 We have this sort of large scale project that involves examining the use of machine learning and education. So rather than diving into building tools, which of course we're also working on, we also wanted to do a holistic survey and analysis of how machine learning is used in education. And we identified education experts and we sat with them and we talked through the papers with them. We were like, this paper's goal is to, let's say, predict student dropout, right? And the goal there would be not just to predict it, but also to hopefully do something about it so that students are not dropping out of schools. And so that's an admirable goal, that's a goal that all of us can get behind. But that problem has to be concretely formulated into some machine learning problem. And then you have to find the right data set and all that. And then now you have this prediction that you're doing around which students are going to drop out and hopefully you get to kind of translate that into some real world intervention. So just taking this student dropout risk example, we had this interview with someone at a large state university that also struggles a lot with student dropout. One of the things that they mentioned was, okay, this paper is predicting which students are likely to drop out. What can we do with that, right? You tell me that some student is at high risk of dropping out. That's terrible. In some sense, the deed is kind of done. At that point, you tell a student, hey, you're at high risk of dropping out. That's not necessarily useful to the student, right? And you tell the schools the student is dropping out. It doesn't necessarily tell them what can you do about it. And so what he said was something subtle, but I really appreciate it. He said, instead of predicting which students are going to drop out, why don't you predict, for instance, which students are likely to miss class? They've already missed some number of classes and maybe they're about to miss a third class or something. We know that if students are missing several classes, that's a sign that they might be kind of at risk of dropping out. But missing classes is a more actionable thing, right? We can tell students, hey, you know, I've noticed that you've been missing a lot of classes. I'm worried that you're going to miss more classes. What can we do here to support you to attend class? The point here is more subtle. It's saying, you know, you have your target variable. That target variable could be dropout or it could be something actionable like missing classes. And the second thing is something that they can more easily do something about. The latter, not as clear.