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AI INTEGRITY

Put an unassisted checkpoint inside every big task

Not a surveillance measure. A baseline: one small piece of the work, done in the room, that shows what the student can do alone.

Aug 17, 2026 · 1 min read

The risk with AI-assisted work isn't just misconduct; it's that assistance masks the learning gap until the exam reveals it. In the Bastani et al. (2025) field experiment, students with unrestricted AI looked great during practice and 17% worse when the tool was removed. An unassisted checkpoint, one paragraph, one solved problem, one sketch of the plan, done in class partway through a big task, surfaces that gap while there's still time to close it. (Manning's education-agent-skills library formalises this as the unassisted-evidence-checkpoint skill.)

In practice

  • Schedule it mid-task, not at the end: ten in-class minutes producing a small artefact that the final submission must visibly grow from.
  • Frame it as support, and mean it: "this is where I find out who needs help before the deadline," not "this is where I catch you."
  • A big mismatch between checkpoint and final piece starts a conversation about process (see "Ask how they used AI, not whether"), with evidence instead of suspicion.

Quick takeaway: build one AI-free moment into the task, and the final grade stops being a guess.

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Require one doubt, one check, one source

A standing rule for every AI answer: one place it could be wrong, one way to check it, one non-AI source to consult.


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Have students log what the AI did for them

After an AI-assisted task, one honest question: which parts could you now do alone? The answer calibrates them better than any rule.


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Make the AI argue against itself

Ask for the answer, then ask for the strongest case that the answer is wrong. The gap between the two is where the judgement lives.


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