But with a huge volume of posts popping up on these sites each day, it's difficult for even this combination of people and machines to keep up. AI still has a long way to go before it can reliably detect hate speech or violence online. Machine learning, the AI technique tech companies depend on to find unsavory content, figures out how to spot patterns in reams of data; it can identify offensive language, videos, or pictures in specific contexts. That's because these kinds of posts follow patterns on which AI can be trained. For example, if you give a machine-learning algorithm plenty of images of guns or written religious slurs, it can learn to spot those things in other images and text.

Artificial intelligence can identify people in pictures, find the next TV series you should binge watch on Netflix, and even drive a car. But on Friday, when a suspected terrorist in New Zealand streamed live video to Facebook of a mass murder, the technology was of no help. The gruesome broadcast went on for at least 17 minutes until New Zealand police reported it to the social network. Recordings of the video and related posts about it rocketed across social media while companies tried to keep up. Why can't AI, which is already used by major social networks to help moderate the status updates, photos, and videos users upload, simply be deployed in greater measures to remove such violence as swiftly as it appears? A big reason is that whether it's hateful written posts, pornography, or violent images or videos, artificial intelligence still isn't great at spotting objectional content online.