Rewriting "The Program:" Derrida’s Of Grammatology in the Age of AI


 Introduction

When Jacques Derrida wrote Of Grammatology in the late 1960s, cybernetics was still in its formative stages. The digital revolution had yet to materialize, and artificial intelligence, as we now understand it, remained largely a theoretical possibility. In The Program, Derrida engaged with the cybernetics of his time to argue that writing—conceived not merely as script but as archi-écriture—precedes and exceeds human speech, cognition, and presence. His intervention challenged the phonocentric bias of Western thought, asserting that meaning is never immediate but always mediated through differential relations. While he acknowledges cybernetics as expanding the field of writing, he also warns that it remains entangled in metaphysical presuppositions that must themselves be interrogated.

The technological limitations of his era inevitably shaped the scope of his analysis. Cybernetics at the time remained largely mechanistic, centered on pre-programmed systems and early information theory. He could not yet engage with the self-modifying processes of machine learning or the linguistic capabilities of contemporary artificial intelligence. However, rather than simply confirming his arguments, AI raises both continuities and challenges within his theoretical framework. This article revisits The Program within its historical context before re-examining its claims in light of contemporary Intelligent Algorithms. First, we reconstruct Derrida’s argument, emphasizing his key claims about writing and cybernetics at the time of Of Grammatology's publication. Then, we turn to modern intelligent systems to assess whether they actualize or extend his insights. To what extent do machine learning models resonate with Derrida’s vision of archi-écriture? Does AI-driven inscription reinforce his concept of writing, or does it introduce theoretical challenges that demand further elaboration?

The Program: Writing as the Condition of Possibility

In The Program, Derrida dismantles the traditional Western privileging of speech over writing, arguing that writing has always been primary. Whereas writing was historically considered a derivative, supplementary form of language, he expands the concept into archi-écriture—a fundamental condition of language in general that precedes and exceeds speech itself. As he states:

"There is not a single signified that escapes, even if recaptured, the play of signifying references that constitute language." (Of Grammatology)

For Derrida, meaning is never fully present but always mediated through traces, deferrals, and inscriptions. Even what appears to be an original, immediate signified is always already structured by an interplay of signifiers. Writing, therefore, is not merely a secondary means of recording speech but the very condition of language itself.

Importantly, he does not argue that cybernetics represents a radical break with prior metaphysical thought. Instead, he suggests that cybernetics exposes what had always been the case: that writing structures meaning in ways previously obscured. He writes:

"Even before being determined as human (with all the distinctive characteristics that have always been attributed to man and the entire system of significations that they imply) or nonhuman, the gramme or the grapheme would thus name the element." (Of Grammatology)

Yet, he remains cautious about the metaphysical presuppositions embedded within cybernetics. While he acknowledges that cybernetics displaces traditional concepts such as "soul," "life," and "choice," he warns that it must still account for its own historico-metaphysical foundations:

"If the theory of cybernetics is by itself to oust all metaphysical concepts—including the concepts of soul, of life, of value, of choice, of memory—it must conserve the notion of writing, trace, gramme, or grapheme, until its own historico-metaphysical character is also exposed." (Of Grammatology)

AI and the Unfolding of Archi-écriture

Modern AI systems provide a compelling demonstration of Derrida’s claim that writing exceeds human presence. Large language models (LLMs) and machine-generated sign systems demonstrate that signification functions independently of speech, presence, or even human intention. Unlike humans, who acquire language through embodied experience and spoken communication, AI systems develop linguistic capabilities solely through textual inscription. This resonates with his argument that language operates primarily as a system of writing rather than speech.

Still, while Artificial Intelligence exemplifies Derrida’s concept of différance—where meaning is never fully present but perpetually deferred—it does not necessarily confirm his broader grammatological project without qualification. He does not suggest that writing requires Machine Learning to function autonomously; rather, his argument is that all language, including human language, was already inscribed within the play of archi-écriture long before Automated Systems. As he states:

"The advent of writing is the advent of this play; today such a play is coming into its own, effacing the limit starting from which one had thought to regulate the circulation of signs." (Of Grammatology)

Thus, while AI demonstrates the autonomy of writing, it does not necessarily mark a fundamental transformation of writing itself. Instead, it reveals what was always the case: that language, even in its so-called "natural" form, has never been an immediate or fully present phenomenon.

The Future Tense and the "Work to Be Done"

Derrida’s use of the future tense in The Program suggests an unfolding transformation rather than a completed rupture. He writes:

"The entire field covered by the cybernetic program will be the field of writing." (Of Grammatology)

This signals a process still in development, rather than a definitive conclusion. In the 1960s, cybernetics was still limited by its mechanical and deterministic models, but Derrida foresaw its potential to challenge traditional metaphysical categories. However, he also warned that cybernetics would not automatically transcend metaphysics; instead, it would remain bound to writing until its own historico-metaphysical character was fully exposed.

From today’s perspective, Intelligent Machines exemplify this paradox. Despite its apparent radical break from human cognition, AI remains deeply embedded in human-designed architectures, biases, and linguistic frameworks. The myth of AI as a "neutral intelligence" is itself a metaphysical illusion, much like the myths Derrida sought to unravel. Intelligent Programs do not escape grammatology; rather, it forces us to confront its operations more explicitly.

Conclusion

Derrida’s insights in The Program remain profoundly relevant in the age of AI. His argument that writing is the fundamental condition of meaning—preceding and exceeding human speech—finds an illuminating counterpart in contemporary machine learning and automated linguistic systems. Artificial Intelligence highlights the grammatological thesis that writing has never been an exclusively human phenomenon. That said, rather than marking an epistemic rupture, Machine Learning functions as yet another manifestation of archi-écriture that must itself be interrogated.

If anything, the rise of Automated Systems reinforces the urgency of Derrida’s project. Rather than simply celebrating Cognitive Computing as an empirical realization of archi-écriture, we must extend his deconstructive approach to interrogate the ways Intelligent Machines reinscribe the very metaphysical assumptions they claim to escape. Far from closing the debate, AI reopens fundamental questions about writing, trace, and the limits of metaphysical thought.

 Related Post

AI and the Chain of Signifiers: Arche-Writing in Machine Learning

https://derridaforlinguists.blogspot.com/2025/03/blog-post_03.html

Bibliography

Derrida, Jacques. Of Grammatology. Translated by Gayatri Chakravorty Spivak. Baltimore: Johns Hopkins University Press, 1976.

Derrida, Jacques. Writing and Difference. Translated by Alan Bass. Chicago: University of Chicago Press, 1978.

Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, Ł., & Polosukhin, I. (2017). "Attention Is All You Need." Advances in Neural Information Processing Systems, 30.

Kaushal, A., & Mahowald, K. (2022). "What do tokens know about their characters and how do they know it?" arXiv preprint arXiv:2206.03406.

Hochreiter, S., & Schmidhuber, J. (1997). "Long Short-Term Memory." Neural Computation, 9(8), 1735–1780.

Bengio, Yoshua, Aaron Courville, and Pascal Vincent. "Representation Learning: A Review and New Perspectives." IEEE Transactions on Pattern Analysis and Machine Intelligence 35, no. 8 (2013): 1798-1828.

Katz, Jonathan, and Yehuda Lindell. Introduction to Modern Cryptography. 2nd ed. Boca Raton: CRC Press, 2014.

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