WEBVTT 00:00:00.083 --> 00:00:02.836 Ankur, thanks for taking the time to be with me today. 00:00:04.004 --> 00:00:07.507 I am so excited about this because you are one of my 00:00:07.507 --> 00:00:12.137 favorite thinkers in the whole space of SDGs and global development. 00:00:12.345 --> 00:00:14.556 But before we get into questions about that, I actually want to 00:00:14.556 --> 00:00:16.141 start with something a little more personal. 00:00:16.516 --> 00:00:19.185 Will you tell a bit about your story and how you ended up at 00:00:19.185 --> 00:00:20.145 the Gates Foundation? 00:00:20.812 --> 00:00:21.146 Pleasure. 00:00:21.146 --> 00:00:21.604 Thank you, Jim. 00:00:23.064 --> 00:00:26.609 I grew up in a household which was slightly weird. 00:00:27.485 --> 00:00:30.363 The belief was that you have to dedicate your life to something 00:00:30.363 --> 00:00:31.281 bigger than yourself. 00:00:32.198 --> 00:00:36.161 My parents, they were in New York City in the 70s, and my dad 00:00:36.161 --> 00:00:39.122 was a physician, was just taking off the sort of American dream. 00:00:39.122 --> 00:00:43.334 And him, his friends, my mom, everybody made a decision to 00:00:43.334 --> 00:00:45.879 move back to India, start a health NGO. 00:00:46.629 --> 00:00:50.967 And so we went from this pathway of like riches to a little bit 00:00:50.967 --> 00:00:53.011 of scarcity, but a lot of joy, 00:00:53.178 --> 00:00:56.222 and because they dedicated their lives to something bigger than themselves. 00:00:56.556 --> 00:00:59.601 So that was the backdrop of where I grew up. 00:00:59.601 --> 00:01:03.354 And India was going through the economic boom, this reform process. 00:01:03.354 --> 00:01:07.400 And I decided to be an economist and be part of the group of 00:01:07.400 --> 00:01:11.613 people who were going to get 400 million people out of poverty. 00:01:11.613 --> 00:01:15.825 And got my PhD from Chicago, and had a thesis advisor who said 00:01:15.825 --> 00:01:19.788 don't be just one more smart person to join the development 00:01:19.788 --> 00:01:24.042 sector—go to some other sector where things are working, learn, 00:01:24.042 --> 00:01:25.376 and then bring that. 00:01:25.627 --> 00:01:27.087 And that brought me to BCG. 00:01:27.504 --> 00:01:31.508 And it was sort of the great six years of my life. Learned a lot, 00:01:31.508 --> 00:01:35.261 managed to do about a third of my time in social impact work. 00:01:35.261 --> 00:01:39.808 And at some point, made—decided to make the move back and ended 00:01:39.808 --> 00:01:44.229 up at the Gates Foundation. And have this really, really cool 00:01:44.229 --> 00:01:44.813 job now. 00:01:44.813 --> 00:01:48.983 Well, this is, this is like the best kind of weird that parents 00:01:48.983 --> 00:01:52.946 could be, for sure, if this is where it ends up leading you. 00:01:53.446 --> 00:01:56.825 And, and I am personally thankful that that was their choice. 00:01:56.825 --> 00:01:59.285 And now we get the chance to collaborate together. 00:02:00.286 --> 00:02:03.331 So now put that economist hat on, put that chief strategy 00:02:03.331 --> 00:02:06.459 officer hat on, and we're a little over halfway through the 00:02:06.459 --> 00:02:07.043 SDG period. 00:02:07.627 --> 00:02:08.211 Where are we? 00:02:08.211 --> 00:02:11.840 Where are we overall from a big picture standpoint? The 00:02:11.840 --> 00:02:15.885 scorecard doesn't look great. And the kind of issues—we don't 00:02:15.885 --> 00:02:19.472 have enough resources for the battle in the next half. 00:02:20.348 --> 00:02:24.060 Developing countries are facing debt burden, rich world have 00:02:24.060 --> 00:02:25.353 other pressing needs. 00:02:25.353 --> 00:02:29.440 They're inward focus, climate change, Ukraine, migrants—that's 00:02:29.440 --> 00:02:33.111 competing with other needs, which are global health and 00:02:33.111 --> 00:02:34.362 global development. 00:02:34.362 --> 00:02:38.867 And so the task is harder, resources are thinner, but I'm 00:02:38.867 --> 00:02:40.326 kind of optimistic. 00:02:40.618 --> 00:02:44.038 OK, well, and I would love to hear then, you know, we had this 00:02:44.038 --> 00:02:47.333 tremendous success in the MDG era, the beginning of the SDG 00:02:47.333 --> 00:02:50.628 era, and then we've hit this, you know, really tough plateau 00:02:50.628 --> 00:02:53.381 and some of the trends that you're talking about. 00:02:53.548 --> 00:02:56.509 So I'd love to hear like, what is it that's making you optimistic? 00:02:56.634 --> 00:03:01.431 We're at a revolution right now, in the sense of science is—the 00:03:01.431 --> 00:03:05.268 scientific frontier on health care, on agriculture 00:03:05.268 --> 00:03:08.062 development. Climate change is here. 00:03:08.062 --> 00:03:11.608 Climate change is going to hurt a lot of farmers. But we have 00:03:11.608 --> 00:03:14.569 the science that can produce seeds that are drought 00:03:14.569 --> 00:03:17.697 resistant, pest resistant, like temperature resistant. 00:03:17.697 --> 00:03:19.032 And so we're pushing that frontier. 00:03:19.282 --> 00:03:22.493 COVID hit us five years back, and we came up with a vaccine 00:03:22.493 --> 00:03:24.954 and we put shots in arms in less than a year. 00:03:24.954 --> 00:03:26.456 Like this is, it's amazing. 00:03:26.456 --> 00:03:29.125 The scientific frontier is crazy and it's brilliant. 00:03:30.460 --> 00:03:32.128 And now the AI frontier is coming. 00:03:32.837 --> 00:03:36.299 When the industrial revolution happened, we increased labor 00:03:36.299 --> 00:03:39.844 productivity by 400%, and you can just imagine that happening 00:03:39.844 --> 00:03:40.511 once again. 00:03:40.595 --> 00:03:44.307 You have a teacher in a classroom in Ghana who is faced 00:03:44.307 --> 00:03:48.311 with 50 kids, seven different learning levels, where one kid 00:03:48.311 --> 00:03:52.398 can't even identify a number to another one who can do 1 + 1, 00:03:52.398 --> 00:03:54.692 another who can do like 111 + 111. 00:03:55.443 --> 00:03:58.154 That kid is faced with an impossible task of teaching 00:03:58.154 --> 00:04:00.073 everybody and helping everybody grow. 00:04:00.073 --> 00:04:04.869 An AI-enabled teacher with the same resources, you could just 00:04:04.869 --> 00:04:08.539 truly, truly change the productivity frontier. 00:04:08.539 --> 00:04:10.583 And so, it's kind of exciting. 00:04:10.583 --> 00:04:14.921 So I am very hopeful that if we harness the power of science and 00:04:14.921 --> 00:04:17.048 technology, we could do wonders. 00:04:18.424 --> 00:04:19.676 Thank you, Ankur. 00:04:19.676 --> 00:04:23.680 I share that optimism by the way. I absolutely agree with you 00:04:23.680 --> 00:04:27.809 that there's this, there is a path out and that innovation and 00:04:27.809 --> 00:04:31.437 scaling innovation is that way to break the compromise. 00:04:31.479 --> 00:04:32.563 A hundred percent with you. 00:04:32.605 --> 00:04:34.190 And so glad to get to hear from you today. 00:04:34.357 --> 00:04:34.649 Thanks. 00:04:34.774 --> 00:04:35.066 Pleasure.