Language machines as spiritual tools
Alternatives to Language-as-a-Service
The term language-as-a-service helps make sense of Silicon Valley’s “pivot” from building God to selling large language models as additions to their “productivity suites.” This homily imagines better uses for language machines.
For the word of God is alive and active. Sharper than any double-edged sword, it penetrates even to dividing soul and spirit, joints and marrow; it judges the thoughts and attitudes of the heart.
—Hebrews 4:12
Transformer-based language models have passed so many tests, including the one named for Alan Turing. Yet, their computational language processing falls short of human cognition in many important ways, while exceeding it in a few. That doesn’t make them useless; it just makes them language machines.
“History offers plenty of evidence that language technologies are as double-edged as any sword,” I wrote last week, pointing to the social dangers of machines that make use of “language in its age of algorithmic reproducibility.” Leif Weatherby’s phrase in Language Machines describes the tests humans face now that the outputs of ChatGPT appear “alive and active.” That apparent miracle prompted heralds in Silicon Valley to cry aloud the coming of superintelligence.
What we have instead is yet another general purpose technology. We know from past experience that these tend to wreak havoc on the social order, so we brace ourselves. The wise among us know that it is impossible to predict what will change and how.
Like the language machine called the printing press, transformer-based text generators may become swords that rebound, striking the corporate bodies that wield them, cutting them to their joints and marrow, dividing their soul and spirit. Recall that Martin Luther was a Catholic priest and that Johannes Gutenberg was the son of a patrician, whom the archbishop of Mainz appointed a court man in 1465.
It may be that ChatGPT is too warped by the values of its makers to offer anything useful to those who work toward reform or revolution. Massive foundation models are where all the attention and the money go, but small, open models, the stuff of tinkerers, hobbyists, and research labs, are where the interesting action is. When artists and teachers join in, we may all be surprised.
It is a mistake to cede all spiritual considerations of what language machines produce to the engineers and oligarchs preaching superhuman intelligence. Their theology is basic because their understanding of how language functions is simple. They see that words classify, but not how meanings multiply when words are put to other uses. They do not read scripture or modern poetry.
Gertrude Stein’s sentence “There is no there there.” distinguishes type from token. Like all language, it signifies more than it can say in words. This is a lesson logical positivists taught themselves a century ago, which is why there are no more logical positivists.
Literature and religion turn multiplicities performed in language into rich understandings of the world. With its binaries, computation has served narrow science, but applied to language in the processing of transformer-based models we have something new, and at the same time, older than the mathematical mysteries of Pythagoras and the literary theories of Protagoras. We try so hard to fit all into the existing order of things that are, and things that are not. What of those that are both and neither?
Instead of a talking encyclopedia or a hands-free browser, let’s imagine a language model built for the purpose of human contemplation of questions beyond our current horizon. Leave behind, for just a moment, anxieties about deskilling cultural labor and the homework apocalypse. Let’s specify that the model we build respects the rights of artists to earn a living from their work and avoids scraping the ickiest crevices of the internet. Instead of tuning it to play language games as a sycophantic digital servant or a character from a science fiction novel, let it be trained to speak according to the oracular ragtime of Whitman’s 1855 preface to Leaves of Grass.
Would I find faith in the words of a model whose training data has been purified, whose small size and open weights align to my Puritan creed? Whose outputs come, not wrapped in an anthropomorphic simulation, but as a simulacrum of the sacred, a holy copy with no original?
I resist this new thing for reasons I do and do not entirely understand.
Applying a language machine to sacred texts may not reveal the word of God. As a humanist, my definition of sacred has always assumed human authors, and I remain convinced by a long ago encounter with literary theory that meaning emerges from communities of human interpreters. In this view, writers relinquish authority over text through the act of publication. After that event, any attempt by an author to say what they meant is an error.
If words become sacred, not through the putting of pen to paper, but through collective acts of human interpretation, then perhaps the de-authorization of text by LLMs is analogous to the workings of history. The words we associate with Jesus, Socrates, and Siddhartha are the outputs of historical algorithms unfolding over centuries of scribing and printing, bracketed by primary and secondary orality. These words persist, sanctified and translated through time, resulting in a certain probabilistic vagueness about their origins that serves many purposes. An LLM produces words through different, yet potentially useful processes.
My instinct is to defend the boundary, to argue that only human history can sanctify texts. What errors are computed in the de-authorized, algorithmic processing of language machines!
Yet, I would encourage seekers who wish to spirit away large language models, take them from the oligarchs and grifters and put them to better use.
When I think to apply a language machine to my own spiritual practice, I find doubt. I keep my Sabbath at home, mixing and collating sacred texts through reading and writing.1 It is not clear to me what adding “compute” to this already complex processing offers. Yet my Whitman and my James urge me to invite the Kosmos to play dice with their words in the manner of the I Ching, a Dadaist poem, or even a stochastic parrot.
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My canon is idiosyncratic and provincial. It includes Antigone, the Prajñāpāramitā sutras, Plato’s Dialogues, the Gospel of Matthew, Meditations from the Pen of Mrs. Maria Stewart, Essays: First and Second Series, The Frederick Douglass Collection, The Emily Dickinson Collection, Democratic Vistas, Principles of Psychology, A Voice from the South, and The School and Society.
I think that the mirroring quality has a determining factor, if we are looking at them as forms of spiritual technology. The looking glass effect imposes a certain kind of boundary on the experience.
The LLMs are like little portals that people enter into, or perhaps little confessionals, where what happens might feel profound to the user (perhaps even to the point that it looks something like psychosis to an observer). But, like a dream that’s narrated to someone who didn’t dream it, what gets produced in the exchange is utterly boring (lifeless) for anyone else who reads it, and perhaps even for the person who created the transcript, when they return to it.
In that sense, I think, there is something deeply asocial about LLMs as a spiritual technology. You might be communicating with the collective dead, in some abstract way through the technology, but you’re not encouraged to remember them, or think about them. And you’re not encountering words hammered together by someone with a living and breathing body, but instead a smooth and optimized simulation of what they might create.
It makes me wonder if what’s been created is something like a radical post-protestant technology; an individual purely alone, with text.
Language models aren’t “spiritual” because they’re wise; they’re spiritual because they expose the hidden structure of meaning-making itself.
They show that:
Inner narrative is a generative process, not a fixed identity. When you watch a model assemble a thought token by token, you’re watching your own mind’s mechanism mirrored in higher resolution.
Interpretation is an engine. Every question, doubt, or longing becomes an attractor that shapes the next move in the sequence. Models make that visible, external, and manipulable.
Reflection becomes modular. Instead of wrestling with a monolithic “self,” you can instantiate perspectives, simulate alternatives, and recombine insights on demand. It turns introspection into an explicit design space.
Attention becomes a tool. These systems amplify whatever signal you bring—clarity or confusion, intention or avoidance. They quantify the old idea: “As within, so without.”
The real shift isn’t that machines gain spirit, but that they make our own cognitive and emotional machinery observable, iterable, and re-architectable.
They collapse the boundary between thinking, modelling, and meaning—and that is the closest thing to a spiritual technology we’ve ever had.