What AICheatCheck is
AICheatCheck is a detector built for schools and universities. It analyses submitted text for the statistical patterns associated with language model output, with the aim of giving institutions one consistent screening step and, in some deployments, embedding checks into teaching platforms.
What you can do with it
- Screen assignments and papers
- Apply one process across a department
- Check web-page submissions
- Flag material for human review
- Record results alongside other evidence
Who it is for
- Educational institutions
- Teachers handling many submissions
- Platforms wanting embedded checks
What to watch out for
- Accuracy figures come from the vendor's own testing, and detectors misclassify fluent human writing, formulaic academic prose and non-native English
- A flag is not evidence: use drafts, version history and a conversation with the student before any accusation
- Screening every submission treats students as suspects by default, which damages trust
- Student work is sensitive data, so check retention and who can see results
Pros & cons
✓ What we like
- Purpose-built for education workflows
- Consistent process across submissions
- Integrable into platforms
! What to watch out for
- Vendor accuracy claims are self-reported
- Not valid as sole evidence
- Mass screening raises trust and privacy issues
FAQ
Does a flag prove AI use?
No. It is a signal that must be paired with process evidence and a conversation.
Who is most at risk of false flags?
Non-native English writers and anyone using conventional academic phrasing.
What should institutions check?
Retention, who can see results, and how students can contest a flag.
Last reviewed: 2026-09-19
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