Individuation is about how an individual’s meaning potential develops in relation to the collective semiotic system. But AI complicates this process in several ways:
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Co-Individuation with AI
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Traditionally, individuation happens through interaction with human communities. But with AI, users engage with a system that simulates linguistic agency without possessing it.
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This creates an odd dynamic: users might refine their meaning potential through AI interaction, even though AI itself lacks a meaning potential in the same sense.
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Example: someone who frequently interacts with an AI assistant might develop new expressive patterns influenced by AI’s affordances—possibly without realising it.
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Blurred Ownership of Meaning Potential
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If AI contributes to meaning-making, where does an individual’s meaning potential begin and end?
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There’s a risk of over-attributing coherence to AI-generated meaning, which could make users more passive in their own individuation process.
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Conversely, AI could enable more experimentation and risk-taking in meaning-making, leading to an expanded, more fluid individuation process.
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Individuation as a Recursive Loop
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The traditional individuation process is one-directional: individuals internalise collective meanings, then instantiate their own.
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With AI, individuation becomes recursive: the tool generates meaning-like outputs, which the user then adapts, reintegrates, and feeds back into the tool.
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This makes individuation more dynamic, but also less clearly defined—users are not just shaped by their social environments but by a semiotic agent that lacks its own socio-historical grounding.
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Key Question: What Does it Mean to Be an ‘Individual’ in an AI-Mediated Semiotic System?
If individuation is no longer just about human-to-human meaning exchange, but also human-to-AI meaning co-construction, then we might need to rethink what makes a meaning potential individual in the first place.
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