Everyone Is Cheating on Homework – So Stop Grading It
A majority of American teenagers — 59%, from a Pew survey out this year — say cheating with AI has become a regular feature of student life. We don’t know how many of the remaining 41% tell the truth on surveys. Every high schooler I ask puts the number higher. They know it’s bad: a RAND survey this winter had 67% of students agree that using AI for schoolwork harms their critical thinking. They use it anyway.
I’ve talked to teachers and school leaders from elementary school to graduate school. I see three main ways schools are handling this wave of AI use:
Punish it: Detect AI use on homework; treat it as cheating.
Prevent it: Move to live assessments – oral or offline – that are hard to cheat on.
Embrace it: Assess the synthesis, not the output.
While all three are common, the first one is a dead-end.
The first approach: Punish AI use
This is widespread today – AI detection tools are everywhere. But teachers should avoid this. Even with good intentions, it usually sparks an adversarial game where students then also use detectors and humanizers to hide their AI use. And so far, students have adapted faster than the tools trying to catch them. The focus shifts from learning to avoiding detection.
School network bans and tutors-with-guardrails don’t work either, at least not standalone. They can’t protect take-home assignments when uncensored ChatGPT is one tab away.
We should just stop grading take-home work that AI can do. If you are testing foundational facts, Prevent is more effective and less adversarial. If it’s about rewarding creativity and sustained effort, Embrace is better.
The University of Chicago Law School just announced a thoughtful AI policy that even non-law schools should look at. The point is to protect critical thinking, not to ban AI. Punishment and detection are nowhere to be found in that document.
The second approach: Prevent AI use
Some knowledge is foundational: basic literacy and numeracy, basic history, and basic science, for example. You don’t absorb this in your everyday experience – it needs to be taught. Students should learn these things, even though computers can do them perfectly. Cognitive scientist Daniel Willingham tells us why. You can only think with the knowledge actually in your head, not the knowledge sitting in a book or chatbot. So we all still need to learn foundational concepts – though what counts as foundational will keep evolving.
Some struggle is useful for learning them. Using AI to generate answers before you understand removes this useful struggle. Assessments need to preserve what Terence Tao calls natural friction to train your mind.
For foundational knowledge that requires struggle, we should make the assessment itself AI-proof. Paper exams are making a resurgence – good. So are oral exams. It’s hard for a student to fake understanding at the speed of a live conversation. The only downside is that it doesn’t scale. Maybe scaling this kind of assessment is where AI should actually be helping.
AI could shift from cheating-enabler/detector to knowledge-assessor – and move the teacher from adversary to coach.
The third approach: Embrace AI use
Once you have enough of a foundation, you can learn to work with AI. This is where the economic value lies – engineers, lawyers and doctors are all using AI today, embedded in their professional tools.
A long essay or computer science project – the kind that requires multiple sittings – is still valuable as a take-home, but only if working with AI is the point. The grading moves from the artifact to an oral defense of it. If you outsource your argument to an AI, you’re caught in the first minute of a live back-and-forth. If you came up with a first draft and went back-and-forth with the AI to strengthen it, that will survive a ten-minute conversation with your teacher. Students show their work by pointing to their own ideas, and by sharing the AI session itself.
The teacher’s job here is to encourage effective AI use. Get this right, and it lets students take on vastly bigger problems, and get a feel for work that is just beyond their abilities. Success looks like a middle schooler in a summer camp drafting their first novel, or a high schooler launching an app in their community. I’ve seen both of these stories. That kind of excitement compounds, and gives a taste of the world they are entering.
So stop punishing the cheating. Protect the learning foundation with assessments that can’t be gamed. Then on top of that foundation, work with AI to build big things in the real world.
In the spirit of Embrace, watch my collaboration with Claude as I wrote this essay: homeworkbench.org/essay (this is my real drafts and actual conversation; the webpage itself was 100% AI-generated)