How AI and ML Help Filter Content
“One challenge with the internet is that it’s dynamic,” says Brett Baldwin, vice president of sales for Lightspeed. “AI and ML add context to the analysis so the algorithms can be changed on the fly.” A significant contribution AI brings that enhances content filtering is its ability to categorize websites and videos in Lightspeed’s database.
“We have hundreds of web crawlers automatically going out and millions of points of student data coming in,” says McMillan. “We know what the most popular websites are. AI helps us check and recheck all that content, categorize it, and make sure it’s accurate.”
AI and ML also help determine safety by analyzing and updating contextual information.
For example, a student might search for why a historical figure committed suicide, with “suicide” being a keyword the AI has flagged. Because it’s within an educational context, the content would not be blocked, but administrators would be alerted to see if this type of information should be filtered in the future. The ML then adjusts the algorithm to block or allow future content.
However, if the context is more concerning, such as a student who is creating a Google Doc that indicates a potential for self-harm, administrators will be alerted, and the right team at the school, such as counseling, will intervene.
Data Analysis Adds Value to Content Filtering
AI-powered content filtering can do much more than analyze websites for appropriateness or pick up on red flags requiring action. It can also provide meaningful data for decision-making.
Most schools aren’t using these administrative analysis tools yet, but McMillan hopes more will in the future.
“We’re not just building a data platform for our customers, we are building much more,” he says. “One key component is for customers to benchmark their results compared with other schools and districts. When data analysis tools are adopted, we’re seeing great results.”