 Ever since I was a little girl, I've loved maps. My blanket, when I was growing up, had a big map on it. My first memory I've ever had was a light-up globe next to my bed when I was little. I used to put maps on the walls everywhere instead of Jonathan Taylor, Thomas' posters that my friends all had. I would invite kids over to play and my favorite board game was called Geografects, where I would take cards out of the thing and ask them, what's the capital of Indonesia? And that's how the game went, and the kids would always go home before we got a chance to sleep over. But luckily, there's a place for me in the future. And here I am, I do geographic information systems. Now, GIS is a party, trust me. There's a ton of data. There's a ton of maps, hard drives, and coding. If you want to think of a mad computer scientist in the basement at 3 a.m., jacked up on Mountain Dew, listening to Techno in front of a Linux console and think that's cool, well, geographers do that too. We just don't talk about it as much. So today, I'm here to tell you all about it. And I'm here to tell you about a third type of distance that I'm developing. The first type of distance is very, very clear. It's a straight line distance. So we have two cities, for example. Right now, we're about 5,000 miles away from Honolulu. Sounds great, right? On a straight line. This is also called Euclidean distance, and it's named after Euclid, the ancient Greek, so you can tell how old it is. We also have a new kind of distance called travel time, or cost distance. And logisticians use this every single day. And this means that no matter how close two points are on a straight line, you still need to get there, and that's not usually a straight line. So you have to take the road that goes and travels. And we use this every day from when you order a pizza to when you take a flight to when you commute to work. So what I've been saying is that it's great that you have a road there. It's great that you have these distances, but I wanna know if anyone actually travels on these roads, if anyone actually uses these distances. So what I do is I take massive, massive data sets of migrants. For example, where I live in Boston, a lot of people migrate to San Francisco because of the tech jobs there. So I look at that. I take travel in Boston, where I live. A lot of people also take the bus to New York City or they fly to Florida. So I look at those magnitudes as well. And from this, emails and telephone calls, I'm developing what I call social distance. So how can we use social distance to make the world a better place? One example is when disease spreads, like take an STD in a developing country, it's not just gonna walk down the road this disease. What it's gonna do is gonna go through people. And these are very complex channels, but the good news is they can be mapped now that we have migrants and emails, et cetera. If we have a political uprising in a city like Cairo, if you wanna predict the next city that an uprising is gonna occur in, you're gonna wanna follow these hidden channels of people where they're talking to, where they're going to, because these are the real hidden roads on which things travel. And you can't see that on a map with Euclidean distance. If you wanna predict the next state to turn red or blue in the US political election, don't look at the boundaries. You're gonna wanna look at who's moving in there, who's moving out of there, the types of people that they're talking to. And the good news is that this digital information is all available to us today. So in the future, you might see this new type of social distance, and hopefully, it'll help us predict a better world. Thank you. Thank you so much. Thank you.