K–12 educators and administrators are tasked with building safe and effective digital learning environments, and this responsibility includes shielding students from inappropriate content online.
Traditionally, this has involved monitoring and filtering web access by keeping lists of appropriate and inappropriate websites. But the Internet is constantly changing. The dynamic nature of the web makes traditional URL-based filtering—the process of categorizing entire web pages by their domains—a largely ineffective method of controlling the kinds of content that students access.
Fortunately, a new method has emerged that uses artificial intelligence to analyze the actual content on web pages in real time, allowing students to see only material that educators deem safe and productive. Content-based filtering marks a different approach to keeping students safe online—one that’s proving to be both more accurate and easier for educators to manage.