With the Super Bowl having just occurred over the weekend, I'm sure that some of you were excited to sit down with some chips and dip turn on the TV and watch several uninterrupted hours of television. That's right, two groups of superhuman athletes battling across the grid iron at their peak performance levels for hours upon hours of action. Or if you've ever watched a football game on TV before Sunday, you were likely settling into your couch with the full awareness that according to the pro football network, you only saw between 15 and 20 minutes of actual football. The rest of the four hour Superbowl broadcast consists of the halftime show timeouts, breaks between plays, and of course, commercials. For many viewers. In fact, the commercials are the main event. Advertisers know that to reach viewers most effectively, they should debut brand new ads with celebrity appearances, gimmicks, or memorable hooks. But the job of drawing in viewers has become increasingly difficult for companies in the tech space, because they have to explain to their audience just what it is they're doing and how. Over the past few Super Bowls, one clear theme has emerged. Companies love to tell their audiences about how they're using data. A few years ago, the Super Bowl broadcast was packed with references to the cloud and big data. And now data's invoked in service of AI and other kinds of algorithms. It's clear that the public has developed an understanding of our new era of massive data availability, in part through commercials like these. But how do large datasets actually help the public?