Presented by
- Michael Webb, PhD
- Daniel McCartney
- Sara Drake
- Nicholas Michael
Session Description
Generative AI did not break academic integrity. It exposed the illusion that policy and detection alone could protect it.
Across higher education, institutions are publishing AI policies while faculty are left navigating ambiguity, inconsistent enforcement, and tools that promise certainty but rarely deliver it. The result is anxiety, uneven standards, and a compliance model that does not scale.
This session presents a structural alternative: Design Over Detection.
Authentic assessment is not merely a pedagogical philosophy. It is the operational layer that makes AI policy functional. By redesigning assignments to make student thinking visible, process documented, and skills demonstrable within Canvas, institutions can shift from reactive detection to built in accountability. Instead of policing AI after submission, design embeds transparency directly into the student workflow.
