How technology helps prioritize review


JAN 19, 2022

Whether potentially violating content is reported by people or detected by Meta’s technology, automation helps us quickly route the content to reviewers who have the right subject matter and language expertise.

We then use technology to rank and prioritize content so our review teams can focus on the most important cases first. This includes content with the potential for offline harm, such as posts related to terrorism and suicide, and viral content that violates our policies and has the potential to reach a large audience.

To make sure review teams spend more time focused on the right decisions, we’re always making improvements to our technology and processes.

How Meta prioritizes content for review

Why review teams are important for content enforcement

To reduce harm in our community, our technology and human review teams are always working together. Here are some ways reviewers, in tandem with technology, help strengthen our entire content enforcement system.

Training our technology

When reviewers make a decision about a piece of content, they’re simultaneously training and refining our technology to help it identify other pieces of similar content over time. This human-technology feedback loop is vital to keeping our systems current.

Improving our artificial intelligence algorithms

When reviewing violating content, review teams manually label the policy guiding their decision, which means they mark the policy that the content, account or behavior violates. This important labeling data helps us improve the quality of our artificial intelligence algorithms that proactively search for harmful content.

Making difficult decisions

Our technology does well in 2 areas in particular: detecting repeated violations and identifying obviously graphic or extreme content. But when there’s a high degree of ambiguity, complexity or nuance in whether our policies apply to a piece of content, reviewers tend to make better decisions than technology.