Higher ed / Apr 15, 2026 / 5 min
Universities Need Assessment Design, Not AI Detection
AI detection tools cannot carry the weight of academic integrity. Institutions need assessments that make thinking visible and AI use explicit.
Higher education often reaches for detection when generative AI disrupts assessment. That response is understandable, but brittle. Detection is uncertain, adversarial, and often disconnected from what faculty actually want students to learn.
The better path is assessment design. Ask students to show process, defend choices, connect work to local context, critique AI output, reflect on revisions, and demonstrate understanding in formats harder to outsource fully.
This does not mean every course should allow unrestricted AI. Some learning goals require unaided practice. Others benefit from supervised AI use. The key is clarity.
Institutions should support faculty with policy templates, assignment models, discipline-specific examples, and review forums where practices improve over time.
Convina's view: AI forces universities to define evidence of learning more precisely. Detection may remain a tool, but design is the strategy.