AI filter

I am struggling to determine how to use the AI filter. On the one hand, the platform claims to be 98% accurate in detecting AI, but on the other hand, it says there may not be academic misconduct. Some students are in an uproar, insisting they did not use AI. Some submissions are not checked for AI- somehow, the filter cannot process them. I don't know if students are finding ways around the filter or if the filter is struggling to process documents. Right now, I am allowing students to re-submit assignments with changes. The whole process is very frustrating. How are other educators handling this new obstacle that is AI. 

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  • Hi Kimberly, 

    Thank you for your post! This is a great question. I'm going to answer this in 2 parts.



    Basically, what is determined to be "Academic Misconduct" would fall on the institutional policy, the classroom policy, and ultimately the teacher. Turnitin provides tools such as the Similarity Report and the AI Detector to help support institutions and educators in their decisions. 

    For example, in relation to AI writing, a teacher may ask students to utilize an AI writing tool to help create their outline for an essay, but want students to develop the essay on their own. Perhaps, that teacher also clearly specified to the students it would be acceptable for some AI writing to be present in their work, but the expectation was the body paragraphs, supporting evidence, thesis statement and concluding statement were all original writing

    When this teacher then reviews the AI Detector report for these submissions, the teacher would be assuming that they (the teacher) would see an acceptable (according to their previous instructions) level of AI Writing within their students' submissions.


    This may not be the case for all teachers or every assignment.

    Each teacher will be able to utilize the AI detection report to make the determination that, if what they are viewing, is in violation of the assignment instructions, classroom policy, school policy, or in some cases, the school district policy.

    A great resource to look at for further suggestions is our Updating your academic integrity policy in the age of AI.


    2. False Positives

    Even with a 98% confidence rate with our AI detection, we understand that there may be false positives.  Meaning, that even though we have focussed our efforts to maintain a less than 1% false positive rate, we acknowledge there is still a small risk. Depending on institutional/classroom policy, a student may have a false positive and may be in danger of being wrongly accused of academic misconduct. 

    Turnitin does not make judgements on Academic Misconduct, but rather provides data for educators to utilize along with their professional judgment, knowledge of their students, and the specific context surrounding the assignment.


    Here are our team's Top three tips for addressing false positives:
    1. Know before you go—make sure you consider the possibility of a false positive upfront and have a plan for what your process and approach will be for determining the outcome. Even better, communicate that to students so that you have a shared set of expectations. 

    2. Assume positive intent—in this space of so much that is new and unknown, give students the strong benefit of the doubt. If the evidence is unclear, assume students will act with integrity. 

    3. Be open and honest—it is important to acknowledge that there may be false positives upfront, so both the instructor and the student should be prepared to have an open and honest dialogue. If you don’t acknowledge that a false positive may occur, it will lead to a far more defensive and confrontational interaction that could ultimately damage relationships with students. 

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