Example Concept: AI in student assessments must be designed to avoid bias by using diverse training data and regularly auditing algorithms for fairness. Transparency is key, meaning students and educators should have access to understand how AI makes decisions. Additionally, data privacy must be safeguarded by ensuring that student information is securely stored and only used for intended educational purposes.