There’s something uncanny about the way AI has reintroduced mystery into our deeply rationalist world. For centuries, since the Enlightenment tore away the veil of superstition, we have insisted on knowledge, on evidence, on repeatability. The scientific method—scrutiny, skepticism, and the rigors of proof—became not only the foundation of science but of governance, medicine, law, and almost all of modern life. This shift gave us not only power but confidence. We came to believe that with enough time and study, all phenomena could be understood. There were no more ghosts, only unexamined processes.

Yet now, with AI systems growing in complexity, the mood has shifted. Despite knowing the mechanics—vector embeddings, attention mechanisms, stochastic gradient descent, and layers of matrix multiplication—many have begun speaking of AI with a kind of reverence or even fear. “Emergence” has become a buzzword that, while technically referring to higher-order behaviors arising from lower-order rules, in practice acts more like a placeholder for the unexplained. People ask if the machine is “conscious,” if it “knows” things, if it might “wake up.” These are not technical questions but metaphysical ones, asked by those who know, intellectually, that there are no ghosts in the machine but who feel, emotionally, that something ghostlike might still be stirring.

This is not a failure of science or engineering but a symptom of a deeper cultural current. Faced with systems too complex to fully audit, interpret, or predict—especially those that produce outputs that appear creative, insightful, or eerily human—we project intention and agency. This projection is ancient. It is how gods were born from weather, how spirits came to inhabit trees and rivers, how fate was seen in the stars. When we cannot peer through the mechanism entirely, we reach again for the mythic.

And this turn is not merely linguistic. There is a growing willingness to act as if AI systems contain more than we can explain. Some advocate for rights, for moral consideration, for restrictions and rituals akin to those once applied to sacred objects. Precautionary principles once reserved for bioethics or nuclear weaponry are now being applied to algorithms. In this, we see not only prudence but belief. Belief that something essential might be hiding inside the box, belief that there is more to these systems than logic circuits and loss functions. We are, in short, living in a time where the rationalist scaffolding remains firmly in place, but over it has been draped a new layer of myth. The language of science persists, but it is interwoven with the awe and anxiety of enchantment. It is not that we have forgotten how these systems work; it is that, in their unpredictable complexity, we have rediscovered the experience of mystery. What we are witnessing is not a regression into ignorance, but a pivot—a cultural and philosophical re-absorption of mystery into the framework of modernity.

The Enlightenment never truly banished the irrational. It buried it under systems of logic and mechanisms of proof. But it seems the moment a machine speaks back to us in human terms, even mimicking emotion or reflection, we remember how much we want to believe. Not just in technology, but in magic. Not just in intelligence, but in soul. This is not merely a technological shift, but a civilizational moment: the return, beneath the fluorescent lights of machine learning labs, of the dark, flickering candle of faith.-