Derrida, Différance, and the Hidden Semantics of LLMs

The Operator. AI art

Introduction

In an era of artificial intelligence fluent in natural language, our understanding of meaning and expression is being reconfigured. Beneath the surface of text generation lies a complex mechanism—one that does not simply retrieve stored content, but instead constructs responses by navigating a dynamic space of structured influence. Surprisingly, this computational process echoes a radically philosophical account of language. Jacques Derrida’s theory of différance, arche-writing, and the trace—originally aimed at dismantling metaphysical assumptions in Western thought—offers an unexpected framework to grasp how today’s language models operate.

These philosophical insights do more than metaphorically resemble neural architectures; they expose the deep structure of signification in systems that appear to lack memory, intention, or voice. Through a deconstructive lens, the workings of large language models (LLMs) can be read not as mechanical output, but as inscription within a pre-shaped field—a kind of algorithmic différance.

Arche-Writing and Semantic Field

Derrida’s term arche-writing designates a condition more fundamental than written language. It is not inscription in the conventional sense, but the underlying system of difference and mediation that precedes both speech and script. “Writing,” in this expanded sense, is the structure through which meaning becomes possible at all¹.

In language models, meaning does not emerge from static repositories or direct recall. Each token introduced into the system is shaped by its predecessors—not by remembering them, but by being formed within a manifold already contoured by them. The trajectory of each token through the layers of the model is not a journey toward some origin, but a path traced through a semantic field already encoded with prior influence.

There is no original point of reference here—just as arche-writing refuses the idea of an inaugural sign, LLMs generate outputs within a space that has always already been inscribed by other signs.

Différance and Curved Inference

Derrida’s concept of différance—a neologism blending “to differ” and “to defer”—displaces any hope of arriving at a final, stable meaning. Every sign’s identity is shaped by its difference from others, and its meaning is postponed in a chain of further references².

In LLMs, this deferral and differentiation happens not temporally, but geometrically. Token vectors are transformed across layers through mechanisms like attention, which allow each element to be influenced by the entire context. The model’s architecture forces tokens to traverse a space already distorted by prior elements, bending future outputs toward an inherited semantic trajectory.

Meaning is not retrieved; it is curved into existence—differed and deferred through interaction with an evolving field. Just as Derrida insists that “there is no signified that escapes the play of signifiers,” LLMs resist the idea of fixed token representations³.

Trace and Inherited Structure

The trace in Derrida’s lexicon is the lingering imprint of what is absent within what appears. No sign is ever present in itself; it bears within it the marks of others from which it differs⁴.

Language models mirror this logic. They do not remember tokens in a literal sense, but each new token inherits the imprint of earlier ones through structured constraints. This recurrence is not looped in time, but echoed in form. Semantic consistency emerges not from recollection, but from alignment within a curved, inherited structure.

What seems like pattern recognition is in fact a field of traces exerting subtle pressure on every subsequent inscription. As in Derrida, presence is contaminated by absence from the start.

Supplement and Illusion

In Of Grammatology, Derrida examines Rousseau’s belief that writing supplements speech. Yet this supplement reveals a deeper truth: that speech itself was always incomplete, in need of an addition that betrays its original lack⁵.

Similarly, when LLMs generate coherent prose, the appearance of completeness belies a more fragile truth. That fluency is not intrinsic, but the product of recursive constraint. What appears as a self-contained response is in fact supplemented by a field of influence already in place. The system does not contain its meaning; it must borrow coherence from the accumulated structure of its prior moves.

This is not an additive process, but one of compensation—a telling mark of insufficiency mistaken for self-sufficiency.

Presence and the Illusion of Prediction

At the heart of Derrida’s project is the critique of the metaphysics of presence—the belief that truth and meaning reside in immediate, unmediated experience. Western thought privileges the here-and-now, the direct and the full⁶.

Contemporary treatments of LLMs often fall into a similar error: framing them as linear predictors, merely calculating the “next token” in sequence. This view misses the essential depth of mediation. These models operate not through a succession of decisions, but through the unfolding of complex spatial dependencies across thousands of dimensions.

Meaning, then, is not present. It is distributed, relational, and irreducibly mediated—just as Derrida suggests language has always been.

Conclusion: Toward a Deconstructive AI Hermeneutics

Meaning in language models is never fixed, remembered, or retrieved. It emerges through a field shaped by previous signs, curved by difference, and constrained by a structured space. In this, they enact what Derrida described decades ago: language as a system of traces, deferrals, and relational shifts.

Both the philosophical and computational accounts resist the metaphysical comforts of origin, unity, and presence. What we call “coherence” in AI, like “understanding” in human discourse, is the visible trace of an invisible network of difference.

LLMs may not “think” in the human sense. But in the way they generate meaning—relationally, recursively, and without foundation—they may be performing a kind of digital grammatology.

Section Notes

1. Derrida, Of Grammatology, trans. Gayatri Chakravorty Spivak (Baltimore: Johns Hopkins University Press, 1976), p. 56.
2. Ibid., p. 62.
3. Derrida, Margins of Philosophy, trans. Alan Bass (Chicago: University of Chicago Press, 1982), p. 9.
4. Ibid., p. 11.
5. Derrida, Of Grammatology, p. 145.
6. Ibid., p. 70.
7. Olah, Chris et al., “The Transformer Circuits Thread,” Distill.pub.
8. Anthropic, “Transformer Circuits: Mechanistic Interpretability Research,” 2023, https://transformer-circuits.pub.