One page, for students. Hand it out at the start of term, not when something has already gone wrong. Print it, paste it into the course page, translate it, change it. No permission needed.
There is no software that can look at a text and know whether a person or a machine produced it. Anyone who tells you otherwise is selling something.
What these tools measure is whether writing looks like the patterns machines produce — even sentence lengths, certain stock phrases, a particular kind of hedging. Human beings write that way too. People who learned English or Spanish as a second language write that way more often, because they were taught the formal register and they stay inside it. People who were drilled in five-paragraph structure write that way. People who are careful write that way.
So being flagged is not evidence that you did anything. It means a piece of software noticed patterns. Software notices patterns in innocent work constantly.
It publishes how often it is wrong about writing known to be human — a figure almost no other tool in this category will state about itself. On its test corpus of 296 texts written before 2022 — published articles, encyclopedia entries, and 206 essays by adult learners of English — it flagged two of them at its recommended setting. The honest reading is the range around that, not the number itself.
Of those 296, 271 were in English. This sheet quotes the English figure, which is the one that applies to you: somewhere under about 3 in 100. If you learned English as a second language, the figure measured on writers like you is under about 4 in 100 — higher than for everyone else, and the tool says so on its own page rather than hiding it in an average. The pooled figure that mixes both languages would credit the tool with a precision measured on a mix, not on writing in your language alone.
It also does something most tools refuse to do: below its supported threshold it prints no verdict at all. A low score is not a certificate that a person wrote something, and it does not claim to be one. A tool that detected nothing would also return a low score.
Your work is not uploaded anywhere. It is analysed on your instructor's machine and it does not leave it.
Not a number. A conversation about your work.
If your instructor asks you about an assignment, they will probably ask things like:
- You wrote this phrase — what does it mean, in your own words?
- Why did you choose this example rather than another one?
- What did you leave out, and why?
- Where did this source come from, and what does it actually say?
These are not trick questions and there is no correct-sounding answer to memorise. Someone who wrote a text can talk about the choices in it. Someone who did not, cannot. That asymmetry, not any score, is what resolves these situations — which is why the conversation is the point and the software is not.
Keep your drafts. Whatever you write in — a document with version history, a folder of dated files, anything. A trail of a piece of work getting made is the most complete answer to any question about it, and it takes no effort to keep if you simply do not delete things.
Keep your sources. Not just the citation — the actual PDF, the link, the page you read. One of the few things a machine genuinely cannot fake is a real source that says what you claim it says.
Ask before, not after. If you are unsure whether a tool is allowed, ask. Every policy has an edge, and asking about the edge has never harmed a student. Using something and hoping is what harms them.
Being asked is not an accusation. Instructors ask about work for many reasons.
Answer honestly, including about any AI tool you used and what you used it for. Under most policies disclosed use is allowed, or at worst carries far less weight than undisclosed use. Bring your drafts, your notes and your sources; if you have them, this usually ends in the same meeting.
If you feel the conversation is going badly, ask two questions, calmly:
What specifically in my work raised the question?
What would I need to show to answer it?
Both are reasonable, and a fair process can answer both. If the only answer you receive is the software said so, that is not sufficient grounds for a decision about you — and your institution almost certainly has an appeals process that says the same. Ask for it in writing.
Say so, as early as you can, and be specific. It will nearly always go better than being found out — and it goes better than a denial that later collapses, which is what turns a small penalty into a serious one.
This sheet describes SignsOfAI, an open-source tool that
runs entirely offline. Its full error rate and the method behind it are published at
Docs/CALIBRATION.md. You are allowed to read them; they are not secret, and
they are not written for insiders.