1 00:00:01,889 --> 00:00:04,595 The world today has many problems. 2 00:00:04,619 --> 00:00:09,598 And they're all very complicated and interconnected and difficult. 3 00:00:10,172 --> 00:00:12,585 But there is something we can do. 4 00:00:12,609 --> 00:00:13,807 I believe 5 00:00:13,831 --> 00:00:18,665 that girls education is the closes thing we have to a silver bullet 6 00:00:18,689 --> 00:00:22,467 to help solve some of the world's most difficult problems. 7 00:00:23,110 --> 00:00:25,245 But you don't have to take my word for it. 8 00:00:25,269 --> 00:00:26,918 The World Bank says 9 00:00:26,942 --> 00:00:30,220 that girls education is one of the best investments 10 00:00:30,244 --> 00:00:31,844 that a country can make. 11 00:00:32,284 --> 00:00:34,403 It helps to positively impact 12 00:00:34,427 --> 00:00:37,974 nine of the 17 Sustainable Development Goals. 13 00:00:37,998 --> 00:00:42,437 Everything, from health, nutrition, employment, 14 00:00:42,461 --> 00:00:46,378 all of these are positively impacted when girls are educated. 15 00:00:47,664 --> 00:00:52,824 Additionally, climate scientists have recently rated girls education 16 00:00:52,848 --> 00:00:57,927 at number six out of 80 actions to reverse global warming. 17 00:00:58,570 --> 00:01:03,639 At number six, it's rated higher than solar panels and electric cars. 18 00:01:05,553 --> 00:01:08,385 And that's because when girls are educated, 19 00:01:08,409 --> 00:01:10,211 they have smaller families, 20 00:01:10,235 --> 00:01:13,637 and the resulting reduction in population 21 00:01:13,661 --> 00:01:16,716 reduces carbon emissions significantly. 22 00:01:18,506 --> 00:01:21,982 But more than that, you know, it's a problem we have to solve once. 23 00:01:22,739 --> 00:01:27,080 Because an educated mother is more than twice as likely 24 00:01:27,104 --> 00:01:28,704 to educate her children. 25 00:01:29,144 --> 00:01:31,160 Which means that by doing it once, 26 00:01:31,184 --> 00:01:34,721 we can close the gender and literacy gap forever. 27 00:01:35,246 --> 00:01:36,705 I work in India, 28 00:01:36,729 --> 00:01:39,571 which has made incredible progress 29 00:01:39,595 --> 00:01:42,328 in bringing elementary education for all. 30 00:01:42,817 --> 00:01:46,865 However, we still have four million out-of-school girls, 31 00:01:46,889 --> 00:01:48,739 one of the highest in the world. 32 00:01:49,898 --> 00:01:53,612 And girls are out of school because of, obviously poverty, 33 00:01:53,636 --> 00:01:55,879 social, cultural factors. 34 00:01:55,903 --> 00:01:58,934 But there's also this underlying factor of mindset. 35 00:02:00,236 --> 00:02:03,169 I have met a girl whose name was Naaraaz [Nath.] 36 00:02:03,641 --> 00:02:05,386 Naaraaz means angry. 37 00:02:05,847 --> 00:02:08,323 And when I asked her, "Why is your name 'angry'?" 38 00:02:08,347 --> 00:02:12,760 she said, "Because everybody was so angry when a girl was born." 39 00:02:14,110 --> 00:02:16,602 Another girl called Antim Bala, 40 00:02:16,626 --> 00:02:18,359 which means the last girl. 41 00:02:18,904 --> 00:02:22,698 Because everybody hoped that would be the last girl to be born. 42 00:02:23,644 --> 00:02:25,334 A girl called [Achuki.] 43 00:02:26,311 --> 00:02:28,350 It means somebody who has arrived. 44 00:02:28,374 --> 00:02:30,937 Not wanted, but arrived. 45 00:02:31,652 --> 00:02:33,815 And it is this mindset 46 00:02:33,839 --> 00:02:37,007 that keeps girls from school or completing their education. 47 00:02:37,442 --> 00:02:40,125 It's this belief that a goat is an asset, 48 00:02:40,149 --> 00:02:41,882 and a girl is a liability. 49 00:02:44,678 --> 00:02:48,122 My organization Educate Girls works to change this. 50 00:02:48,146 --> 00:02:51,075 And we work in some of the most difficult, rural, 51 00:02:51,099 --> 00:02:52,899 remote and tribal villages. 52 00:02:54,009 --> 00:02:55,510 And how do we do it? 53 00:02:55,534 --> 00:02:57,843 We first and foremost find 54 00:02:57,867 --> 00:03:01,734 young, passionate, educated youth from the same villages. 55 00:03:02,089 --> 00:03:03,803 Both men and women. 56 00:03:04,474 --> 00:03:05,871 And we call them Team Balika, 57 00:03:05,895 --> 00:03:07,490 balika just means the girl child, 58 00:03:07,514 --> 00:03:10,331 so this is a team that we are creating for the girl child. 59 00:03:11,434 --> 00:03:14,322 And so once we recruit our community volunteers, 60 00:03:14,346 --> 00:03:17,608 we train them, we mentor them, we hand-hold them. 61 00:03:18,461 --> 00:03:20,037 That's when our work starts. 62 00:03:20,061 --> 00:03:24,410 And the first piece we do is about identifying every single girl 63 00:03:24,434 --> 00:03:26,168 who's not going to school. 64 00:03:26,711 --> 00:03:29,937 But the way we do it is a little different and high-tech, 65 00:03:29,961 --> 00:03:31,653 at least in my view. 66 00:03:32,307 --> 00:03:35,021 Each of our front-line staff have a smart phone. 67 00:03:35,045 --> 00:03:37,719 It has its own Educate Girls app. 68 00:03:37,743 --> 00:03:40,950 And this app has everything that our team needs. 69 00:03:40,974 --> 00:03:46,436 It has digital maps of where they're going to be conducting the survey, 70 00:03:46,460 --> 00:03:48,761 it has the survey in it, all the questions, 71 00:03:48,785 --> 00:03:51,626 little guides on how best to conduct the survey, 72 00:03:51,650 --> 00:03:55,779 so that the data that comes to us is in real time and is of good quality. 73 00:03:56,819 --> 00:03:58,089 So armed with this, 74 00:03:58,113 --> 00:04:01,498 our teams and our volunteers go door-to-door 75 00:04:01,522 --> 00:04:05,315 to every single household to find every single girl 76 00:04:05,339 --> 00:04:08,220 who may either we never enrolled or dropped out of school. 77 00:04:08,244 --> 00:04:11,506 And because we have this data and technology piece, 78 00:04:11,530 --> 00:04:15,493 very quickly we can figure out who the girls are and where they are. 79 00:04:15,517 --> 00:04:17,914 Because each of our villages are ge-otagged 80 00:04:17,938 --> 00:04:20,334 and we can actually build that information out 81 00:04:20,358 --> 00:04:21,625 very, very quickly. 82 00:04:22,533 --> 00:04:25,130 And so once we know where the girls are, 83 00:04:25,154 --> 00:04:28,583 we actually start the process of bringing them back into school. 84 00:04:28,924 --> 00:04:31,814 And that actually is just our community mobilization process, 85 00:04:31,838 --> 00:04:35,252 it starts with village meetings, neighborhood meetings, 86 00:04:35,276 --> 00:04:39,220 and as you see, individual counseling of parents and families, 87 00:04:39,244 --> 00:04:41,879 to be able to bring the girls back into school. 88 00:04:41,903 --> 00:04:46,529 And this can take anything from a few weeks to a few months. 89 00:04:47,639 --> 00:04:50,076 And once we bring the girls into the school system, 90 00:04:50,100 --> 00:04:51,506 we also work with the schools 91 00:04:51,530 --> 00:04:55,418 to make sure that schools have all the basic infrastructure 92 00:04:55,442 --> 00:04:57,354 so that the girls would be able to stay. 93 00:04:57,378 --> 00:05:00,196 And this would include separate toilet for girls, 94 00:05:00,220 --> 00:05:01,839 drinking water, 95 00:05:01,863 --> 00:05:04,855 things that will help them to be retained. 96 00:05:04,879 --> 00:05:08,641 But all of this would be useless if our children weren't learning. 97 00:05:08,665 --> 00:05:10,915 So we actually run a learning program. 98 00:05:11,593 --> 00:05:13,703 And this is a supplementary learning program, 99 00:05:13,727 --> 00:05:16,029 and it's very, very important, 100 00:05:16,053 --> 00:05:19,362 because most of our children are first-generation learners. 101 00:05:19,934 --> 00:05:22,832 That means there's nobody at home to help them with homework, 102 00:05:22,856 --> 00:05:25,060 there's nobody who can support their education. 103 00:05:25,084 --> 00:05:26,768 Their parents can't read and write. 104 00:05:26,792 --> 00:05:28,419 So it's really, really key 105 00:05:28,443 --> 00:05:32,078 that we do the support of the learning in the classrooms. 106 00:05:32,625 --> 00:05:34,506 So this is essentially our model, 107 00:05:34,530 --> 00:05:36,840 in terms of finding, bringing the girls in, 108 00:05:36,864 --> 00:05:39,188 making sure that they're staying and learning. 109 00:05:39,490 --> 00:05:41,690 And we know that our model works. 110 00:05:42,133 --> 00:05:44,037 And we know this because 111 00:05:44,061 --> 00:05:47,196 a most recent randomized control evaluation 112 00:05:47,220 --> 00:05:48,918 confirms its efficacy. 113 00:05:50,807 --> 00:05:54,520 Our evaluator found that over a three-year period 114 00:05:54,544 --> 00:05:59,672 Educate Girls was able to bring back 92 percent of all out-of-school girls 115 00:05:59,696 --> 00:06:00,846 back into school. 116 00:06:01,474 --> 00:06:07,991 (Applause) 117 00:06:08,015 --> 00:06:09,451 And in terms of learning, 118 00:06:09,475 --> 00:06:12,110 our children's learning went up significantly 119 00:06:12,134 --> 00:06:14,245 as compared to control schools. 120 00:06:14,269 --> 00:06:18,160 So much so, that it was like an additional year of schooling 121 00:06:18,184 --> 00:06:19,545 for the average student. 122 00:06:19,998 --> 00:06:21,379 And that's enormous, 123 00:06:21,403 --> 00:06:24,768 when you think about a tribal child who's entering the school system 124 00:06:24,792 --> 00:06:26,058 for the first time. 125 00:06:27,057 --> 00:06:29,446 So here we have a model that works, 126 00:06:29,470 --> 00:06:31,438 we know it's scalable, 127 00:06:31,462 --> 00:06:35,109 because we are already functioning at 13,000 villages. 128 00:06:35,133 --> 00:06:36,426 We know it's smart, 129 00:06:36,450 --> 00:06:39,403 because of the use of data and technology. 130 00:06:39,427 --> 00:06:42,164 We know that it's sustainable and systemic, 131 00:06:42,188 --> 00:06:45,189 because we work in partnership with the community, 132 00:06:45,213 --> 00:06:47,085 it's actually led by the community. 133 00:06:47,419 --> 00:06:49,680 And we work in partnership with the government, 134 00:06:49,704 --> 00:06:52,903 so there's no creation of a parallel delivery system. 135 00:06:53,418 --> 00:06:56,625 And so because we have this innovative partnership 136 00:06:56,649 --> 00:07:00,553 with the community, the government, this smart model, 137 00:07:00,577 --> 00:07:03,870 we have this big, audacious dream today. 138 00:07:05,030 --> 00:07:08,840 And that is to solve a full 40 percent of the problem 139 00:07:08,864 --> 00:07:12,117 of out-of-school girls in India in the next five years. 140 00:07:13,343 --> 00:07:19,340 (Applause) 141 00:07:19,364 --> 00:07:21,546 And you're thinking, that's a little ... 142 00:07:21,991 --> 00:07:25,035 You know, how am I even thinking about doing that, 143 00:07:25,059 --> 00:07:28,872 because India is not a small place, it's a huge country. 144 00:07:30,053 --> 00:07:32,553 It's a country of over a billion people. 145 00:07:32,577 --> 00:07:36,212 We have 650,000 villages. 146 00:07:36,561 --> 00:07:38,188 How is it that I'm standing here, 147 00:07:38,212 --> 00:07:40,172 saying that one small organization 148 00:07:40,196 --> 00:07:43,282 is going to solve a full 40 percent of the problem? 149 00:07:44,109 --> 00:07:46,720 And that's because we have a key insight. 150 00:07:46,744 --> 00:07:47,895 And that is, 151 00:07:47,919 --> 00:07:52,537 because of our entire approach with data and with technology, 152 00:07:52,561 --> 00:07:55,243 that five percent of villages in India 153 00:07:55,267 --> 00:07:58,283 have 40 percent of the out-of school girls. 154 00:07:58,307 --> 00:08:01,069 And this is a big, big piece of the puzzle. 155 00:08:01,093 --> 00:08:04,262 Which means, I don't have to work across the entire country. 156 00:08:04,286 --> 00:08:07,428 I have to work in those five percent of the villages, 157 00:08:07,452 --> 00:08:09,524 about 35,000 villages, 158 00:08:09,548 --> 00:08:12,754 to actually be able to solve a large piece of the problem. 159 00:08:13,865 --> 00:08:15,093 And that's really key, 160 00:08:15,117 --> 00:08:17,577 because these villages 161 00:08:17,601 --> 00:08:20,736 not only have high burden of out-of-school girls, 162 00:08:20,760 --> 00:08:23,609 but also lot of related indicators, right, 163 00:08:23,633 --> 00:08:28,967 like malnutrition, stunting, poverty, infant mortality, 164 00:08:28,991 --> 00:08:30,141 child marriage. 165 00:08:30,706 --> 00:08:32,643 So by working and focusing here, 166 00:08:32,667 --> 00:08:35,129 you can actually create a large multiplier effect 167 00:08:35,153 --> 00:08:37,158 across all of these indicators. 168 00:08:37,784 --> 00:08:38,936 And it would mean 169 00:08:38,960 --> 00:08:43,760 that we would be able to bring back 1.6 million girls back into school. 170 00:08:44,784 --> 00:08:50,860 (Applause) 171 00:08:51,741 --> 00:08:55,186 I have to say, I have been doing this for over a decade, 172 00:08:55,210 --> 00:09:00,037 and I have never met a girl who said to me, 173 00:09:00,061 --> 00:09:01,752 you know, "I want to stay at home," 174 00:09:01,776 --> 00:09:03,172 "I want to graze the cattle," 175 00:09:03,196 --> 00:09:05,459 "I want to look after the siblings," 176 00:09:05,483 --> 00:09:07,506 "I want to be a child bride." 177 00:09:07,530 --> 00:09:11,767 Every single girl I meet wants to go to school. 178 00:09:12,919 --> 00:09:14,886 And that's what we really want to do. 179 00:09:14,910 --> 00:09:19,021 We want to be able to fulfill those 1.6 million dreams. 180 00:09:20,609 --> 00:09:21,862 And it doesn't take much. 181 00:09:21,886 --> 00:09:25,309 To find and enroll a girl with our model is about 20 dollars. 182 00:09:25,934 --> 00:09:29,101 To make sure that she is learning and providing a learning program, 183 00:09:29,125 --> 00:09:30,725 it's another 40 dollars. 184 00:09:31,430 --> 00:09:33,573 But today is the time to do it. 185 00:09:33,597 --> 00:09:36,961 Because she is truly the biggest asset we have. 186 00:09:37,740 --> 00:09:40,811 I am Safeena Husain, and I educate girls. 187 00:09:41,129 --> 00:09:42,309 Thank you. 188 00:09:42,333 --> 00:09:45,962 (Applause)