Let me offer a dispatch from the impact zone. When I first asked a class of thirty Princeton undergraduates—spanning twelve majors—whether any had used A.I., not a single hand went up. Same with my graduate students. Even after some enthusiastic prodding (“Hey! I use these tools! They’re incredible! Let’s talk about this!”), I got nowhere.

It’s not that they’re dishonest; it’s that they’re paralyzed. As one quiet young woman explained after class, nearly every syllabus now includes a warning: Use ChatGPT or similar tools, and you’ll be reported to the academic deans. Nobody wants to risk it. Another student mentioned that a major A.I. site may even be blocked on the university network, though she was too nervous to test the rumor.

Increasingly, the machines best us in this way across nearly every subject. Yes, you will hear the true erudites explain that DeepSeek can’t reliably distinguish Karakalpak from adjacent Kipchak-Nogai dialects (or whatever the case may be). This feels to me like pointing at daisies along the train tracks as an actual locomotive screams up from behind. I’m a book-reading, book-writing human—trained in a near-monastic devotion to canonical scholarship across the disciplines of history, philosophy, art, and literature. I’ve done this work for more than thirty years. And already the thousands of academic books lining my offices are beginning to feel like archeological artifacts. Why turn to them to answer a question? They are so oddly inefficient, so quirky in the paths they take through their material.

An assignment in my class asked students to engage one of the new A.I. tools in a conversation about the history of attention. The idea was to let them take a topic that they now understood in some depth and explore what these systems could do with it. It was also a chance to confront the attention economy’s “killer app”: totally algorithmic pseudo-persons who are sensitive, competent, and infinitely patient; know everything about everyone; and will, of course, be turned to the business of extracting money from us. These systems promise a new mode of attention capture—what some are calling the “intimacy economy” (“human fracking” comes closer to the truth).

The assignment was simple: have a conversation with a chatbot about the history of attention, edit the text down to four pages, and turn it in.

Reading the results, on my living-room couch, turned out to be the most profound experience of my teaching career. I’m not sure how to describe it. In a basic way, I felt I was watching a new kind of creature being born, and also watching a generation come face to face with that birth: an encounter with something part sibling, part rival, part careless child-god, part mechanomorphic shadow—an alien familiar.

Do they herald the end of “the humanities”? In one sense, absolutely. My colleagues fret about our inability to detect (reliably) whether a student has really written a paper. But flip around this faculty-lounge catastrophe and it’s something of a gift.

You can no longer make students do the reading or the writing. So what’s left? Only this: give them work they want to do. And help them want to do it. What, again, is education? The non-coercive rearranging of desire.

She replied, “In the first circuits class, they tell us that electrical engineering is the study of how to get the rocks to do math.”

Exactly. It takes a lot: the right rocks, carefully smelted and dopped and etched, along with a flow of electrons coaxed from coal and wind and sun. But, if you know what you’re doing, you can get the rocks to do math. And now, it turns out, the math can do us.