Using AI in Your Teaching? What Should You Tell Students?

Image credit: Photo by Sora Shimazaki

Faculty conversations about AI often focus on students. However, what if faculty use AI to revise assignment instructions, prepare lecture slides, or edit feedback? What should you tell your students? 

At NYU, the Office of the Provost has shared some initial recommendations around faculty disclosure of AI use. More specific guidance about the form these disclosures should take is likely forthcoming. In the meantime, a useful starting point is to describe what AI contributed and how you reviewed its output (Note: The sample language below is intended to be illustrative). 

Disclosing AI Use in Course Materials

It is important to be clear about how AI was used to develop course materials. Did AI help revise the wording of instructions you wrote? Suggest examples for a presentation? Draft practice questions that you then checked and revised?

For example, your disclosure might read:

I used generative AI to help edit the assignment instructions for clarity. I reviewed and approved the final instructions.

If AI contributed to the development of a resource, your disclosure should be more specific:

I used generative AI to draft examples for these lecture slides. I checked their accuracy, revised them, and selected the examples included in the slides.

Disclosing AI Use in Feedback and Grading

NYU faculty also need to communicate to students how AI contributed to feedback on or evaluation of student work. For example, if AI helped edit feedback you had already written, the note could say:

I used generative AI to copyedit my written feedback for clarity. I reviewed the final comments and made the grading decision.

If AI was used to check the application of rubric criteria, a note might say:

I used generative AI to help check the consistency of my application of the rubric criteria. I reviewed its suggestions and made the final grading decision.

It is important to use language that accurately reflects your process. Since GenAI tools hallucinate, reviewing AI output does not, by itself, establish that an evaluation is fair or accurate. Additionally, be sure to review institutional policies/guidance before using an AI to assess any student work (at NYU, see Recommendations for Faculty Use of AI).

Why Explain Your AI Use?

Explaining our use of AI gives students a clearer picture of how course materials were developed, how feedback was prepared, and where our judgment shaped them. Moreover, this practice reinforces academic transparency and normalizes open discussion around AI use. The examples above are starting points for the discussion. 

For help thinking through AI disclosure in your teaching, contact the Learning and Teaching Nexus at nexus@nyu.edu, request a consultation, or explore our workshops and Zoomside Chats. Visit NYU’s Frequently Asked Questions About Teaching and AI, Teaching with Generative AI, and the Nexus AI guides (NYU login required) for more information. 

This blog was developed with AI assistance. The author reviewed and revised the content and made all final editorial decisions.