Academic Integrity & Assessment

Assessment is how education certifies what a student has learned, and generative AI has shaken its foundation. When a chatbot can write a passable essay in seconds, the take-home written assignment — a century-old default — no longer reliably measures a student's own work. Schools and universities have scrambled to respond, and the response has divided into two very different approaches.

The first is detection: software that tries to tell whether text was written by AI. The second, and increasingly favored, is redesign: rethinking assessment so that it is resilient to AI in the first place — authentic tasks, supervised or oral components, and assessment of the process rather than only the final product. The honest truth of 2026 is that detection is on shaky ground, while assessment redesign is the harder but more durable path.

On the detection side, Turnitin is the dominant academic-integrity platform and GPTZero and Copyleaks are widely used AI-writing detectors — but all three sit in a genuinely contested category. On the redesign side, Packback builds AI-resilient assessment and AI-assisted grading around curiosity and credibility, and Cadmus provides an authentic-writing environment plus AI-supported oral assessment. Gradescope speeds grading of student work at scale. The credible institutional answer increasingly leans toward redesign over detection.

AI is forcing a genuine rethink of how learning is measured, and the honest story here is unusually important. AI-writing detectors are unreliable: independent testing shows meaningful false-positive rates, they disproportionately misflag non-native English writers, and their accuracy collapses on lightly edited text — in 2026 a major university publicly disabled AI detection over these concerns. Treating a detector's output as proof of cheating is dangerous and has harmed innocent students. The more durable response is redesigning assessment to be authentic and AI-resilient, which shifts educators' work from policing toward better task design. The role of human judgment — in grading, in interpreting a detector's signal, and in designing assessment — becomes more central, not less.