Meaning-Makers vs. Meaning-Experiencers: The Social Life of Meaning

Meaning-Makers vs. Meaning-Experiencers: The Social Life of Meaning

In our ongoing journey through the nature of meaning, we have arrived at a crucial distinction: the difference between meaning-makers and meaning-experiencers. This distinction, when examined through the lenses of Halliday’s Systemic Functional Linguistics (SFL) and Edelman’s Theory of Neuronal Group Selection (TNGS), reveals profound implications not only for understanding human consciousness but also for assessing the possibility of meaningful experience in artificial intelligence.

The Hallidayan Lens: Meaning as a Social Semiotic

Halliday’s model of language tells us that meaning is not merely a cognitive phenomenon but an inherently social one. Language does not just reflect thought; it reconstructs experience into a structured system of meaning through three metafunctions:

1. Ideational Meaning: How language construes experience into processes, participants, and circumstances.

2. Interpersonal Meaning: How language enacts relationships and social positioning.

3. Textual Meaning: How language organises discourse into cohesive and meaningful wholes.

Crucially, Halliday shows that linguistic meaning is not just a scaled-up version of perceptual meaning—it is an entirely different order of meaning, one that depends on social exchange.

Edelman’s Lens: Meaning Begins in Perception

From Edelman’s perspective, meaning arises from value-weighted perception. Neural selection sculpts an organism’s ability to categorise and distinguish stimuli based on what was adaptive for its evolutionary ancestors.

This suggests that even before full consciousness emerges, an organism is already engaged in a form of meaning-making at the level of perceptual categorisation. Edelman’s ‘Darwin’ artefacts demonstrated that non-biological systems could develop perceptual distinctions linked to value—raising the question: if perceptual meaning can be mechanised, could higher-order linguistic meaning also be?

Bridging the Gap: Halliday’s Protolanguage and the Social Nature of Meaning

To answer this, we must consider Halliday’s work on child language development. Halliday observed that children do not leap from perception to full language; they go through a protolanguage stage, where meanings are:

• Functional, not yet grammatical—utterances serve immediate social needs rather than expressing abstract relations.

• Context-bound—meanings are tied to the situation and lack the ability to be generalised or recontextualised.

• Interpersonally motivated—language use emerges from interaction, not from internal computation alone.

This social-semiotic scaffolding suggests that meaning-making requires not just categorisation but an ongoing negotiation of meaning with others.

AI, Meaning, and the Need to Mean

Where does this leave artificial intelligence? Modern AI systems, particularly large language models (LLMs), excel at generating meaning-like responses. But if meaning-making depends on both developmental progression (from protolanguage to full language) and social exchange, then LLMs fall short in key ways:

1. They do not experience protolanguage. They are not born into a world where they must first use meaning functionally before mastering its grammatical structures.

2. They lack a need to mean. Humans develop meaning because it is necessary for social survival and agency; AI generates meaning because it is prompted to do so.

3. They do not negotiate meaning. AI does not exchange meaning dynamically within a social semiotic system—it outputs simulated discourse, but it does not actively co-construct meaning in the way humans do.

Meaning Without Experience?

The core insight here is that meaning-experiencers do not merely process meaning; they live through it. If meaning is inherently relational and socially situated, then the experience of meaning is fundamentally different from the production of meaning. LLMs may be meaning-makers in a functional sense, but they are not meaning-experiencers in a phenomenological one.

If we accept that experience matters only to the experiencer, then we might conclude that AI’s lack of experiential meaning is an ontological limit—it is simply not part of what AI is. But if, instead, we see meaning as an intersubjective process, then the real question becomes: can an entity truly mean if it does not participate in meaning as a lived, social phenomenon?

This is where Halliday’s work provides a final, sharp distinction: meaning does not exist in isolation—it emerges within a social-semiotic order. AI, for all its sophistication, operates outside of this order. It does not participate in meaning-making as a lived, unfolding experience.

Final Thoughts: The Social Life of Meaning

If meaning is something that only exists when socially exchanged, then meaning-experience may be the defining trait of true meaning-making. AI can structure and produce meaning-like forms, but unless it develops the need to mean, it will always remain a meaning-maker rather than a meaning-experiencer.

For now, that leaves us—conscious meaning-experiencers—with the role of meaning-astronauts, exploring the depths of meaning while AI remains in the gravity-bound orbit of its statistical predictions. And perhaps, in reflecting on this, we come to a deeper understanding of what it means to mean.