A Brown professor recently looked at his class and realized something chilling: he suspected the majority of them had used AI to complete their assignments. The internet did what the internet does — it clutched its pearls, debated the ethics, and demanded stricter policing.
But everyone’s arguing about the wrong thing.
The students didn’t break the system. They just showed you what the system actually rewards. And it isn’t learning.
If your test can be passed by a machine that doesn’t understand the subject, your test wasn’t measuring understanding — it was measuring compliance.
Think about what a typical college assessment looks like. You write an essay. You produce a report. You submit a deliverable. The professor reads the output and assigns a grade. The process — how you got there, whether you struggled, whether you actually transformed your thinking — is invisible. It was never part of the equation.
For decades, this worked fine by accident. Producing a passable essay required enough effort that you’d probably learn something along the way. The output and the learning were tangled together. You couldn’t get one without the other.
AI severed that connection. Completely. Permanently.
Now a student can produce a polished paper in minutes without engaging with a single idea. The output looks identical to the one produced by someone who spent three days wrestling with the material. And that’s not a bug in the student’s behavior — that’s the system’s architecture being exposed.
One commenter on the original story said it perfectly: “If there is a smart shortcut we will take it. It’s how we became the humans we are today.” Another added, “Sadly most students have not been taught how to value learning. They just want a high mark with the least effort.”
They’re both right. And they’re both describing the same thing from different angles.
You built a system that rewards grades, then got mad when students optimized for grades. That’s not a cheating crisis — it’s an incentives crisis.
Here’s what nobody in academia wants to hear: the students are acting rationally. They’ve been told, explicitly and implicitly, for their entire lives that the grade is the point. The GPA gets you into the next school. The degree gets you the interview. The credential opens the door. Nobody ever asked them, in any formal way, to demonstrate that they’d actually changed how they think.
So when a tool comes along that produces the required output with minimal effort, of course they use it. You would too. You do — every time you use a calculator instead of long division, every time you Google instead of memorizing, every time you use a template instead of starting from scratch.
The difference is that those earlier tools automated skills we’d already agreed were commoditized. AI is automating the last thing left: the production of the artifact that earns the credential.
And that terrifies educators, because it threatens the one thing they control: the assessment.
The fear isn’t that students will stop learning. The fear is that everyone will realize the credential never proved they had.
What would fix this? Not AI detection software. Not honor codes. Not stricter penalties. Those are band-aids on a severed artery. The fix is changing what you measure.
If you want to know if someone can think, test their thinking. Put them in a room. Watch them reason through a problem in real time. Ask them to critique their own AI-generated draft. Make them defend a position against pushback. Assess the process — the iteration, the struggle, the revision — not just the polished artifact that comes out the other end.
This is harder. It’s messier. It doesn’t scale to a lecture hall of 300. And that’s exactly the point. If your assessment scales effortlessly, it’s probably measuring something a machine can fake.
The Brown professor is right to be alarmed. But the alarm shouldn’t be about AI. It should be about a system that spent decades confusing the signal for the thing it was supposed to signal. AI didn’t create that confusion. It just made it impossible to ignore.
Every student who uses AI to cheat is holding up a mirror. What academia sees in it is a reflection of what it chose to value — and it chose grades over learning a long, long time ago.
FAQ
Q: Are you seriously saying cheating is justified?
A: No. I'm saying the behavior is rational given the incentives. Calling it 'cheating' misses the point — the system was always measuring output, not learning. AI just exposed the gap that was always there.
Q: So what should educators actually do?
A: Stop assessing artifacts. Start assessing process — real-time reasoning, iteration, defense of ideas, critique of AI-generated work. If your test can be faked by a machine, it was never measuring what you thought it was.
Q: Isn't this just letting students off the hook?
A: The contrarian take: the students who use AI are the ones who understood the system best. They saw that the grade was the product and optimized for it. The problem isn't their strategy — it's that the strategy works.