1 00:00:00,620 --> 00:00:02,395 When we think about mapping cities, 2 00:00:02,395 --> 00:00:05,200 we tend to think about roads and streets and buildings, 3 00:00:05,200 --> 00:00:08,000 and the settlement narrative that led to their creation, 4 00:00:08,000 --> 00:00:10,984 or you might think about the bold vision of an urban designer, 5 00:00:10,984 --> 00:00:13,487 but there's other ways to think about mapping cities 6 00:00:13,487 --> 00:00:15,653 and how they got to be made. 7 00:00:15,653 --> 00:00:17,746 Today, I want to show you a new kind of map. 8 00:00:17,746 --> 00:00:19,242 This is not a geographic map. 9 00:00:19,242 --> 00:00:22,373 This is a map of the relationships between people in my hometown 10 00:00:22,373 --> 00:00:23,713 of Baltimore, Maryland, 11 00:00:23,713 --> 00:00:28,130 and what you can see here is that each dot represents a person, 12 00:00:28,130 --> 00:00:31,424 each line represents a relationship between those people, 13 00:00:31,424 --> 00:00:34,870 and each color represents a community within the network. 14 00:00:34,870 --> 00:00:39,732 Now, I'm here on the green side, down on the far right where the geeks are, 15 00:00:39,732 --> 00:00:43,580 and TEDx also is down on the far right. (Laughter) 16 00:00:43,580 --> 00:00:46,157 Now, on the other side of the network, 17 00:00:46,157 --> 00:00:49,117 you tend to have primarily African-American and Latino folks 18 00:00:49,117 --> 00:00:52,707 who are really concerned about somewhat different things than the geeks are, 19 00:00:52,707 --> 00:00:54,148 but just to give some sense, 20 00:00:54,148 --> 00:00:56,554 the green part of the network we call Smalltimore, 21 00:00:56,554 --> 00:00:58,099 for those of us that inhabit it, 22 00:00:58,099 --> 00:01:01,014 because it seems as though we're living in a very small town. 23 00:01:01,014 --> 00:01:03,048 We see the same people over and over again, 24 00:01:03,048 --> 00:01:05,219 but that's because we're not really exploring 25 00:01:05,219 --> 00:01:08,081 the full depth and breadth of the city. 26 00:01:08,081 --> 00:01:09,833 On the other end of the network, 27 00:01:09,833 --> 00:01:12,770 you have folks who are interested in things like hip-hop music 28 00:01:12,770 --> 00:01:16,574 and they even identify with living in the DC/Maryland/Virginia area 29 00:01:16,574 --> 00:01:20,990 over, say, the Baltimore city designation proper. 30 00:01:20,990 --> 00:01:23,090 But in the middle, you see that there's 31 00:01:23,090 --> 00:01:25,573 something that connects the two communities together, 32 00:01:25,573 --> 00:01:26,452 and that's sports. 33 00:01:26,452 --> 00:01:29,540 We have the Baltimore Orioles, the Baltimore Ravens football team, 34 00:01:29,540 --> 00:01:30,986 Michael Phelps, the Olympian. 35 00:01:30,986 --> 00:01:33,824 Under Armour, you may have heard of, is a Baltimore company, 36 00:01:33,824 --> 00:01:36,257 and that community of sports acts as the only bridge 37 00:01:36,257 --> 00:01:38,528 between these two ends of the network. 38 00:01:38,528 --> 00:01:40,423 Let's take a look at San Francisco. 39 00:01:40,423 --> 00:01:43,609 You see something a little bit different happening in San Francisco. 40 00:01:43,609 --> 00:01:48,002 On the one hand, you do have the media, politics and news lobe 41 00:01:48,002 --> 00:01:50,537 that tends to exist in Baltimore and other cities, 42 00:01:50,537 --> 00:01:52,892 but you also have this very predominant group 43 00:01:52,892 --> 00:01:57,285 of geeks and techies that are sort of taking over the top half of the network, 44 00:01:57,285 --> 00:01:59,787 and there's even a group that's so distinct and clear 45 00:01:59,787 --> 00:02:02,137 that we can identify it as Twitter employees, 46 00:02:02,137 --> 00:02:05,504 next to the geeks, in between the gamers and the geeks, 47 00:02:05,504 --> 00:02:08,445 at the opposite end of the hip-hop spectrum. 48 00:02:08,445 --> 00:02:10,162 So you can see, though, 49 00:02:10,162 --> 00:02:12,843 that the tensions that we've heard about in San Francisco 50 00:02:12,843 --> 00:02:15,764 in terms of people being concerned about gentrification 51 00:02:15,764 --> 00:02:18,523 and all the new tech companies that are bringing new wealth 52 00:02:18,523 --> 00:02:20,620 and settlement into the city are real, 53 00:02:20,620 --> 00:02:22,849 and you can actually see that documented here. 54 00:02:22,849 --> 00:02:24,869 You can see the LGBT community 55 00:02:24,869 --> 00:02:28,165 is not really getting along with the geek community that well, 56 00:02:28,165 --> 00:02:30,297 the arts community, the music community. 57 00:02:30,297 --> 00:02:32,070 And so it leads to things like this. 58 00:02:32,070 --> 00:02:33,043 ["Evict Twitter"] 59 00:02:33,043 --> 00:02:34,867 Somebody sent me this photo a few weeks ago, 60 00:02:34,867 --> 00:02:37,774 and it shows what is happening on the ground in San Francisco, 61 00:02:37,774 --> 00:02:40,158 and I think you can actually try to understand that 62 00:02:40,158 --> 00:02:41,860 through looking at a map like this. 63 00:02:41,860 --> 00:02:43,620 Let's take a look at Rio de Janeiro. 64 00:02:43,620 --> 00:02:46,074 I spent the last few weeks gathering data about Rio, 65 00:02:46,074 --> 00:02:48,881 and one of the things that stood out to me about this city 66 00:02:48,881 --> 00:02:51,003 is that everything's really kind of mixed up. 67 00:02:51,003 --> 00:02:55,107 It's a very heterogenous city in a way that Baltimore or San Francisco is not. 68 00:02:55,107 --> 00:02:57,562 You still have the lobe of people involved 69 00:02:57,562 --> 00:02:59,946 with government, newspapers, politics, columnists. 70 00:02:59,946 --> 00:03:03,350 TEDxRio is down in the lower right, right next to bloggers and writers. 71 00:03:03,350 --> 00:03:06,059 But then you also have this tremendous diversity of people 72 00:03:06,059 --> 00:03:08,333 that are interested in different kinds of music. 73 00:03:08,333 --> 00:03:10,537 Even Justin Bieber fans are represented here. 74 00:03:10,537 --> 00:03:13,429 Other boy bands, country singers, 75 00:03:13,429 --> 00:03:16,337 gospel music, funk and rap and stand-up comedy, 76 00:03:16,337 --> 00:03:19,376 and there's even a whole section around drugs and jokes. 77 00:03:19,376 --> 00:03:20,862 How cool is that? 78 00:03:20,862 --> 00:03:23,996 And then the Flamengo football team is also represented here. 79 00:03:23,996 --> 00:03:26,156 So you have that same kind of spread 80 00:03:26,156 --> 00:03:28,871 of sports and civics and the arts and music, 81 00:03:28,871 --> 00:03:31,032 but it's represented in a very different way, 82 00:03:31,032 --> 00:03:34,352 and I think that maybe fits with our understanding of Rio 83 00:03:34,352 --> 00:03:38,366 as being a very multicultural, musically diverse city. 84 00:03:38,366 --> 00:03:41,984 So we have all this data. 85 00:03:41,984 --> 00:03:45,102 It's an incredibly rich set of data that we have about cities now, 86 00:03:45,102 --> 00:03:48,348 maybe even richer than any data set that we've ever had before. 87 00:03:48,348 --> 00:03:50,272 So what can we do with it? 88 00:03:50,272 --> 00:03:53,142 Well, I think the first thing that we can try to understand 89 00:03:53,142 --> 00:03:55,480 is that segregation is a social construct. 90 00:03:55,480 --> 00:03:58,824 It's something that we choose to do, and we could choose not to do it, 91 00:03:58,824 --> 00:04:00,756 and if you kind of think about it, 92 00:04:00,756 --> 00:04:04,167 what we're doing with this data is aiming a space telescope at a city 93 00:04:04,167 --> 00:04:07,199 and looking at it as if was a giant high school cafeteria, 94 00:04:07,199 --> 00:04:10,937 and seeing how everybody arranged themselves in a seating chart. 95 00:04:10,937 --> 00:04:14,250 Well maybe it's time to shake up the seating chart a little bit. 96 00:04:14,250 --> 00:04:16,790 The other thing that we start to realize 97 00:04:16,790 --> 00:04:19,428 is that race is a really poor proxy for diversity. 98 00:04:19,428 --> 00:04:22,365 We've got people represented from all different types of races 99 00:04:22,365 --> 00:04:24,691 across the entire map here -- 100 00:04:24,691 --> 00:04:27,067 only looking at race 101 00:04:27,067 --> 00:04:29,785 doesn't really contribute to our development of diversity. 102 00:04:29,785 --> 00:04:31,524 So if we're trying to use diversity 103 00:04:31,524 --> 00:04:34,605 as a way to tackle some of our more intractable problems, 104 00:04:34,605 --> 00:04:37,899 we need to start to think about diversity in a new way. 105 00:04:37,899 --> 00:04:41,426 And lastly, we have the ability to create 106 00:04:41,426 --> 00:04:44,520 interventions to start to reshape our cities in a new way, 107 00:04:44,520 --> 00:04:47,120 and I believe that if we have that capability, 108 00:04:47,120 --> 00:04:50,185 we may even bear some responsibility to do so. 109 00:04:50,185 --> 00:04:51,950 So what is a city? 110 00:04:51,950 --> 00:04:54,156 I think some might say that it is 111 00:04:54,156 --> 00:04:57,316 a geographical area or a collection of streets and buildings, 112 00:04:57,316 --> 00:05:00,068 but I believe that a city is the sum of the relationships 113 00:05:00,068 --> 00:05:01,629 of the people that live there, 114 00:05:01,629 --> 00:05:07,680 and I believe that if we can start to document those relationships in a real way 115 00:05:07,680 --> 00:05:09,413 then maybe we have a real shot 116 00:05:09,413 --> 00:05:12,088 at creating those kinds of cities that we'd like to have. 117 00:05:12,088 --> 00:05:13,445 Thank you. 118 00:05:13,445 --> 00:05:15,749 (Applause)