1 00:00:01,875 --> 00:00:04,601 The world today has many problems. 2 00:00:04,625 --> 00:00:10,143 And they're all very complicated and interconnected and difficult. 3 00:00:10,167 --> 00:00:12,601 But there is something we can do. 4 00:00:12,625 --> 00:00:13,893 I believe 5 00:00:13,917 --> 00:00:18,684 that girls' education is the closest thing we have to a silver bullet 6 00:00:18,708 --> 00:00:23,101 to help solve some of the world's most difficult problems. 7 00:00:23,125 --> 00:00:25,226 But you don't have to take my word for it. 8 00:00:25,250 --> 00:00:26,934 The World Bank says 9 00:00:26,958 --> 00:00:30,226 that girls' education is one of the best investments 10 00:00:30,250 --> 00:00:32,268 that a country can make. 11 00:00:32,292 --> 00:00:34,393 It helps to positively impact 12 00:00:34,417 --> 00:00:37,976 nine of the 17 Sustainable Development Goals. 13 00:00:38,000 --> 00:00:42,434 Everything from health, nutrition, employment -- 14 00:00:42,458 --> 00:00:46,417 all of these are positively impacted when girls are educated. 15 00:00:47,667 --> 00:00:52,809 Additionally, climate scientists have recently rated girls' education 16 00:00:52,833 --> 00:00:58,559 at number six out of 80 actions to reverse global warming. 17 00:00:58,583 --> 00:01:03,625 At number six, it's rated higher than solar panels and electric cars. 18 00:01:05,542 --> 00:01:08,393 And that's because when girls are educated, 19 00:01:08,417 --> 00:01:10,226 they have smaller families, 20 00:01:10,250 --> 00:01:13,643 and the resulting reduction in population 21 00:01:13,667 --> 00:01:17,000 reduces carbon emissions significantly. 22 00:01:18,500 --> 00:01:22,726 But more than that, you know, it's a problem we have to solve once. 23 00:01:22,750 --> 00:01:27,059 Because an educated mother is more than twice as likely 24 00:01:27,083 --> 00:01:29,101 to educate her children. 25 00:01:29,125 --> 00:01:31,143 Which means that by doing it once, 26 00:01:31,167 --> 00:01:35,226 we can close the gender and literacy gap forever. 27 00:01:35,250 --> 00:01:36,684 I work in India, 28 00:01:36,708 --> 00:01:39,559 which has made incredible progress 29 00:01:39,583 --> 00:01:42,809 in bringing elementary education for all. 30 00:01:42,833 --> 00:01:46,851 However, we still have four million out-of-school girls, 31 00:01:46,875 --> 00:01:48,750 one of the highest in the world. 32 00:01:49,917 --> 00:01:53,601 And girls are out of school because of, obviously poverty, 33 00:01:53,625 --> 00:01:55,893 social, cultural factors. 34 00:01:55,917 --> 00:01:59,042 But there's also this underlying factor of mindset. 35 00:02:00,250 --> 00:02:03,601 I have met a girl whose name was Naraaz Nath. 36 00:02:03,625 --> 00:02:05,809 Naaraaz means angry. 37 00:02:05,833 --> 00:02:08,309 And when I asked her, "Why is your name 'angry'?" 38 00:02:08,333 --> 00:02:12,750 she said, "Because everybody was so angry when a girl was born." 39 00:02:14,125 --> 00:02:16,601 Another girl called Antim Bala, 40 00:02:16,625 --> 00:02:18,893 which means the last girl. 41 00:02:18,917 --> 00:02:22,208 Because everybody hoped that would be the last girl to be born. 42 00:02:23,625 --> 00:02:25,333 A girl called Aachuki. 43 00:02:26,292 --> 00:02:28,351 It means somebody who has arrived. 44 00:02:28,375 --> 00:02:31,643 Not wanted, but arrived. 45 00:02:31,667 --> 00:02:33,809 And it is this mindset 46 00:02:33,833 --> 00:02:37,434 that keeps girls from school or completing their education. 47 00:02:37,458 --> 00:02:40,143 It's this belief that a goat is an asset 48 00:02:40,167 --> 00:02:41,875 and a girl is a liability. 49 00:02:44,667 --> 00:02:48,143 My organization Educate Girls works to change this. 50 00:02:48,167 --> 00:02:51,059 And we work in some of the most difficult, rural, 51 00:02:51,083 --> 00:02:52,917 remote and tribal villages. 52 00:02:54,000 --> 00:02:55,518 And how do we do it? 53 00:02:55,542 --> 00:02:57,851 We first and foremost find 54 00:02:57,875 --> 00:03:02,059 young, passionate, educated youth from the same villages. 55 00:03:02,083 --> 00:03:04,434 Both men and women. 56 00:03:04,458 --> 00:03:05,851 And we call them Team Balika, 57 00:03:05,875 --> 00:03:07,476 balika just means the girl child, 58 00:03:07,500 --> 00:03:10,417 so this is a team that we are creating for the girl child. 59 00:03:11,417 --> 00:03:14,309 And so once we recruit our community volunteers, 60 00:03:14,333 --> 00:03:17,625 we train them, we mentor them, we hand-hold them. 61 00:03:18,458 --> 00:03:20,018 That's when our work starts. 62 00:03:20,042 --> 00:03:24,393 And the first piece we do is about identifying every single girl 63 00:03:24,417 --> 00:03:26,684 who's not going to school. 64 00:03:26,708 --> 00:03:29,934 But the way we do it is a little different and high-tech, 65 00:03:29,958 --> 00:03:32,268 at least in my view. 66 00:03:32,292 --> 00:03:35,018 Each of our frontline staff have a smartphone. 67 00:03:35,042 --> 00:03:37,726 It has its own Educate Girls app. 68 00:03:37,750 --> 00:03:40,934 And this app has everything that our team needs. 69 00:03:40,958 --> 00:03:46,434 It has digital maps of where they're going to be conducting the survey, 70 00:03:46,458 --> 00:03:48,768 it has the survey in it, all the questions, 71 00:03:48,792 --> 00:03:51,643 little guides on how best to conduct the survey, 72 00:03:51,667 --> 00:03:55,792 so that the data that comes to us is in real time and is of good quality. 73 00:03:56,833 --> 00:03:58,101 So armed with this, 74 00:03:58,125 --> 00:04:01,518 our teams and our volunteers go door-to-door 75 00:04:01,542 --> 00:04:05,309 to every single household to find every single girl 76 00:04:05,333 --> 00:04:08,226 who may either we never enrolled or dropped out of school. 77 00:04:08,250 --> 00:04:11,518 And because we have this data and technology piece, 78 00:04:11,542 --> 00:04:15,476 very quickly we can figure out who the girls are and where they are. 79 00:04:15,500 --> 00:04:17,934 Because each of our villages are geotagged, 80 00:04:17,958 --> 00:04:20,351 and we can actually build that information out 81 00:04:20,375 --> 00:04:21,875 very, very quickly. 82 00:04:22,542 --> 00:04:25,143 And so once we know where the girls are, 83 00:04:25,167 --> 00:04:28,893 we actually start the process of bringing them back into school. 84 00:04:28,917 --> 00:04:31,809 And that actually is just our community mobilization process, 85 00:04:31,833 --> 00:04:35,268 it starts with village meetings, neighborhood meetings, 86 00:04:35,292 --> 00:04:39,226 and as you see, individual counseling of parents and families, 87 00:04:39,250 --> 00:04:41,893 to be able to bring the girls back into school. 88 00:04:41,917 --> 00:04:46,542 And this can take anything from a few weeks to a few months. 89 00:04:47,625 --> 00:04:50,059 And once we bring the girls into the school system, 90 00:04:50,083 --> 00:04:51,518 we also work with the schools 91 00:04:51,542 --> 00:04:55,434 to make sure that schools have all the basic infrastructure 92 00:04:55,458 --> 00:04:57,363 so that the girls will be able to stay. 93 00:04:57,387 --> 00:05:00,184 And this would include a separate toilet for girls, 94 00:05:00,208 --> 00:05:01,809 drinking water, 95 00:05:01,833 --> 00:05:04,851 things that will help them to be retained. 96 00:05:04,875 --> 00:05:08,643 But all of this would be useless if our children weren't learning. 97 00:05:08,667 --> 00:05:11,559 So we actually run a learning program. 98 00:05:11,583 --> 00:05:13,684 And this is a supplementary learning program, 99 00:05:13,708 --> 00:05:16,018 and it's very, very important, 100 00:05:16,042 --> 00:05:19,893 because most of our children are first-generation learners. 101 00:05:19,917 --> 00:05:22,809 That means there's nobody at home to help them with homework, 102 00:05:22,833 --> 00:05:25,059 there's nobody who can support their education. 103 00:05:25,083 --> 00:05:26,768 Their parents can't read and write. 104 00:05:26,792 --> 00:05:28,434 So it's really, really key 105 00:05:28,458 --> 00:05:32,601 that we do the support of the learning in the classrooms. 106 00:05:32,625 --> 00:05:34,518 So this is essentially our model, 107 00:05:34,542 --> 00:05:36,851 in terms of finding, bringing the girls in, 108 00:05:36,875 --> 00:05:39,476 making sure that they're staying and learning. 109 00:05:39,500 --> 00:05:42,101 And we know that our model works. 110 00:05:42,125 --> 00:05:44,018 And we know this because 111 00:05:44,042 --> 00:05:47,184 a most recent randomized control evaluation 112 00:05:47,208 --> 00:05:48,917 confirms its efficacy. 113 00:05:50,792 --> 00:05:54,518 Our evaluator found that over a three-year period 114 00:05:54,542 --> 00:05:59,684 Educate Girls was able to bring back 92 percent of all out-of-school girls 115 00:05:59,708 --> 00:06:01,434 back into school. 116 00:06:01,458 --> 00:06:07,976 (Applause) 117 00:06:08,000 --> 00:06:09,434 And in terms of learning, 118 00:06:09,458 --> 00:06:12,101 our children's learning went up significantly 119 00:06:12,125 --> 00:06:14,226 as compared to control schools. 120 00:06:14,250 --> 00:06:18,143 So much so, that it was like an additional year of schooling 121 00:06:18,167 --> 00:06:19,976 for the average student. 122 00:06:20,000 --> 00:06:21,393 And that's enormous, 123 00:06:21,417 --> 00:06:24,768 when you think about a tribal child who's entering the school system 124 00:06:24,792 --> 00:06:26,167 for the first time. 125 00:06:27,042 --> 00:06:29,434 So here we have a model that works; 126 00:06:29,458 --> 00:06:31,434 we know it's scalable, 127 00:06:31,458 --> 00:06:35,101 because we are already functioning at 13,000 villages. 128 00:06:35,125 --> 00:06:36,434 We know it's smart, 129 00:06:36,458 --> 00:06:39,393 because of the use of data and technology. 130 00:06:39,417 --> 00:06:42,184 We know that it's sustainable and systemic, 131 00:06:42,208 --> 00:06:45,184 because we work in partnership with the community, 132 00:06:45,208 --> 00:06:47,393 it's actually led by the community. 133 00:06:47,417 --> 00:06:49,643 And we work in partnership with the government, 134 00:06:49,667 --> 00:06:52,375 so there's no creation of a parallel delivery system. 135 00:06:53,417 --> 00:06:56,643 And so because we have this innovative partnership 136 00:06:56,667 --> 00:07:00,559 with the community, the government, this smart model, 137 00:07:00,583 --> 00:07:03,875 we have this big, audacious dream today. 138 00:07:05,042 --> 00:07:08,851 And that is to solve a full 40 percent of the problem 139 00:07:08,875 --> 00:07:12,125 of out-of-school girls in India in the next five years. 140 00:07:12,958 --> 00:07:19,351 (Applause) 141 00:07:19,375 --> 00:07:21,976 And you're thinking, that's a little ... 142 00:07:22,000 --> 00:07:25,018 You know, how am I even thinking about doing that, 143 00:07:25,042 --> 00:07:28,875 because India is not a small place, it's a huge country. 144 00:07:30,042 --> 00:07:32,559 It's a country of over a billion people. 145 00:07:32,583 --> 00:07:36,518 We have 650,000 villages. 146 00:07:36,542 --> 00:07:38,184 How is it that I'm standing here, 147 00:07:38,208 --> 00:07:40,184 saying that one small organization 148 00:07:40,208 --> 00:07:43,417 is going to solve a full 40 percent of the problem? 149 00:07:44,125 --> 00:07:46,726 And that's because we have a key insight. 150 00:07:46,750 --> 00:07:48,018 And that is, 151 00:07:48,042 --> 00:07:52,518 because of our entire approach, with data and with technology, 152 00:07:52,542 --> 00:07:55,226 that five percent of villages in India 153 00:07:55,250 --> 00:07:58,268 have 40 percent of the out-of-school girls. 154 00:07:58,292 --> 00:08:01,059 And this is a big, big piece of the puzzle. 155 00:08:01,083 --> 00:08:04,268 Which means, I don't have to work across the entire country. 156 00:08:04,292 --> 00:08:07,434 I have to work in those five percent of the villages, 157 00:08:07,458 --> 00:08:09,518 about 35,000 villages, 158 00:08:09,542 --> 00:08:12,750 to actually be able to solve a large piece of the problem. 159 00:08:13,875 --> 00:08:15,143 And that's really key, 160 00:08:15,167 --> 00:08:17,559 because these villages 161 00:08:17,583 --> 00:08:20,726 not only have high burden of out-of-school girls, 162 00:08:20,750 --> 00:08:23,601 but also a lot of related indicators, right, 163 00:08:23,625 --> 00:08:28,976 like malnutrition, stunting, poverty, infant mortality, 164 00:08:29,000 --> 00:08:30,684 child marriage. 165 00:08:30,708 --> 00:08:32,643 So by working and focusing here, 166 00:08:32,667 --> 00:08:35,143 you can actually create a large multiplier effect 167 00:08:35,167 --> 00:08:37,768 across all of these indicators. 168 00:08:37,792 --> 00:08:39,058 And it would mean 169 00:08:39,082 --> 00:08:43,457 that we would be able to bring back 1.6 million girls back into school. 170 00:08:44,792 --> 00:08:50,875 (Applause) 171 00:08:51,750 --> 00:08:55,184 I have to say, I have been doing this for over a decade, 172 00:08:55,208 --> 00:09:00,018 and I have never met a girl who said to me, 173 00:09:00,042 --> 00:09:01,768 you know, "I want to stay at home," 174 00:09:01,792 --> 00:09:03,184 "I want to graze the cattle," 175 00:09:03,208 --> 00:09:05,476 "I want to look after the siblings," 176 00:09:05,500 --> 00:09:07,518 "I want to be a child bride." 177 00:09:07,542 --> 00:09:11,750 Every single girl I meet wants to go to school. 178 00:09:12,917 --> 00:09:14,893 And that's what we really want to do. 179 00:09:14,917 --> 00:09:19,042 We want to be able to fulfill those 1.6 million dreams. 180 00:09:20,625 --> 00:09:21,934 And it doesn't take much. 181 00:09:21,958 --> 00:09:25,893 To find and enroll a girl with our model is about 20 dollars. 182 00:09:25,917 --> 00:09:29,101 To make sure that she is learning and providing a learning program, 183 00:09:29,125 --> 00:09:31,393 it's another 40 dollars. 184 00:09:31,417 --> 00:09:33,559 But today is the time to do it. 185 00:09:33,583 --> 00:09:37,726 Because she is truly the biggest asset we have. 186 00:09:37,750 --> 00:09:41,101 I am Safeena Husain, and I educate girls. 187 00:09:41,125 --> 00:09:42,393 Thank you. 188 00:09:42,417 --> 00:09:45,958 (Applause)