WEBVTT 00:00:01.889 --> 00:00:04.595 The world today has many problems. 00:00:04.619 --> 00:00:09.598 And they're all very complicated and interconnected and difficult. 00:00:10.172 --> 00:00:12.585 But there is something we can do. 00:00:12.609 --> 00:00:13.807 I believe 00:00:13.831 --> 00:00:18.665 that girls education is the closes thing we have to a silver bullet 00:00:18.689 --> 00:00:22.467 to help solve some of the world's most difficult problems. 00:00:23.110 --> 00:00:25.245 But you don't have to take my word for it. 00:00:25.269 --> 00:00:26.918 The World Bank says 00:00:26.942 --> 00:00:30.220 that girls education is one of the best investments 00:00:30.244 --> 00:00:31.844 that a country can make. 00:00:32.284 --> 00:00:34.403 It helps to positively impact 00:00:34.427 --> 00:00:37.974 nine of the 17 Sustainable Development Goals. 00:00:37.998 --> 00:00:42.437 Everything, from health, nutrition, employment, 00:00:42.461 --> 00:00:46.378 all of these are positively impacted when girls are educated. 00:00:47.664 --> 00:00:52.824 Additionally, climate scientists have recently rated girls education 00:00:52.848 --> 00:00:57.927 at number six out of 80 actions to reverse global warming. 00:00:58.570 --> 00:01:03.639 At number six, it's rated higher than solar panels and electric cars. 00:01:05.553 --> 00:01:08.385 And that's because when girls are educated, 00:01:08.409 --> 00:01:10.211 they have smaller families, 00:01:10.235 --> 00:01:13.637 and the resulting reduction in population 00:01:13.661 --> 00:01:16.716 reduces carbon emissions significantly. 00:01:18.506 --> 00:01:21.982 But more than that, you know, it's a problem we have to solve once. 00:01:22.739 --> 00:01:27.080 Because an educated mother is more than twice as likely 00:01:27.104 --> 00:01:28.704 to educate her children. 00:01:29.144 --> 00:01:31.160 Which means that by doing it once, 00:01:31.184 --> 00:01:34.721 we can close the gender and literacy gap forever. 00:01:35.246 --> 00:01:36.705 I work in India, 00:01:36.729 --> 00:01:39.571 which has made incredible progress 00:01:39.595 --> 00:01:42.328 in bringing elementary education for all. 00:01:42.817 --> 00:01:46.865 However, we still have four million out-of-school girls, 00:01:46.889 --> 00:01:48.739 one of the highest in the world. 00:01:49.898 --> 00:01:53.612 And girls are out of school because of, obviously poverty, 00:01:53.636 --> 00:01:55.879 social, cultural factors. 00:01:55.903 --> 00:01:58.934 But there's also this underlying factor of mindset. 00:02:00.236 --> 00:02:03.169 I have met a girl whose name was Naaraaz [Nath.] 00:02:03.641 --> 00:02:05.386 Naaraaz means angry. 00:02:05.847 --> 00:02:08.323 And when I asked her, "Why is your name 'angry'?" 00:02:08.347 --> 00:02:12.760 she said, "Because everybody was so angry when a girl was born." 00:02:14.110 --> 00:02:16.602 Another girl called Antim Bala, 00:02:16.626 --> 00:02:18.359 which means the last girl. 00:02:18.904 --> 00:02:22.698 Because everybody hoped that would be the last girl to be born. 00:02:23.644 --> 00:02:25.334 A girl called [Achuki.] 00:02:26.311 --> 00:02:28.350 It means somebody who has arrived. 00:02:28.374 --> 00:02:30.937 Not wanted, but arrived. 00:02:31.652 --> 00:02:33.815 And it is this mindset 00:02:33.839 --> 00:02:37.007 that keeps girls from school or completing their education. 00:02:37.442 --> 00:02:40.125 It's this belief that a goat is an asset, 00:02:40.149 --> 00:02:41.882 and a girl is a liability. 00:02:44.678 --> 00:02:48.122 My organization Educate Girls works to change this. 00:02:48.146 --> 00:02:51.075 And we work in some of the most difficult, rural, 00:02:51.099 --> 00:02:52.899 remote and tribal villages. 00:02:54.009 --> 00:02:55.510 And how do we do it? 00:02:55.534 --> 00:02:57.843 We first and foremost find 00:02:57.867 --> 00:03:01.734 young, passionate, educated youth from the same villages. 00:03:02.089 --> 00:03:03.803 Both men and women. 00:03:04.474 --> 00:03:05.871 And we call them Team Balika, 00:03:05.895 --> 00:03:07.490 balika just means the girl child, 00:03:07.514 --> 00:03:10.331 so this is a team that we are creating for the girl child. 00:03:11.434 --> 00:03:14.322 And so once we recruit our community volunteers, 00:03:14.346 --> 00:03:17.608 we train them, we mentor them, we hand-hold them. 00:03:18.461 --> 00:03:20.037 That's when our work starts. 00:03:20.061 --> 00:03:24.410 And the first piece we do is about identifying every single girl 00:03:24.434 --> 00:03:26.168 who's not going to school. 00:03:26.711 --> 00:03:29.937 But the way we do it is a little different and high-tech, 00:03:29.961 --> 00:03:31.653 at least in my view. 00:03:32.307 --> 00:03:35.021 Each of our front-line staff have a smart phone. 00:03:35.045 --> 00:03:37.719 It has its own Educate Girls app. 00:03:37.743 --> 00:03:40.950 And this app has everything that our team needs. 00:03:40.974 --> 00:03:46.436 It has digital maps of where they're going to be conducting the survey, 00:03:46.460 --> 00:03:48.761 it has the survey in it, all the questions, 00:03:48.785 --> 00:03:51.626 little guides on how best to conduct the survey, 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. 00:03:56.819 --> 00:03:58.089 So armed with this, 00:03:58.113 --> 00:04:01.498 our teams and our volunteers go door-to-door 00:04:01.522 --> 00:04:05.315 to every single household to find every single girl 00:04:05.339 --> 00:04:08.220 who may either we never enrolled or dropped out of school. 00:04:08.244 --> 00:04:11.506 And because we have this data and technology piece, 00:04:11.530 --> 00:04:15.493 very quickly we can figure out who the girls are and where they are. 00:04:15.517 --> 00:04:17.914 Because each of our villages are ge-otagged 00:04:17.938 --> 00:04:20.334 and we can actually build that information out 00:04:20.358 --> 00:04:21.625 very, very quickly. 00:04:22.533 --> 00:04:25.130 And so once we know where the girls are, 00:04:25.154 --> 00:04:28.583 we actually start the process of bringing them back into school. 00:04:28.924 --> 00:04:31.814 And that actually is just our community mobilization process, 00:04:31.838 --> 00:04:35.252 it starts with village meetings, neighborhood meetings, 00:04:35.276 --> 00:04:39.220 and as you see, individual counseling of parents and families, 00:04:39.244 --> 00:04:41.879 to be able to bring the girls back into school. 00:04:41.903 --> 00:04:46.529 And this can take anything from a few weeks to a few months. 00:04:47.639 --> 00:04:50.076 And once we bring the girls into the school system, 00:04:50.100 --> 00:04:51.506 we also work with the schools 00:04:51.530 --> 00:04:55.418 to make sure that schools have all the basic infrastructure 00:04:55.442 --> 00:04:57.354 so that the girls would be able to stay. 00:04:57.378 --> 00:05:00.196 And this would include separate toilet for girls, 00:05:00.220 --> 00:05:01.839 drinking water, 00:05:01.863 --> 00:05:04.855 things that will help them to be retained. 00:05:04.879 --> 00:05:08.641 But all of this would be useless if our children weren't learning. 00:05:08.665 --> 00:05:10.915 So we actually run a learning program. 00:05:11.593 --> 00:05:13.703 And this is a supplementary learning program, 00:05:13.727 --> 00:05:16.029 and it's very, very important, 00:05:16.053 --> 00:05:19.362 because most of our children are first-generation learners. 00:05:19.934 --> 00:05:22.832 That means there's nobody at home to help them with homework, 00:05:22.856 --> 00:05:25.060 there's nobody who can support their education. 00:05:25.084 --> 00:05:26.768 Their parents can't read and write. 00:05:26.792 --> 00:05:28.419 So it's really, really key 00:05:28.443 --> 00:05:32.078 that we do the support of the learning in the classrooms. 00:05:32.625 --> 00:05:34.506 So this is essentially our model, 00:05:34.530 --> 00:05:36.840 in terms of finding, bringing the girls in, 00:05:36.864 --> 00:05:39.188 making sure that they're staying and learning. 00:05:39.490 --> 00:05:41.690 And we know that our model works. 00:05:42.133 --> 00:05:44.037 And we know this because 00:05:44.061 --> 00:05:47.196 a most recent randomized control evaluation 00:05:47.220 --> 00:05:48.918 confirms its efficacy. 00:05:50.807 --> 00:05:54.520 Our evaluator found that over a three-year period 00:05:54.544 --> 00:05:59.672 Educate Girls was able to bring back 92 percent of all out-of-school girls 00:05:59.696 --> 00:06:00.846 back into school. 00:06:01.474 --> 00:06:07.991 (Applause) 00:06:08.015 --> 00:06:09.451 And in terms of learning, 00:06:09.475 --> 00:06:12.110 our children's learning went up significantly 00:06:12.134 --> 00:06:14.245 as compared to control schools. 00:06:14.269 --> 00:06:18.160 So much so, that it was like an additional year of schooling 00:06:18.184 --> 00:06:19.545 for the average student. 00:06:19.998 --> 00:06:21.379 And that's enormous, 00:06:21.403 --> 00:06:24.768 when you think about a tribal child who's entering the school system 00:06:24.792 --> 00:06:26.058 for the first time. 00:06:27.057 --> 00:06:29.446 So here we have a model that works, 00:06:29.470 --> 00:06:31.438 we know it's scalable, 00:06:31.462 --> 00:06:35.109 because we are already functioning at 13,000 villages. 00:06:35.133 --> 00:06:36.426 We know it's smart, 00:06:36.450 --> 00:06:39.403 because of the use of data and technology. 00:06:39.427 --> 00:06:42.164 We know that it's sustainable and systemic, 00:06:42.188 --> 00:06:45.189 because we work in partnership with the community, 00:06:45.213 --> 00:06:47.085 it's actually led by the community. 00:06:47.419 --> 00:06:49.680 And we work in partnership with the government, 00:06:49.704 --> 00:06:52.903 so there's no creation of a parallel delivery system. 00:06:53.418 --> 00:06:56.625 And so because we have this innovative partnership 00:06:56.649 --> 00:07:00.553 with the community, the government, this smart model, 00:07:00.577 --> 00:07:03.870 we have this big, audacious dream today. 00:07:05.030 --> 00:07:08.840 And that is to solve a full 40 percent of the problem 00:07:08.864 --> 00:07:12.117 of out-of-school girls in India in the next five years. 00:07:13.343 --> 00:07:19.340 (Applause) 00:07:19.364 --> 00:07:21.546 And you're thinking, that's a little ... 00:07:21.991 --> 00:07:25.035 You know, how am I even thinking about doing that, 00:07:25.059 --> 00:07:28.872 because India is not a small place, it's a huge country. 00:07:30.053 --> 00:07:32.553 It's a country of over a billion people. 00:07:32.577 --> 00:07:36.212 We have 650,000 villages. 00:07:36.561 --> 00:07:38.188 How is it that I'm standing here, 00:07:38.212 --> 00:07:40.172 saying that one small organization 00:07:40.196 --> 00:07:43.282 is going to solve a full 40 percent of the problem? 00:07:44.109 --> 00:07:46.720 And that's because we have a key insight. 00:07:46.744 --> 00:07:47.895 And that is, 00:07:47.919 --> 00:07:52.537 because of our entire approach with data and with technology, 00:07:52.561 --> 00:07:55.243 that five percent of villages in India 00:07:55.267 --> 00:07:58.283 have 40 percent of the out-of school girls. 00:07:58.307 --> 00:08:01.069 And this is a big, big piece of the puzzle. 00:08:01.093 --> 00:08:04.262 Which means, I don't have to work across the entire country. 00:08:04.286 --> 00:08:07.428 I have to work in those five percent of the villages, 00:08:07.452 --> 00:08:09.524 about 35,000 villages, 00:08:09.548 --> 00:08:12.754 to actually be able to solve a large piece of the problem. 00:08:13.865 --> 00:08:15.093 And that's really key, 00:08:15.117 --> 00:08:17.577 because these villages 00:08:17.601 --> 00:08:20.736 not only have high burden of out-of-school girls, 00:08:20.760 --> 00:08:23.609 but also lot of related indicators, right, 00:08:23.633 --> 00:08:28.967 like malnutrition, stunting, poverty, infant mortality, 00:08:28.991 --> 00:08:30.141 child marriage. 00:08:30.706 --> 00:08:32.643 So by working and focusing here, 00:08:32.667 --> 00:08:35.129 you can actually create a large multiplier effect 00:08:35.153 --> 00:08:37.158 across all of these indicators. 00:08:37.784 --> 00:08:38.936 And it would mean 00:08:38.960 --> 00:08:43.760 that we would be able to bring back 1.6 million girls back into school. 00:08:44.784 --> 00:08:50.860 (Applause) 00:08:51.741 --> 00:08:55.186 I have to say, I have been doing this for over a decade, 00:08:55.210 --> 00:09:00.037 and I have never met a girl who said to me, 00:09:00.061 --> 00:09:01.752 you know, "I want to stay at home," 00:09:01.776 --> 00:09:03.172 "I want to graze the cattle," 00:09:03.196 --> 00:09:05.459 "I want to look after the siblings," 00:09:05.483 --> 00:09:07.506 "I want to be a child bride." 00:09:07.530 --> 00:09:11.767 Every single girl I meet wants to go to school. 00:09:12.919 --> 00:09:14.886 And that's what we really want to do. 00:09:14.910 --> 00:09:19.021 We want to be able to fulfill those 1.6 million dreams. 00:09:20.609 --> 00:09:21.862 And it doesn't take much. 00:09:21.886 --> 00:09:25.309 To find and enroll a girl with our model is about 20 dollars. 00:09:25.934 --> 00:09:29.101 To make sure that she is learning and providing a learning program, 00:09:29.125 --> 00:09:30.725 it's another 40 dollars. 00:09:31.430 --> 00:09:33.573 But today is the time to do it. 00:09:33.597 --> 00:09:36.961 Because she is truly the biggest asset we have. 00:09:37.740 --> 00:09:40.811 I am Safeena Husain, and I educate girls. 00:09:41.129 --> 00:09:42.309 Thank you. 00:09:42.333 --> 00:09:45.962 (Applause)