Students and teachers jointly set limits on how long AI-assisted learning records should remain identifiable after those records have served their educational purpose.
These references were saved as background for this fictional scenario.
Schools preserve sources, revisions, rejected suggestions, and explanations so they can assess how students question and correct artificial intelligence rather than merely scoring final answers. Students help design the rules governing those records, including who may view them, how they may be interpreted, and when identifying details should be removed. The resulting compromise preserves process-based assessment while reducing the chance that adolescent uncertainty becomes a permanent credential.
At midnight in a school archive in Daejeon, eighteen-year-old Seo Yuna reviews twelve years of abandoned hypotheses and corrected mistakes before their identifying details are removed under a policy her student council helped draft. She chooses three pages to keep in her private portfolio.
Removing identifying details from developmental records could complicate investigations of academic misconduct and weaken some long-term research. Wealthier families might also preserve richer private portfolios, creating a new advantage even under a privacy-focused system.