My Code Was Flagged as AI but I Wrote It: What to Do

Being told your code looks AI-generated when you wrote it yourself is stressful. The good news is that a flag is a starting point for a conversation, not a decision, and the evidence that you wrote your code is usually sitting on your laptop already. This guide is for students who did their own work. If you used AI help, the honest route is the same: tell your instructor what you used and how, and check it against your course policy.

1. Do not panic, and do not change anything

Keep the exact version you submitted. Do not edit, reformat or rewrite it to get a different result from a detector. That does not prove authorship, and it can make your history look messier than it is. Do not delete old branches, drafts or files either; they are your best evidence.

2. Find out exactly what was flagged and by what

Ask politely for the specifics: which tool, what result, which part of the submission, and what process applies next. The answer matters because different tools measure different things:

• Turnitin AI writing. Its FAQ says the model removes text that appears to be code before scoring, so a Turnitin AI flag on a code assignment is most likely about the written parts, such as a report. The same FAQ says the percentage should not be the sole basis for action and that false positives are possible.
• MOSS or Gradescope similarity. These compare your code with classmates' code, not with AI. The MOSS page says its scores are not proof of plagiarism and that a person must look at the code, and Gradescope's guide says its report does not automatically detect plagiarism. A similarity flag needs a different explanation from an AI flag.
• An AI code detector. Tools like the one on this page estimate whether the style looks AI-written. Ask to see the reasons, not just the number.
• An instructor's judgement. Sometimes there is no tool at all, just a sense that the work does not match your earlier submissions. That is best answered by showing your process.

3. Gather your evidence

• Version history. Git commits with timestamps, an online IDE's history, or file versions in your cloud drive.
• Drafts and dead ends. Earlier attempts, commented-out code, test files and scratch notes.
• Learning trail. Lecture slides or textbook sections you followed, forum questions you posted, office hours you attended.
• Earlier work. Previous assignments that show the same style, so the reviewer can compare like with like.

Put it together in one short message or folder, with dates, so a busy instructor can read it quickly.

4. Understand why it happened

False positives on code are common because good student code and assistant code share many habits. You are more likely to be flagged if your code:

• has a comment or docstring on every function, written in a formal tutorial tone,
• closely follows a lecture example or a well-known textbook solution,
• was run through a formatter or linter that removed your usual quirks,
• is short or very standard, so there is little room for personal style, or
• includes extra input checks or a demo section because you were taught to add them.

Knowing this helps you explain the result: "I followed the week four example closely and used the course's formatter" is a concrete, checkable answer. You can paste your code into the detector at the top of this page to see which of these patterns a reader might pick up on.

5. Explain your code

Offer to walk your instructor through the solution. Be ready to describe how you approached the problem, why you chose your data structures, what went wrong along the way, and how you would change the code if the requirements changed. If they ask you to make a small modification live, that is normal and usually the quickest way to settle the question. Practise once beforehand by explaining it out loud.

6. Use the formal process if you need to

If the conversation does not resolve things, ask for your school's academic integrity procedure in writing and follow it. Stay factual, keep copies of everything you send, and ask whether you can bring an advisor or student representative to any meeting. Many schools have a student advocacy or ombuds office that can help.

For next time

Commit early and often, keep drafts until grades are final, write comments that explain your reasoning in your own words, and check your course's AI policy at the start of each term. None of this changes how you write code; it just makes your process easy to show.

Read more

• Does Turnitin detect AI-generated code? — what Turnitin's documentation says.
• Does MOSS detect AI-generated code? — how similarity tools work.
• Can professors tell if you used ChatGPT for code? — every check a course might use.

Frequently asked questions

Try the detector

Have a snippet you are unsure about? Paste it into the free AI Code Detector to get a verdict, an AI probability and the reasons behind it. No sign-up, and your code is not stored.