We use cookies and similar technologies to understand our visitors’ experiences. By continuing to use this website, you agree to this condition of use. For further information, please see our privacy notice.

Learning Design Center

Schedule a Consultation
Lots of equipment on a table while people have a meeting

Use of AI Detection

What to know before you use an AI detection tool

Turnitin AI Detection is currently the only AI detection tool supported by the University of San Diego and available to faculty when a student submits their assignment in Canvas. Due to intellectual privacy and data security considerations, faculty should not upload student work into external AI detection tools or web applications to verify students' originality.

Before using an AI detection tool, it is important to understand what the tool can and cannot do to ensure that any concerns about academic misconduct are justified and appropriately supported. AI detection tools analyze patterns such as predictability and sentence variation. They do not assess the truthfulness of content or the extent of student learning.

Research indicates that while detection tools can distinguish between AI-generated and human-written text with moderate to high success, none are fully reliable (Erol et al., 2025). False positives can occur, meaning that human-authored work may be incorrectly identified as AI-generated. Additionally, AI-generated content often appears highly original and can bypass traditional plagiarism detection tools, further complicating evaluation .

Turnitin reinforces these limitations in its guidance, noting that its AI writing detection “may not always be accurate… and should not be used as the sole basis for adverse actions against a student” (Turnitin, 2024).

If you plan to use Turnitin's AI writing detection, consider the following:

  1. Be Transparent with Students
    • Include a syllabus or assignment-level statement that clearly communicates how the assignment supports the learning outcomes for the course and the expectations for generative AI use and non-use.
    • Disclose that AI detection tool that you will use in the evaluation of their assignment.
  2. Review AI Detection Reports with a Critical Lens
    • When reviewing an AI detection report, look beyond the percentage score. Focus on evaluating the parts of the assignment flagged as potentially using AI, checking for contextual relevance and consistency with the student's previous work.
  3. Prioritize Instructional Intervention
    • If AI detection suggests the use of unauthorized tools, faculty should prioritize a conversation with the student over an accusation. Consider deemphasizing the student's final product and focus on the student's learning process.
    • Consider asking questions like:
      • Can you walk me through how you developed this response?
      • How does this connect to our course materials or discussions?
      • What sources or ideas influenced your thinking?
      • Can you explain this section in your own words?

The use of AI detections should be part of a broader approach to evaluating student learning and academic integrity. Human judgement tends to be more reliable in the evaluation of student originality (Erol et al., 2025). If your expectation is that students complete their work without the use of AI tools, it is important to model that same approach in how their work is evaluated. Relying on your own disciplinary expertise and judgment ensures consistency, fairness, and alignment between your expectations and your practices.

Resources

  • Turninitin.com AI Detection FAQ
  • Turninitin.com AI Detection Disclosure Statement - Our AI writing assessment is designed to help educators identify text that might be prepared by a generative AI tool. Our AI writing assessment may not always be accurate (it may misidentify writing that is likely human generated as AI generated and likely AI generated as human generated) so it should not be used as the sole basis for adverse actions against a student. It takes further scrutiny and human judgment in conjunction with an organization's application of its specific academic policies to determine whether any academic misconduct has occurred.
  • Erol, G., Ergen, A., Erol, B. G., Ergen, Ş. K., Bora, T. S., Çölgeçen, A. D., Araz, B., Şahin, C., Bostancı, G., Kılıç, İ., Macit, Z. B., Sevgi, U. T., & Güngör, A. (2025). Can we trust academic AI detective? Accuracy and limitations of AI-output detectors. Acta Neurochirurgica, 167, Article 214. https://doi.org/10.1007/s00701-025-06622-4