Some AI policies try to define permitted tools, require disclosure, or make the writing process more visible. This one is intentionally starker: students are asked to differentiate themselves from AI in the work they submit.
That means their submitted work should show signs of human judgment, creativity, and reflection that are specific to the course and assignment: close engagement with assigned materials, situated interpretation, accountable evidence, personal revision choices, and claims that do more than reproduce the safest middle of what a chatbot might say.
This policy allows some AI use, but asks students to make sure the final submission goes beyond what AI can easily produce. If a submitted assignment is so generic, detached from course materials, or machine-like that the instructor cannot identify the student’s unique voice and perspective, the student may be asked to revise or redo the work.
The tone matters here. The redo should feel like a route back into the assignment, not a trapdoor into an accusation.
It works best when students know what “differentiation” looks like in practice. Depending on the course, that might mean:
The advantage of this framing is that it keeps the focus on the submitted work rather than on surveillance. The risk is that it gives the instructor interpretive authority over what counts as sufficiently differentiated, which can feel subjective unless the policy is explained with examples and a clear redo path.
Possible syllabus language
You may use AI tools in this course when they help you brainstorm, revise, test ideas, or better understand difficult material, unless an assignment says otherwise.
But you are responsible for making sure that your submitted work clearly differentiates you from AI. That means it should show your engagement with course materials, your judgment about evidence, your interpretive choices, and your ability to explain why your claims matter. If I cannot see enough of your thinking in the work, I may ask you to revise or redo it. This applies whether or not you used AI.
Using AI is not a substitute for reading, thinking, drafting, or learning. You remain responsible for the accuracy, integrity, and intellectual substance of anything you submit.
It does not require the instructor to reconstruct the student’s whole process or prove whether AI was used. The question is whether the work, as submitted, shows something beyond what a generic AI response could offer.
It also gives instructors a way to respond to suspicious or generic work without turning every case into an investigation. “Redo this because I cannot assess your thinking yet” can be a more useful pedagogical response than “prove you did not use AI.” It preserves the instructor’s responsibility to assess learning while giving the student a way back into the assignment.
Subjectivity is the hard part
A policy built around differentiating student thinking from AI output can be powerful, but it needs examples. Without examples, students may experience the standard as vague or arbitrary, especially if they are still learning what strong disciplinary thinking looks like.
The policy works best when students see concrete contrasts: a generic AI-shaped paragraph beside a paragraph that makes a risky, specific, evidence-based choice. Otherwise, “differentiate yourself” can sound like a vibe rather than an assessable expectation.
It is also worth naming the fairness problem. Some students write in polished, generic academic prose because they have been trained to do exactly that. Others may sound unlike themselves because they are multilingual writers, anxious writers, or writers still trying on disciplinary voice. A redo policy should be framed as an opportunity to discuss what makes work specific, creative, and assessable, not as an automatic accusation.
I would not rely on the syllabus statement alone. The policy needs to appear again inside assignments and class discussions, especially in the first few weeks, with language specific to that task:
I would also build in a low-stakes practice version before using the policy on a major assignment. Students could compare an AI-generated response with a stronger student response and identify where the human thinking becomes visible.