Artificial intelligence has embedded itself throughout campus operations, from student-facing chatbots and adaptive learning platforms to predictive analytics and automated scheduling tools. This webinar examines the legal and governance challenges created when a statute written in 1974 must govern technologies its authors never imagined.
Key topics include:
- When AI-generated outputs, including predictive risk scores, personalized learning pathways, and chatbot interaction logs, constitute FERPA-protected education records
- Why institutional responsibility extends to third-party AI vendors and cloud providers that hold student data
- The transparency paradox: students’ right to inspect their records versus the “black box” nature of deep learning models
- Tensions between AI’s need for large, granular datasets and FERPA’s data minimization mandate
- Privacy-by-design approaches that build protections into AI systems from inception
- What custom vendor contracts must address beyond standard Terms of Service, including data ownership, prohibitions on mining student data for product development, and destruction protocols
- Handling student requests to inspect and amend AI-generated records
- Preparing for emerging technologies, including Large Language Models and biometric analysis systems
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