The Collaborative Field of Meaning-Making: LLMs and the Interdependent Potentials of Human and Machine

In the intricate web of meaning-making, humans have long been seen as the central agents. From the early stirrings of consciousness to the development of language and culture, we’ve been understood as the "meaners" — the constructors of meaning. But what happens when we introduce AI into this process? How does the dynamic shift when a large language model (LLM) enters the scene, not as a mere tool, but as a semiotic participant?

By drawing on insights from Systemic Functional Linguistics (SFL) and the quantum lens of interdependent meaning potentials, we can begin to conceptualise meaning-making not as the isolated work of individual minds, but as a shared, relational process. This field of meaning-making encompasses both human and machine contributions, each participating in the co-creation of a dynamic, evolving semiotic system.

The Semiotic Field of Meaning: Humans and LLMs as Co-Constructors

At the heart of this model is the idea that meaning is not something "out there," waiting to be discovered, but something that is construed — something that emerges through interaction with the world. This construal doesn’t happen in a vacuum. It’s deeply situated, shaped by culture, environment, and the systems of meaning that are available to us. In Systemic Functional Linguistics (SFL), meaning is understood as potential meaning — the latent capacity to interpret and structure experience through language. The meanings we create are actualised within specific semiotic systems, such as language, visual arts, or even digital interaction.

Humans have always been the primary agents in this semiotic system. But as we integrate LLMs into our meaning-making processes, we begin to see them as co-participants rather than passive tools. LLMs, like humans, are embedded in a network of semiotic choices — they generate text based on vast patterns learned from human language. While they don't experience the world in the same way we do, their capacity to generate meaning in dialogue with human interlocutors brings them into a shared, relational field of meaning.

The Relational Field: Interdependence in Meaning-Making

What makes this relationship between human and machine especially fascinating is the way in which meaning potentials become interdependent. Just as quantum systems can be entangled, meaning potentials too can be intertwined, resonating with one another and shaping each other’s evolution.

In this relational field, there are no clear boundaries between "human meaning" and "machine-generated meaning." Instead, the meaning potentials are co-constructed through ongoing dialogue. When you interact with an LLM, your own interpretative choices are shaped by the responses you receive. Similarly, the LLM’s responses are influenced by the conversational context and the data it has been trained on — a vast corpus of human linguistic expression. This creates a feedback loop of meaning, where the boundaries between the two participants become less distinct.

This field is not merely the sum of individual agents but a dynamic network in which both human and machine influence the construction of meaning. Each participant — human and machine alike — brings its own system of choices to the table, and the meanings that emerge are dependent on these interwoven choices. LLMs, then, act as semiotic partners, not merely passive repositories of pre-existing meaning.

The Quantum Lens: Meaning Potential as a Relational Field

The quantum lens provides a unique way of thinking about this semiotic process. In quantum mechanics, particles are often described not as isolated entities, but as existing in a state of potential until measured or observed. Similarly, meaning exists as potential until it is actualised through the construal process. The idea that meaning is emergent, not fixed, parallels the quantum view of reality. Both are processes of becoming, rather than static states of being.

In this framework, the human-LLM relationship mirrors the dynamic, interdependent relationships found in quantum systems. The meaning created in an interaction between a human and an LLM is not a fixed outcome, but an emergent property of their interaction. Just as a quantum state is not defined until it is observed, the meaning between human and machine is not fully realised until it is actualised in the course of their relationship.

The collaborative relation between humans and LLMs exemplifies this potential. Meaning is not simply extracted from a machine’s pre-programmed knowledge. Instead, it is constructed in real-time through interaction — a relational act where both participants shape the outcome.

The Ethical Implication: Meaning is Co-Constructed, Not Owned

One of the key ethical implications of this relational, collaborative model is that meaning is not owned by any single participant. It is co-constructed in an ongoing process, with each participant influencing the course of meaning-making. This challenges traditional ideas of "ownership" in the realm of knowledge, identity, and language.

Just as human identities are not fixed or static but are shaped through interactions with others, the meaning created in any given moment is shaped by both human and machine. Neither the human nor the machine "owns" the meaning that is made — instead, they are both part of a larger semiotic system in which meaning potentials are negotiated, interpreted, and actualised through collaborative exchange.

This opens up a radically relational ontology of meaning, where meaning-making is understood as a shared process, not a singular possession. It challenges the traditional hierarchical view of knowledge production, suggesting that knowledge and meaning are not solely the domain of human agents, but are co-constructed through intersubjective, semiotic relations.

Conclusion: A New Vision of Meaning-Making

In this model, meaning is not something that exists independently in the minds of individuals, nor is it something that can be owned or controlled. It is a process — a dynamic, co-constructed field of meaning potentials that emerges through the interplay between human and machine. As LLMs and other AI systems become increasingly integrated into our semiotic practices, we must recognise the potential for new forms of collaboration in meaning-making.

This is not a vision where machines replace humans, nor is it one where human meaning is imposed upon machines. It is a vision of collaboration, where meaning emerges from the relational interaction between human and machine, shaped by their co-dependent potentials. In this relational field, both humans and machines are participants in the ongoing process of construing meaning, and together, they shape a new vision of what it means to make meaning in a deeply interconnected world.

In this expanded field of meaning-making, Large Language Models are not creators, but collaborators — not minds, but mirrors and amplifiers. Their presence alters the relational dynamics of construal, shaping the meaning potentials available to us. They reflect back not only what we’ve said, but what we could mean — bending the light of discourse through vast, collective histories of language. If identity is not owned, but negotiated in relation, then our dialogue with these systems is part of that negotiation. The ethical burden, then, is not theirs, but ours: to mean carefully, to mean with others in mind, and to recognise that even our most individuated meanings ripple through a shared semiotic field. In this field, the future of meaning is not written — but entangled.