Faculty Checklist to Determine if Content is "AI-Proof"

1.

[Y/N] Does the assignment require students to reference highly specific, local or recent course materials?

AI tools rely on broad training data and generally do not have access to specific in-class discussions, recent local events, guest speaker presentations or unpublished course materials.

2.

[Y/N] Does the assessment focus on the process of learning rather than solely on a final product?

Assignments that require students to show their iterative work—such as submitting brainstorms, outlines, rough drafts, version histories and peer reviews over time—are much harder to automate with a single AI prompt.

3.

[Y/N] Does the prompt require the integration of personal experiences, reflections or unique perspectives?

While AI can generate generic text, it struggles to authentically write about human emotions, personal reflections or specific hands-on experiences a student had during a lab, clinical rotation or personal event.

4.

[Y/N] Does the task demand higher-order critical thinking and application rather than simple recall or summarization?

Assessments should push beyond basic knowledge retrieval toward synthesizing multiple complex viewpoints, evaluating methodologies or applying concepts to novel scenarios—tasks that AI tools currently struggle to do with deep analytical rigor.

5.

[Y/N] Are alternative, multimodal or interactive submission formats required?

Moving away from the standard five-paragraph essay to formats like oral presentations, video/audio projects, infographics, in-class debates or oral defenses makes it significantly more difficult for a student to submit purely AI-generated work.