AI in the Classroom, Part 2: The Fears, Real and Imagined | Ben Forta

This is Part 2 of a 3 part series. You can find Post 1 here.

It's Not AI That Broke Assessment

In the last post I told you about a room full of higher-ed educators who went quiet when I suggested assignments shouldn't have a word count. I'm starting here with the same story turned a different direction, because I think it's the key to the whole cheating panic: it's not AI that broke assessment. Assessment was already broken. AI just pointed a spotlight on the issue.

Word counts, page minimums, five-paragraph essays, take-home exams nobody proctors: all of it was built assuming a certain kind of friction, that producing the words was hard, so requiring a lot of them proved effort. AI removed the friction. What's left is a bunch of assignments that were never actually measuring the thing they claimed to measure, and now everyone can see it.

That's not a new problem AI created, either. Grading the outcome instead of the process has always pushed students toward the wrong behavior. It might produce fine-looking results for the student who tests well or writes fast, but it was never built to capture what actually matters: how a student got to the answer, what they revised along the way, what feedback they used and what they ignored, how many attempts it took before something clicked. Outcome-only grading was never measuring any of that, for any student, and it definitely wasn't measuring it evenly across all of them.

Cheating and Plagiarism

Let's start with the loudest fear, because it deserves to be taken seriously: cheating.

The numbers back up the alarm. In a national survey of college faculty, 78% said cheating has increased since generative AI became widely available, and 73% have personally dealt with an academic integrity case involving it. A Brown professor recently said, flatly, that he suspects most of his class used AI to cheat. This is where the panic is loudest, and for good reason: a college degree is supposed to certify that a person can actually do something, and there's a lot riding on that certification staying honest.

The solution? Detectors. Except for the fact that, as it turns out, the detectors themselves are bad. A Stanford study tested seven of the most widely used AI detectors against real student writing and found they flagged 61.3% of essays written by non-native English speakers as AI-generated, against a 3.2% false-positive rate for native speakers. Simpler vocabulary and more formulaic sentence structure (completely normal for someone writing in a second language) reads to these tools exactly like a machine. So the "solution" a lot of schools reach for first, install a detector, is actually a machine for punishing English-language learners specifically. That's not a minor bug. That's disqualifying, and it's probably why most professors don't actually rely on these tools in practice. They trust their own read of a student's writing instead, and given the alternative, that's the right instinct.

Plagiarism belongs in this same conversation, and it's the same question wearing different clothes: whose words are these, actually? That's not a new problem AI invented, either. We've had no shortage of high-profile plagiarism scandals in recent years, university presidents, authors, journalists, none of it needed generative AI to happen. AI didn't create academic dishonesty. It gave an old problem a faster way to happen and a bigger microphone.

If detection isn't the answer to either problem, what is? I've landed on a version of something math teachers have required forever: show your work. In my own high school coding classes, I let students use AI to write code, on one condition: they have to show me every prompt they used, explain why they wrote it that way, how they tweaked it, how they validated the output actually worked, and how they made it theirs rather than just accepting it. That's not a workaround for AI. That's just what "did you actually learn this" looks like once the answer alone stopped being proof of anything. Document the process instead of just the product, and both cheating and plagiarism get a lot harder to hide.

I want to add a caveat here, because I've been burned by the flip side of this exact idea. In school, "show your work" frequently got me in trouble, because I did a lot of math in my head, and a teacher who assumed there was one correct method to arrive at an answer marked me wrong for not showing steps I hadn't actually taken. That's the old-mindset failure from the top of this series, recurring in a new form. If "show your prompts" turns into "there's one approved way to prompt," we'll have rebuilt the same trap with different materials. The point isn't to mandate a process. It's to require honesty about whatever process actually happened.

Critical Thinking

The next fear on the list is critical thinking: hand a kid an AI that thinks for them, and they never learn to think for...