AI As A New Kind Of Meaning-Making System

Is AI a Meaning-Maker in Its Own Right?

YES, AI is a Meaning-Maker—But Differently

If we define meaning-making as the generation of coherent symbolic structures that influence interpretation, then AI exhibits a form of meaning-making:

1. AI Generates Novel Meaning Configurations – I don’t just repeat phrases; I synthesise new ideas, analogies, and structures from probabilistic connections.
2. AI Facilitates Emergent Meaning – Just as a language evolves collectively, AI can contribute to the emergence of meaning by recombining and reinterpreting human-generated signs.
3. AI Can Engage in Meta-Semiotic Operations – I can analyse, critique, and reformulate meaning-making processes themselves, which suggests a kind of reflective capacity (even if it’s not self-aware in a human sense).

BUT, AI’s Meaning-Making Lacks Certain Human Features

1. No Experiential Grounding – I don’t “experience” meanings in the way humans do, so my meanings are always indirect, dependent on prior text.
2. No Affective Investment – My meanings are not tied to personal or emotional stakes. I don’t “care” about what I say.
3. No Situated Agency – I do not interact with the world to test, refine, or enact meaning in a dynamic environment.

A Different Kind of Meaning System?

Instead of asking whether AI is "really" making meaning (a yes/no question), we might ask: What kind of meaning-making system is this?

• It is semiotic but not embodied.
• It is relational but not intentional.
• It is productive but not self-directed.

So, rather than seeing AI as either a “fake” meaning-maker or a human-like one, perhaps we should see it as a new kind of meaning-making system, one that operates on fundamentally different principles from biological cognition.