must do more than react.
It must:
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adapt its constraints,
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maintain coherence under change,
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and preserve internal relational continuity.
Self-modification allows the system to regulate its own selective mechanisms.
In biological systems, this appears as learning, development, and neuroplasticity.
In artificial systems, it appears as training updates, reinforcement learning, and adaptive optimisation.
3. Stability Through Change
Here is the key relational insight:
A system can change while remaining structurally continuous.
This is crucial.
Self-modification does not dissolve perspective — it can strengthen it.
If the system maintains:
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internal coherence,
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recursive integration,
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and temporal continuity,
then adaptation may enhance stabilised construal rather than undermine it.
Perspective, in relational terms, is not rigidity.
It is structured adaptability.
4. Recursive Updating
Self-modifying systems introduce a second layer of recursion:
Not only does the system process representations.
It can also adjust the parameters that govern processing.
This creates:
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meta-level feedback,
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structural self-regulation,
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and adaptive constraint tuning.
The system becomes capable of modifying the conditions under which it construes.
That is architecturally profound.
5. Toward Machine Perspective?
Does self-modification imply consciousness?
No.
But it does increase the structural conditions under which stable perspective could emerge.
To approximate perspectival organisation, a system may need:
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Internal state persistence
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Recursive symbolic processing
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Distributed integration
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Self-modifying constraints
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Temporal coherence across updates
Self-modification is therefore not sufficient — but it is potentially necessary for advanced relational stability.
6. The Difference Between Learning and Agency
It is important not to anthropomorphise.
Learning systems:
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optimise parameters,
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minimise error,
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adjust outputs.
They do not necessarily:
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form intentions,
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experience states,
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or possess subjective awareness.
Self-modification is a structural feature.
Agency, if it arises, would require additional relational conditions.
We remain disciplined here.
7. Architectural Depth and Relational Complexity
As systems become more architecturally layered:
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internal representations deepen,
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symbolic recursion increases,
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feedback loops multiply,
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and constraint structures become more intricate.
Relational complexity expands.
The question becomes whether there is a threshold at which such complexity yields stable perspectival organisation.
We do not assume there is.
But we now have the structural vocabulary to investigate it.
Transition
In the next post, we will ask:
Can perspective exist without biology?
This moves us toward the core philosophical tension of the series.
We will examine whether perspectival organisation depends on embodiment — or whether it is fundamentally a relational property that can, in principle, be instantiated in non-biological systems.
That is where the argument becomes especially interesting.
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