The solution to AI’s effects on school? School.

You’ve heard about it. Students don’t do school because artificial intelligence does it for them. AI summarizes readings, answers questions, generates essays, and adds citations. Agents log into learning management systems and complete coursework. Bots now “write” at human — rather than algorithmic — speed to evade metadata detectors.

Students have achieved wicked technoefficiency, saving time and engagement while generating correct answers and polished products.

Responses? Some teachers pore over (often inaccurate) AI detector results and police students instead of interacting with them. Some assign less homework and reading and instead have students read and write in class so they can watch them. Or they convert essays to blue books — remember those? — shifting writing from an inquiry and exploration process into a content dump.

Dutiful students suffer the surveillance, do the work, and requirements are checked off. “School” happens. Everyone’s disheartened.

But that’s not how it has to be.

We’re longtime Drexel writing teachers who last term taught a new course, “Writing For and About AI.” In the class, we worked with students to take on AI — machine learning — and its impact on writing and their intellectual lives.

We worked with students as they wrote for the machine. It’s their reality: Writing into AI apps already is part of their professional, personal, and civic lives.

We also helped them write about the machine, about AI’s consequences for writing, learning, creativity, work, and the environment.

We aren’t futurists. We couldn’t tell students what their lives will be in five years. But we did all read challenging texts and resources about how transformers parse and mathematicize writing to generate language back at us, how AI may affect our voices and exposure to other voices, differences between writing and generating text, data centers, the future of work, and search technology.

Our students read critiques of AI, but the course wasn’t anti-technology. They also read pro-AI perspectives, and heard from those who see ways to harness AI for school and work.

What we found, as we often do working with our smart, curious undergrads, was not what we — or you — might think.

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Our students didn’t want to do less work, or turn over learning to machines. We’re at Drexel, known for its co-op, and so many students had used AI in business and corporate settings. They’re not naive. They took critical, nuanced stances about AI, its generated content, and the effects of integrating it into their lives.

Students weren’t anti-AI, but they were stressed about AI paranoia, being talked at about AI, and how the “Are students using AI?” focus has damaged their classrooms.

They expressed frustration, worry, and anger about how some students rip through schoolwork with AI. But they were also frustrated about some schoolwork, wondering why they’re not asked more often to do authentic, meaningful assignments. They want to take on problems and questions that matter, thinking deeply and connecting with classmates and teachers.

When overwhelmed with work that feels meaningless, the whole endeavor can become a series of obstacles to the college degree finish line. We don’t — nor did they — justify cheating, but given all that, might they at least be tempted to outsource work to AI?

More broadly, they voiced doubt and often opposition to how AI colonizes their writing, thinking, and working lives. They recognized tension between using AI to automate/eliminate tasks and a desire to preserve meaningful work.

These talented writing students were annoyed that apps would do the powerful writing and thinking they do. As they sharpened prompting skills and experimented with AI — two of our course objectives — they saw how AI does information and language well, but writing, not so much.

Given space to experiment, explore, and learn, our students developed sturdy questions and insights:

Things meaningful to our students matter to us. School is not just learning answers. This class reinforced how important — and enjoyable — it is to work with students asking and developing complex questions.

We didn’t start with answers: The process of thinking, creating, and refining questions is what it was about. In fact, our students might argue that in school — especially with tools that automate so much work — this is exactly what humans should be doing.

Dan Driscoll and Scott Warnock are writing faculty in Drexel University’s department of English and philosophy.