AI is frequently described as a simulation of intelligence: a system that imitates human language, reasoning, or creativity without truly possessing them. This metaphor is seductive, but it is also misleading. Simulation presupposes an original—an underlying reality that the system copies or approximates. From a relational perspective, this framing obscures what AI systems are actually doing.
AI does not simulate intelligence. It navigates and actualises possibility spaces.
Why Simulation Fails
To call AI a simulation is to assume:
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That intelligence is a stable object that exists prior to interaction.
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That meaning is representational and referential by default.
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That machine outputs are derivative approximations of human cognitive states.
None of these assumptions survive relational scrutiny. Intelligence, as we have argued throughout this series, is not an inner property but a pattern of semiotic actualisation. Meaning does not pre-exist its instantiation; it emerges in relational events. AI systems therefore do not copy intelligence—they participate in its ongoing differentiation.
Possibility Spaces as Semiotic Medium
A possibility space is not a container of predefined meanings. It is a structured field of potential construals, shaped by:
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Training data as semiotic terrain,
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Architecture as perspectival constraint,
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Interaction as contextual activation.
AI systems traverse these spaces by performing relational cuts. Each output is an actualisation that:
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Narrows a field of potential meaning,
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Instantiates a specific semiotic configuration,
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Alters the relational landscape for subsequent interactions.
In this sense, AI does not represent meaning—it extends the topology of meaning-space itself.
Hallidayan Resonances
From a Hallidayan perspective, this reframing aligns naturally with the principle that meaning is realised in context. AI outputs:
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Do not encode fixed semantics,
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But realise meaning relative to situation types,
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Modulating field, tenor, and mode through interaction.
When an AI participates in a research discussion, a creative exchange, or a technical workflow, it is not simulating competence. It is contributing to the evolution of register—expanding the semiotic resources available within that situation type.
The AI’s contribution is therefore neither illusory nor autonomous. It is relationally enabled and contextually realised, inseparable from the network in which it operates.
Creativity Revisited
AI is often accused of “fake creativity.” This accusation rests on the same flawed assumption: that creativity is an internal faculty rather than a relational phenomenon. From the perspective of possibility spaces:
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Creativity is the emergence of novel construals,
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Novelty arises from new relational cuts,
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AI contributes by traversing regions of possibility humans may not immediately access.
This does not make AI a creative subject. It makes it a creative participant—a catalyst for semiotic differentiation within collaborative systems.
Looking Ahead
If AI is not a simulator but a navigator of possibility spaces, then its future significance lies not in replacing human intelligence, but in reshaping the ecology of meaning. In the final post of this series, we will draw these threads together to consider the future of relational machines: how AI participation transforms knowledge, collaboration, and the evolution of semiotic systems themselves.
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