The integration of AI in education raises complex questions about student data privacy. This panel discussion will convene experts from AI EdTech companies, student data privacy advocates, and the Future of Privacy Forum to explore the evolving landscape of data privacy in the age of AI.
Data minimization is a privacy principle that states that organizations should only collect and store personal data necessary to accomplish a specific purpose, and only for as long as needed. It’s a key principle for reducing the risk of data breaches and respecting individual privacy.
Join us on December 2 at 2pm ET as we dive deep into operational best practices for data collection, sharing and retention, with a particular focus on how to manage data effectively when working with EdTech Vendors and researchers.
Join us for a lively webinar where we will dive down quickly into exactly what this means for the Education Marketplace and ecosystem. Join experts from data interoperability, privacy think tanks and K12 legal counsel as we engage in a moderated discussion about the intersection of AI, Interoperability & Privacy in K12.
