# Unverifiable student work

Teachers can't tell who learned and who prompted

Problem 0011 · Education · Theme: Measurement · What it would take: A side project · Scope: Global · Editorial grade: Critical · Framed 21 September 2026 · Updated 22 September 2026 · Framed from public reporting

Most institutions are writing or planning a policy about AI; few have changed what they actually measure. The essay, the problem set and the report were proxies for thinking that worked only while producing them was expensive. That assumption is gone. Detection tools are unreliable enough to risk accusing the wrong students, and much of what is graded no longer shows reliably what a student understands.

## Who lives with it

Teachers and lecturers redesigning assessment alone · students wrongly suspected · institutions whose credentials depend on the answer

## Why now

A UNESCO survey found 19% of higher education institutions had formal AI guidance with a further 42% developing it, while more than half reported uncertainty about how to apply AI pedagogically and one in four had already encountered ethical problems including authorship disputes.

## Why it matters

The question has moved from catching misuse to evidencing learning, and nothing is built for the new question. Making a student's reasoning visible, cheaply and without treating them as a suspect, solves what detection never could.

## From public reporting

- [Two-thirds of higher education institutions have or are developing guidance on AI use](https://www.unesco.org/en/articles/unesco-survey-two-thirds-higher-education-institutions-have-or-are-developing-guidance-ai-use), UNESCO, 2 September 2025

## Cite it

“Teachers can't tell who learned and who prompted.” Ainna Problem Radar, problem 0011, 21 September 2026. https://ainna.ai/problems/teachers-cant-tell-who-learned-and-who-prompted

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