Recorded at | April 15, 2019 |
---|---|
Event | TED2019 |
Duration (min:sec) | 09:45 |
Video Type | TED Stage Talk |
Words per minute | 172.54 medium |
Readability (FK) | 61.09 easy |
Speaker | Safeena Husain |
Official TED page for this talk
Synopsis
"Girls' education is the closest thing we have to a silver bullet to help solve some of the world's most difficult problems," says social entrepreneur Safeena Husain. In a visionary talk, she shares her plan to enroll a staggering 1.6 million girls in school over the next five years -- combining advanced analytics with door-to-door community engagement to create new educational pathways for girls in India. (This ambitious plan is part of the Audacious Project, TED's initiative to inspire and fund global change.)
1 | 00:13 | The world today has many problems. | ||
2 | 00:16 | And they're all very complicated and interconnected and difficult. | ||
3 | 00:22 | But there is something we can do. | ||
4 | 00:24 | I believe | ||
5 | 00:25 | that girls' education is the closest thing we have to a silver bullet | ||
6 | 00:30 | to help solve some of the world's most difficult problems. | ||
7 | 00:35 | But you don't have to take my word for it. | ||
8 | 00:37 | The World Bank says | ||
9 | 00:38 | that girls' education is one of the best investments | ||
10 | 00:42 | that a country can make. | ||
11 | 00:44 | It helps to positively impact | ||
12 | 00:46 | nine of the 17 Sustainable Development Goals. | ||
13 | 00:50 | Everything from health, nutrition, employment -- | ||
14 | 00:54 | all of these are positively impacted when girls are educated. | ||
15 | 00:59 | Additionally, climate scientists have recently rated girls' education | ||
16 | 01:04 | at number six out of 80 actions to reverse global warming. | ||
17 | 01:10 | At number six, it's rated higher than solar panels and electric cars. | ||
18 | 01:17 | And that's because when girls are educated, | ||
19 | 01:20 | they have smaller families, | ||
20 | 01:22 | and the resulting reduction in population | ||
21 | 01:25 | reduces carbon emissions significantly. | ||
22 | 01:30 | But more than that, you know, it's a problem we have to solve once. | ||
23 | 01:34 | Because an educated mother is more than twice as likely | ||
24 | 01:39 | to educate her children. | ||
25 | 01:41 | Which means that by doing it once, | ||
26 | 01:43 | we can close the gender and literacy gap forever. | ||
27 | 01:47 | I work in India, | ||
28 | 01:48 | which has made incredible progress | ||
29 | 01:51 | in bringing elementary education for all. | ||
30 | 01:54 | However, we still have four million out-of-school girls, | ||
31 | 01:58 | one of the highest in the world. | ||
32 | 02:01 | And girls are out of school because of, obviously poverty, | ||
33 | 02:05 | social, cultural factors. | ||
34 | 02:07 | But there's also this underlying factor of mindset. | ||
35 | 02:12 | I have met a girl whose name was Naraaz Nath. | ||
36 | 02:15 | Naaraaz means angry. | ||
37 | 02:17 | And when I asked her, "Why is your name 'angry'?" | ||
38 | 02:20 | she said, "Because everybody was so angry when a girl was born." | ||
39 | 02:26 | Another girl called Antim Bala, | ||
40 | 02:28 | which means the last girl. | ||
41 | 02:30 | Because everybody hoped that would be the last girl to be born. | ||
42 | 02:35 | A girl called Aachuki. | ||
43 | 02:38 | It means somebody who has arrived. | ||
44 | 02:40 | Not wanted, but arrived. | ||
45 | 02:43 | And it is this mindset | ||
46 | 02:45 | that keeps girls from school or completing their education. | ||
47 | 02:49 | It's this belief that a goat is an asset | ||
48 | 02:52 | and a girl is a liability. | ||
49 | 02:56 | My organization Educate Girls works to change this. | ||
50 | 03:00 | And we work in some of the most difficult, rural, | ||
51 | 03:03 | remote and tribal villages. | ||
52 | 03:06 | And how do we do it? | ||
53 | 03:07 | We first and foremost find | ||
54 | 03:09 | young, passionate, educated youth from the same villages. | ||
55 | 03:14 | Both men and women. | ||
56 | 03:16 | And we call them Team Balika, | ||
57 | 03:17 | balika just means the girl child, | ||
58 | 03:19 | so this is a team that we are creating for the girl child. | ||
59 | 03:23 | And so once we recruit our community volunteers, | ||
60 | 03:26 | we train them, we mentor them, we hand-hold them. | ||
61 | 03:30 | That's when our work starts. | ||
62 | 03:32 | And the first piece we do is about identifying every single girl | ||
63 | 03:36 | who's not going to school. | ||
64 | 03:38 | But the way we do it is a little different and high-tech, | ||
65 | 03:41 | at least in my view. | ||
66 | 03:44 | Each of our frontline staff have a smartphone. | ||
67 | 03:47 | It has its own Educate Girls app. | ||
68 | 03:49 | And this app has everything that our team needs. | ||
69 | 03:52 | It has digital maps of where they're going to be conducting the survey, | ||
70 | 03:58 | it has the survey in it, all the questions, | ||
71 | 04:00 | little guides on how best to conduct the survey, | ||
72 | 04:03 | so that the data that comes to us is in real time and is of good quality. | ||
73 | 04:08 | So armed with this, | ||
74 | 04:10 | our teams and our volunteers go door-to-door | ||
75 | 04:13 | to every single household to find every single girl | ||
76 | 04:17 | who may either we never enrolled or dropped out of school. | ||
77 | 04:20 | And because we have this data and technology piece, | ||
78 | 04:23 | very quickly we can figure out who the girls are and where they are. | ||
79 | 04:27 | Because each of our villages are geotagged, | ||
80 | 04:29 | and we can actually build that information out | ||
81 | 04:32 | very, very quickly. | ||
82 | 04:34 | And so once we know where the girls are, | ||
83 | 04:37 | we actually start the process of bringing them back into school. | ||
84 | 04:40 | And that actually is just our community mobilization process, | ||
85 | 04:43 | it starts with village meetings, neighborhood meetings, | ||
86 | 04:47 | and as you see, individual counseling of parents and families, | ||
87 | 04:51 | to be able to bring the girls back into school. | ||
88 | 04:53 | And this can take anything from a few weeks to a few months. | ||
89 | 04:59 | And once we bring the girls into the school system, | ||
90 | 05:02 | we also work with the schools | ||
91 | 05:03 | to make sure that schools have all the basic infrastructure | ||
92 | 05:07 | so that the girls will be able to stay. | ||
93 | 05:09 | And this would include a separate toilet for girls, | ||
94 | 05:12 | drinking water, | ||
95 | 05:13 | things that will help them to be retained. | ||
96 | 05:16 | But all of this would be useless if our children weren't learning. | ||
97 | 05:20 | So we actually run a learning program. | ||
98 | 05:23 | And this is a supplementary learning program, | ||
99 | 05:25 | and it's very, very important, | ||
100 | 05:28 | because most of our children are first-generation learners. | ||
101 | 05:31 | That means there's nobody at home to help them with homework, | ||
102 | 05:34 | there's nobody who can support their education. | ||
103 | 05:37 | Their parents can't read and write. | ||
104 | 05:38 | So it's really, really key | ||
105 | 05:40 | that we do the support of the learning in the classrooms. | ||
106 | 05:44 | So this is essentially our model, | ||
107 | 05:46 | in terms of finding, bringing the girls in, | ||
108 | 05:48 | making sure that they're staying and learning. | ||
109 | 05:51 | And we know that our model works. | ||
110 | 05:54 | And we know this because | ||
111 | 05:56 | a most recent randomized control evaluation | ||
112 | 05:59 | confirms its efficacy. | ||
113 | 06:02 | Our evaluator found that over a three-year period | ||
114 | 06:06 | Educate Girls was able to bring back 92 percent of all out-of-school girls | ||
115 | 06:11 | back into school. | ||
116 | 06:13 | (Applause) | ||
117 | 06:20 | And in terms of learning, | ||
118 | 06:21 | our children's learning went up significantly | ||
119 | 06:24 | as compared to control schools. | ||
120 | 06:26 | So much so, that it was like an additional year of schooling | ||
121 | 06:30 | for the average student. | ||
122 | 06:32 | And that's enormous, | ||
123 | 06:33 | when you think about a tribal child who's entering the school system | ||
124 | 06:36 | for the first time. | ||
125 | 06:39 | So here we have a model that works; | ||
126 | 06:41 | we know it's scalable, | ||
127 | 06:43 | because we are already functioning at 13,000 villages. | ||
128 | 06:47 | We know it's smart, | ||
129 | 06:48 | because of the use of data and technology. | ||
130 | 06:51 | We know that it's sustainable and systemic, | ||
131 | 06:54 | because we work in partnership with the community, | ||
132 | 06:57 | it's actually led by the community. | ||
133 | 06:59 | And we work in partnership with the government, | ||
134 | 07:01 | so there's no creation of a parallel delivery system. | ||
135 | 07:05 | And so because we have this innovative partnership | ||
136 | 07:08 | with the community, the government, this smart model, | ||
137 | 07:12 | we have this big, audacious dream today. | ||
138 | 07:17 | And that is to solve a full 40 percent of the problem | ||
139 | 07:20 | of out-of-school girls in India in the next five years. | ||
140 | 07:24 | (Applause) | ||
141 | 07:31 | And you're thinking, that's a little ... | ||
142 | 07:34 | You know, how am I even thinking about doing that, | ||
143 | 07:37 | because India is not a small place, it's a huge country. | ||
144 | 07:42 | It's a country of over a billion people. | ||
145 | 07:44 | We have 650,000 villages. | ||
146 | 07:48 | How is it that I'm standing here, | ||
147 | 07:50 | saying that one small organization | ||
148 | 07:52 | is going to solve a full 40 percent of the problem? | ||
149 | 07:56 | And that's because we have a key insight. | ||
150 | 07:58 | And that is, | ||
151 | 08:00 | because of our entire approach, with data and with technology, | ||
152 | 08:04 | that five percent of villages in India | ||
153 | 08:07 | have 40 percent of the out-of-school girls. | ||
154 | 08:10 | And this is a big, big piece of the puzzle. | ||
155 | 08:13 | Which means, I don't have to work across the entire country. | ||
156 | 08:16 | I have to work in those five percent of the villages, | ||
157 | 08:19 | about 35,000 villages, | ||
158 | 08:21 | to actually be able to solve a large piece of the problem. | ||
159 | 08:25 | And that's really key, | ||
160 | 08:27 | because these villages | ||
161 | 08:29 | not only have high burden of out-of-school girls, | ||
162 | 08:32 | but also a lot of related indicators, right, | ||
163 | 08:35 | like malnutrition, stunting, poverty, infant mortality, | ||
164 | 08:41 | child marriage. | ||
165 | 08:42 | So by working and focusing here, | ||
166 | 08:44 | you can actually create a large multiplier effect | ||
167 | 08:47 | across all of these indicators. | ||
168 | 08:49 | And it would mean | ||
169 | 08:51 | that we would be able to bring back 1.6 million girls back into school. | ||
170 | 08:56 | (Applause) | ||
171 | 09:03 | I have to say, I have been doing this for over a decade, | ||
172 | 09:07 | and I have never met a girl who said to me, | ||
173 | 09:12 | you know, "I want to stay at home," | ||
174 | 09:13 | "I want to graze the cattle," | ||
175 | 09:15 | "I want to look after the siblings," | ||
176 | 09:17 | "I want to be a child bride." | ||
177 | 09:19 | Every single girl I meet wants to go to school. | ||
178 | 09:24 | And that's what we really want to do. | ||
179 | 09:26 | We want to be able to fulfill those 1.6 million dreams. | ||
180 | 09:32 | And it doesn't take much. | ||
181 | 09:33 | To find and enroll a girl with our model is about 20 dollars. | ||
182 | 09:37 | To make sure that she is learning and providing a learning program, | ||
183 | 09:41 | it's another 40 dollars. | ||
184 | 09:43 | But today is the time to do it. | ||
185 | 09:45 | Because she is truly the biggest asset we have. | ||
186 | 09:49 | I am Safeena Husain, and I educate girls. | ||
187 | 09:53 | Thank you. | ||
188 | 09:54 | (Applause) |