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In the context of academic integrity, the risks of false positives are significant (Klee 2023; Fowler 2023). Unreliable AI detection not only fails to improve academic integrity but may deepen existing inequalities. Non-native English speakers are flagged by AI detection tools at a disproportionate rate (Myers 2023). Other tools like Grammarly with legitimate academic applications, particularly for writers with dyslexia and other learning disabilities, also increase the likelihood of being flagged by AI detectors (Shapiro 2018; Steere 2023).
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For all of the reasons given above, university ITS does not currently license, support, or recommend any kind of AI detector. Barring a significant technological breakthrough on this front, these tools are simply not reliable enough to be incorporated into our university policies and procedures. |
What to Do?
All this leaves instructors in a challenging position where the best recommendations being put forward are to redesign their assessments. Redesigning assessments is difficult and time consuming, and the new assessment methods often require more time to grade. Just as AI tools are beginning to make the process of writing faster and easier for everybody, it feels unfair that teachers of writing are forced to spend more of their own precious time on addressing the downsides and potential misuse of these tools.
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We are also unable to recommend any alternative technological solution. None of the AI detection tools currently available online are accurate enough to provide credible evidence in academic integrity investigations. The risk of misleading results harming students who are acting in good faith is too great. ITS is committed to thorough and transparent vetting of any new tools that emerge in the future. If a reliable tool for AI detection becomes available, ITS will evaluate the tool and consider recommending it to the Syracuse University academic community.
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Other AI Policy and Planning Resources from Syracuse University
Center for Teaching and Learning Excellence (CTLE)
Center for Learning And Student Success (CLASS)
Syracuse University Libraries Artificial Intelligence Research Guide
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Bibliography
“Authentic Assessment.” n.d. Center for Innovative Teaching and Learning. Accessed February 27, 2024. https://citl.indiana.edu/teaching-resources/assessing-student-learning/authentic-assessment/index.html.
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