Students often assume that AI detection tools must be accurate beyond doubt to justify a cheating case. That assumption is incorrect. Universities do not require certainty to move forward. They often treat AI detection results as indicators, not proof, but indicators can still be enough to open a case.
What matters is not whether the software is perfect, but how institutions use it. AI flags are frequently combined with faculty judgment, writing comparisons, and course context. Together, those elements can justify further action under university standards.
This is frustrating for students because it feels like the burden shifts unfairly. But from the university’s perspective, AI detection tools are part of a broader evaluative process.
Understanding how these tools are used is critical to understanding why cases move forward even when students feel the technology is unreliable.
Richard Asselta has worked with students across the country addressing academic misconduct cases involving AI detection tools. Contact Richard today for a consultation.