Simon Willison notes that artificial intelligence forces computer science educators to rethink how they teach and assess students, yet effective methods remain unclear after only a few years of adoption. The evaluation cycle is measured in multiple years because any new educational mechanism introduced today will not yield reliable results until the current cohort graduates in three to six years time. Students effectively become guinea pigs for untested ways of learning and teaching while institutions struggle to adapt to these rapid changes.
This delay creates a significant gap between technological reality and academic validation, leaving universities to operate with incomplete data on student outcomes. The lack of immediate feedback prevents the rapid iteration usually seen in software development, making it difficult to determine which pedagogical approaches actually work in practice.
* Evaluation results are delayed by three to six years
* Students act as test subjects for unproven teaching methods
* Institutions lack real-time data on AI’s impact on learning
