1 00:00:15,076 --> 00:00:21,556 Speaker 1: Pushkin. I am Mayve Higgins, and this is solvable interviews 2 00:00:21,596 --> 00:00:24,916 Speaker 1: with the world's most innovative thinkers working to solve the 3 00:00:24,956 --> 00:00:30,396 Speaker 1: world's biggest problems. My solvable is putting the beneficiary as 4 00:00:30,436 --> 00:00:33,716 Speaker 1: the focus of the aid and philanthropic sector and not 5 00:00:33,836 --> 00:00:37,276 Speaker 1: the donor. We're letting the beneficiary choose where they want 6 00:00:37,276 --> 00:00:39,676 Speaker 1: to spend the capital and taking that decision out of 7 00:00:39,676 --> 00:00:42,916 Speaker 1: our own hands. That's Michael Faye, the co founder and 8 00:00:43,076 --> 00:00:48,116 Speaker 1: president of Give Directly. Now imagine this. You're watching TV, 9 00:00:48,356 --> 00:00:52,076 Speaker 1: or you're on your phone and you see some terrible disaster, 10 00:00:52,436 --> 00:00:55,436 Speaker 1: or you read a story about extreme poverty in a 11 00:00:55,516 --> 00:00:59,196 Speaker 1: country far from yours. If you want to help, and 12 00:00:59,396 --> 00:01:02,196 Speaker 1: if you're moved to do something, the action you take 13 00:01:02,276 --> 00:01:06,636 Speaker 1: will most likely be to send money. There are NGOs 14 00:01:06,676 --> 00:01:10,556 Speaker 1: and aid organizations all over the world. Perhaps you'll find 15 00:01:10,636 --> 00:01:14,156 Speaker 1: one working in that country or specializing in the type 16 00:01:14,156 --> 00:01:17,036 Speaker 1: of aid you'd think is needed there, and you send 17 00:01:17,076 --> 00:01:20,236 Speaker 1: them a donation. Then you feel a little bit better. 18 00:01:20,876 --> 00:01:24,476 Speaker 1: But it's important to check, isn't it How effective is 19 00:01:24,476 --> 00:01:27,876 Speaker 1: that aid system? Is it measured? Is it working for 20 00:01:27,956 --> 00:01:31,116 Speaker 1: the people that it's supposed to be helping? And how 21 00:01:31,156 --> 00:01:33,916 Speaker 1: can you even check that in the first place. Today, 22 00:01:34,156 --> 00:01:36,876 Speaker 1: governments and donors are trying to find out how their 23 00:01:36,916 --> 00:01:41,436 Speaker 1: money can make the biggest difference, and increasingly they're turning 24 00:01:41,476 --> 00:01:45,596 Speaker 1: to a promising new tool, cash transfers, in other words, 25 00:01:45,956 --> 00:01:49,476 Speaker 1: giving people cold hard cat. I guess it's not that 26 00:01:49,636 --> 00:01:53,076 Speaker 1: new anymore because since the year two thousand, a growing 27 00:01:53,156 --> 00:01:57,996 Speaker 1: number of developing countries have introduced these cash transfers instead 28 00:01:57,996 --> 00:02:01,156 Speaker 1: of giving aid in the form of goods or services, 29 00:02:01,156 --> 00:02:05,716 Speaker 1: and more recently, donors and development banks have begun championing 30 00:02:05,756 --> 00:02:09,636 Speaker 1: these programs. Cash transfer programs have spread from a few 31 00:02:09,716 --> 00:02:13,396 Speaker 1: middle income countries to basically all regions of the world. 32 00:02:13,956 --> 00:02:17,236 Speaker 1: So you can understand why a growing number of voices 33 00:02:17,516 --> 00:02:20,956 Speaker 1: are calling for an end to paying the middleman in 34 00:02:20,996 --> 00:02:24,396 Speaker 1: the shape of aid organizations, and those voices are asking 35 00:02:24,876 --> 00:02:29,316 Speaker 1: why not just give directly to the people who need it. Well, 36 00:02:29,356 --> 00:02:34,116 Speaker 1: our guest, Michael Faye, founded his organization Give Directly to 37 00:02:34,196 --> 00:02:39,276 Speaker 1: do just that. His organization are currently testing a universal 38 00:02:39,436 --> 00:02:43,596 Speaker 1: basic income in order to try and permanently end extreme 39 00:02:43,676 --> 00:02:47,716 Speaker 1: poverty for thousands of people and Kenya by guaranteeing those 40 00:02:47,756 --> 00:02:52,196 Speaker 1: people an income high enough to meet their basic needs. Now, 41 00:02:52,236 --> 00:02:54,876 Speaker 1: if that works. They're planning to do the same in 42 00:02:54,996 --> 00:02:59,196 Speaker 1: other regions. We'll see the initiative launched in November twenty 43 00:02:59,436 --> 00:03:02,276 Speaker 1: seventeen and it's going along now. It's set to run 44 00:03:02,356 --> 00:03:05,236 Speaker 1: for twelve years. Let's hear all about it now in 45 00:03:05,236 --> 00:03:10,476 Speaker 1: this conversation with Jacob Weisberg. So, Michael's the nature of 46 00:03:10,476 --> 00:03:15,716 Speaker 1: this problem is the problem? Extreme poverty? Is at all poverty? 47 00:03:16,556 --> 00:03:18,796 Speaker 1: What should we be thinking about trying to solve here? 48 00:03:19,996 --> 00:03:22,276 Speaker 1: I think there are all sorts of these problems. There's 49 00:03:22,316 --> 00:03:24,516 Speaker 1: extreme poverty. There are people that are poor because they 50 00:03:24,516 --> 00:03:29,076 Speaker 1: were born in extremely poor location. There are people Interack 51 00:03:29,196 --> 00:03:32,596 Speaker 1: that are suffering post genocide and trying to rebuild lives. 52 00:03:32,956 --> 00:03:35,476 Speaker 1: And then I was recently in Uganda in a refugee 53 00:03:35,476 --> 00:03:38,116 Speaker 1: camp where people have been for thirty years and don't 54 00:03:38,156 --> 00:03:40,996 Speaker 1: have the capital to really build and move on in 55 00:03:41,036 --> 00:03:44,836 Speaker 1: their lives. And why is this the problem you're focusing on. 56 00:03:44,876 --> 00:03:47,556 Speaker 1: I know your background is economics. How do you find 57 00:03:47,596 --> 00:03:51,956 Speaker 1: yourself running an international aid organization. We slowly tripped into it. 58 00:03:51,996 --> 00:03:54,996 Speaker 1: So I did my PhD in development and at that 59 00:03:55,036 --> 00:03:57,556 Speaker 1: time we were studying what worked and didn't work in 60 00:03:57,636 --> 00:04:01,196 Speaker 1: poverty alleviation, and the reality was that before the early 61 00:04:01,236 --> 00:04:04,116 Speaker 1: two thousands, this isn't something we spent much time on. 62 00:04:04,596 --> 00:04:07,396 Speaker 1: If you are a pharmaceutical company, you might test your drug, 63 00:04:07,876 --> 00:04:11,116 Speaker 1: but if you're a GEO or an aid organization, you 64 00:04:11,116 --> 00:04:15,436 Speaker 1: weren't necessarily testing whether what you did was effective. What 65 00:04:15,436 --> 00:04:17,036 Speaker 1: we learned in that period is that a lot of 66 00:04:17,036 --> 00:04:19,196 Speaker 1: what we were doing was not as effective as we 67 00:04:19,196 --> 00:04:21,996 Speaker 1: had hoped, and this simple idea of just giving people 68 00:04:22,076 --> 00:04:25,556 Speaker 1: cash actually worked pretty well. Where does that idea come from? 69 00:04:25,596 --> 00:04:28,476 Speaker 1: I mean, the idea that you replace something complicated with 70 00:04:28,516 --> 00:04:31,876 Speaker 1: something simple. When it comes to internationally, it's the simplest idea, 71 00:04:31,876 --> 00:04:33,676 Speaker 1: and we should take no credit for it. I think 72 00:04:33,676 --> 00:04:35,196 Speaker 1: it's been an idea that's been out there for a 73 00:04:35,276 --> 00:04:39,236 Speaker 1: very long time, but it's unsettling. We think people will 74 00:04:39,276 --> 00:04:42,396 Speaker 1: waste the money, we think they'll stop working, and that's 75 00:04:42,396 --> 00:04:44,396 Speaker 1: just not what the evidence tells us. So there was 76 00:04:44,436 --> 00:04:47,516 Speaker 1: a moral judgment at the heart of the old aid 77 00:04:47,596 --> 00:04:51,036 Speaker 1: system that you have to give people. You have to 78 00:04:51,036 --> 00:04:53,876 Speaker 1: give money to deserving people, or you have to give 79 00:04:53,916 --> 00:04:57,796 Speaker 1: them specific kinds of help, food, clothing that won't be 80 00:04:57,836 --> 00:05:02,556 Speaker 1: wasted or lead to moral squal or whatever it is. 81 00:05:02,956 --> 00:05:04,516 Speaker 1: I think that's right, and I think there's a certain 82 00:05:04,556 --> 00:05:07,476 Speaker 1: implicit paternalism and a lot of what we were doing 83 00:05:07,756 --> 00:05:10,196 Speaker 1: we thought, oh, we'll give this person the goat, we said, 84 00:05:10,236 --> 00:05:12,116 Speaker 1: goat is great for their life, or we'll give them 85 00:05:12,116 --> 00:05:16,756 Speaker 1: this specific nutrition intervention. And as you reflect upon that, 86 00:05:17,156 --> 00:05:19,596 Speaker 1: I think it's important to ask why why do we 87 00:05:19,636 --> 00:05:22,116 Speaker 1: think this person is going to waste money? I certainly 88 00:05:22,156 --> 00:05:25,076 Speaker 1: don't want to receive my salary in bags of rice 89 00:05:25,196 --> 00:05:27,716 Speaker 1: or corn. I'd like salary in dollars, so I get 90 00:05:27,716 --> 00:05:30,316 Speaker 1: to choose. But why do we treat other people differently? 91 00:05:30,756 --> 00:05:35,956 Speaker 1: So is your premise that giving cash instead is more 92 00:05:37,036 --> 00:05:40,436 Speaker 1: just and fair, or that it's more effective or both. 93 00:05:41,196 --> 00:05:43,676 Speaker 1: I think it's a bit of all. I think we 94 00:05:43,716 --> 00:05:46,636 Speaker 1: should measure the impact of cash and compare it to 95 00:05:46,716 --> 00:05:51,876 Speaker 1: other things. Us the aid sector philanthropists should have to 96 00:05:51,916 --> 00:05:54,956 Speaker 1: make the argument to a recipient that we're doing more 97 00:05:55,036 --> 00:05:58,596 Speaker 1: good with the money than they could themselves. And I 98 00:05:58,636 --> 00:06:00,996 Speaker 1: think that's the minimum bar we should meet, and we 99 00:06:01,076 --> 00:06:03,836 Speaker 1: often talk about that being the index fund or the 100 00:06:03,876 --> 00:06:07,116 Speaker 1: benchmark for other interventions. But I also think there's an 101 00:06:07,116 --> 00:06:11,796 Speaker 1: element about dignity choice. And when you talk to the recipients, 102 00:06:11,796 --> 00:06:13,916 Speaker 1: they'll tell you that. They'll say this is not a 103 00:06:13,996 --> 00:06:16,596 Speaker 1: large village. There's actually one village in Library with only 104 00:06:16,636 --> 00:06:20,596 Speaker 1: seven people. But we all have different needs. I may 105 00:06:20,636 --> 00:06:23,116 Speaker 1: need to send my child to secondary school and pay 106 00:06:23,156 --> 00:06:25,756 Speaker 1: school fees. Someone else may want to feed their newborn, 107 00:06:25,956 --> 00:06:27,836 Speaker 1: and somebody else may want to buy a motorbike to 108 00:06:27,876 --> 00:06:31,836 Speaker 1: start a business. It's impossible to know that from here. 109 00:06:32,436 --> 00:06:34,076 Speaker 1: But the people who do know their needs are the 110 00:06:34,076 --> 00:06:38,276 Speaker 1: people themselves now, being a group of academic economists who 111 00:06:38,356 --> 00:06:41,636 Speaker 1: started this organization, I think you did something unusual as 112 00:06:41,676 --> 00:06:44,836 Speaker 1: you set it up as a kind of study. Yeah, 113 00:06:44,836 --> 00:06:47,756 Speaker 1: so we started with an evaluation, so before we got going, 114 00:06:48,236 --> 00:06:50,796 Speaker 1: we knew that there are other cash evaluations that cash 115 00:06:50,836 --> 00:06:54,116 Speaker 1: transfers were an effective means of helping people, but we 116 00:06:54,156 --> 00:06:56,716 Speaker 1: wanted to make sure that we give directly we're also 117 00:06:56,796 --> 00:07:00,156 Speaker 1: as effective. So we did that before even launching publicly. 118 00:07:00,676 --> 00:07:03,116 Speaker 1: And what have you learned from the studies you've done? 119 00:07:03,156 --> 00:07:04,956 Speaker 1: I guess I mean talk a little bit about that. 120 00:07:04,996 --> 00:07:08,236 Speaker 1: I know you started first in Kenya and have expanded 121 00:07:08,236 --> 00:07:11,396 Speaker 1: in East Africa now elsewhere. But what are the oldest 122 00:07:11,436 --> 00:07:14,516 Speaker 1: experiments in cash transfers now? Tell you Yeah, and we're 123 00:07:14,516 --> 00:07:17,076 Speaker 1: not even the oldest. Before us, there are cash programs 124 00:07:17,076 --> 00:07:20,396 Speaker 1: in Brazil, Mexico, many places. So let's start with what 125 00:07:20,436 --> 00:07:23,516 Speaker 1: it's not and what everybody's worried about. People do not 126 00:07:23,676 --> 00:07:26,556 Speaker 1: spend it on alcohol and drugs, and they do not 127 00:07:27,156 --> 00:07:30,756 Speaker 1: stop working. And I think that's been shown across contexts. 128 00:07:30,956 --> 00:07:33,036 Speaker 1: What people do do is they spend the money well, 129 00:07:33,596 --> 00:07:36,676 Speaker 1: and how they spend it is really context specific. So 130 00:07:36,756 --> 00:07:41,356 Speaker 1: you'll see projects that gave money to grandparents in South 131 00:07:41,396 --> 00:07:44,076 Speaker 1: Africa and that seems to have gone largely towards nutrition. 132 00:07:44,556 --> 00:07:48,396 Speaker 1: You'll see other programs where business income increased. You'll see 133 00:07:48,436 --> 00:07:52,396 Speaker 1: programs that during the cash transfer program itself you actually 134 00:07:52,476 --> 00:07:56,436 Speaker 1: saw a fall in HIV and STD prevalence. The range 135 00:07:56,516 --> 00:07:59,556 Speaker 1: is wide, but that's sort of the point of cash 136 00:07:59,756 --> 00:08:02,556 Speaker 1: is that people have different needs and we should expect 137 00:08:02,636 --> 00:08:05,596 Speaker 1: the outcomes to be based on the specific needs. Now, 138 00:08:05,596 --> 00:08:07,796 Speaker 1: that's the idea of cash transfers, which is that if 139 00:08:07,836 --> 00:08:10,476 Speaker 1: you want to aid, you should give money and not 140 00:08:10,756 --> 00:08:12,956 Speaker 1: bags of rice or a goad. And then there's the 141 00:08:13,036 --> 00:08:16,956 Speaker 1: idea of universal basic income, which is the version of 142 00:08:16,956 --> 00:08:19,156 Speaker 1: that that people are talking about in the developed world 143 00:08:19,196 --> 00:08:23,436 Speaker 1: as well. But your large scale experiments in Africa are 144 00:08:23,476 --> 00:08:27,476 Speaker 1: with UBI universal basic income, right, yeah. So universal basic 145 00:08:27,516 --> 00:08:29,396 Speaker 1: income has come to me in a lot of things 146 00:08:29,876 --> 00:08:32,756 Speaker 1: in the media, and in my view, it's something very specific. 147 00:08:33,036 --> 00:08:35,276 Speaker 1: So it's universal. So you don't go and try to 148 00:08:35,276 --> 00:08:37,516 Speaker 1: find the poorest person in the village. You give it 149 00:08:37,556 --> 00:08:40,116 Speaker 1: to everybody. Everybody in the village, everybody in the village. 150 00:08:40,116 --> 00:08:42,316 Speaker 1: It could be everybody in the country, depending on how 151 00:08:42,356 --> 00:08:45,076 Speaker 1: broad your scope. It's basic so it's not a large 152 00:08:45,076 --> 00:08:47,556 Speaker 1: amount of money. It's a small enough amount of money 153 00:08:47,556 --> 00:08:49,716 Speaker 1: that you can get by. So in the case of Kenya, 154 00:08:49,716 --> 00:08:52,316 Speaker 1: we're giving seventy five cents a day, which is the 155 00:08:52,316 --> 00:08:55,196 Speaker 1: food poverty line, and then it's an income, so it's 156 00:08:55,236 --> 00:08:57,076 Speaker 1: over a long period of time. This isn't a one 157 00:08:57,076 --> 00:09:01,636 Speaker 1: time transfer or not. We're actually doing the first long 158 00:09:01,756 --> 00:09:06,156 Speaker 1: term universal basic income that's ever been done anywhere. That's 159 00:09:06,156 --> 00:09:08,396 Speaker 1: in Kenya, and people will be getting money for twelve years. 160 00:09:08,916 --> 00:09:13,196 Speaker 1: Tell me what's happened in one of these Kenyon villages 161 00:09:13,356 --> 00:09:17,676 Speaker 1: where you're conducting this experiment with universal basic income, I mean, 162 00:09:17,796 --> 00:09:20,196 Speaker 1: how things change? What is it like? Yeah, so I 163 00:09:20,196 --> 00:09:22,156 Speaker 1: can give you the anecdotes, I can't give you the 164 00:09:22,156 --> 00:09:25,276 Speaker 1: evidence quite yet. We're doing the evaluation and that hasn't 165 00:09:25,276 --> 00:09:29,076 Speaker 1: come out yet, but adotally it's incredibly interesting. So I 166 00:09:29,116 --> 00:09:32,156 Speaker 1: think you see many of the kind of standard spending decisions, 167 00:09:32,196 --> 00:09:35,196 Speaker 1: whether it's on school fees or food or a pair 168 00:09:35,236 --> 00:09:37,556 Speaker 1: of houses that you might see elsewhere. But I think 169 00:09:37,596 --> 00:09:40,716 Speaker 1: there's a social element of the universality that makes it 170 00:09:40,756 --> 00:09:43,276 Speaker 1: a bit different than some of the other programs. And 171 00:09:43,316 --> 00:09:46,636 Speaker 1: I think a recent recipients said it best when he said, look, 172 00:09:46,676 --> 00:09:51,276 Speaker 1: before Universal Basic Income, there was rich and poor in 173 00:09:51,356 --> 00:09:55,676 Speaker 1: the village. Now we're all Universal Basic Income recipients. We 174 00:09:55,716 --> 00:09:58,436 Speaker 1: can talk about the twenty two dollars a month that 175 00:09:58,476 --> 00:10:01,356 Speaker 1: we're receiving as a community, and we can have that 176 00:10:01,436 --> 00:10:04,316 Speaker 1: conversation openly in a way that we wouldn't talk about 177 00:10:04,316 --> 00:10:07,596 Speaker 1: our investments or funding otherwise. The second thing you see 178 00:10:07,636 --> 00:10:09,636 Speaker 1: is you actually see a pooling of resource. Is because 179 00:10:09,636 --> 00:10:12,436 Speaker 1: of this, you see groups of ten people that will 180 00:10:12,476 --> 00:10:14,996 Speaker 1: actually start lending to each other. So each month, one 181 00:10:15,036 --> 00:10:17,356 Speaker 1: person out of that group will take all the money 182 00:10:17,356 --> 00:10:19,276 Speaker 1: so that they can make an investment, and the next 183 00:10:19,316 --> 00:10:22,596 Speaker 1: month you'll see someone else. And then you see other 184 00:10:22,676 --> 00:10:25,396 Speaker 1: pro social behaviors. So I was in the house of 185 00:10:25,436 --> 00:10:27,836 Speaker 1: a village elder and she said, you know what's really 186 00:10:27,876 --> 00:10:31,236 Speaker 1: amazing one of my jobs is to break up marital disputes, 187 00:10:31,956 --> 00:10:35,156 Speaker 1: and I usually have two to three marital disputes a 188 00:10:35,196 --> 00:10:38,276 Speaker 1: month that I need to intervene. I haven't had one 189 00:10:38,676 --> 00:10:41,716 Speaker 1: in four and a half months. And you give to 190 00:10:42,036 --> 00:10:46,956 Speaker 1: every adult in the village, So in a family, husband wife, 191 00:10:47,476 --> 00:10:49,996 Speaker 1: not the children obviously that they get a larger grant 192 00:10:49,996 --> 00:10:52,476 Speaker 1: depending on how many children they have. No so the 193 00:10:52,556 --> 00:10:55,356 Speaker 1: children will get if they're eighteen and above. So once 194 00:10:55,396 --> 00:10:57,756 Speaker 1: they're a team, they'll start receiving basic income as well. 195 00:10:58,156 --> 00:11:00,316 Speaker 1: But it's at the individual level. And as you say, 196 00:11:00,356 --> 00:11:02,636 Speaker 1: the results aren't in and I know you have kind 197 00:11:02,636 --> 00:11:06,356 Speaker 1: of control villages where you're not doing this, But what 198 00:11:06,396 --> 00:11:09,796 Speaker 1: do you hope to see from this experiment? What do 199 00:11:09,796 --> 00:11:13,156 Speaker 1: you hope it will show. The beauty of cash is 200 00:11:13,196 --> 00:11:16,036 Speaker 1: that where agnostic, which is I don't have a preference 201 00:11:16,396 --> 00:11:19,476 Speaker 1: for what a recipient spends money on. And that's different 202 00:11:19,716 --> 00:11:22,356 Speaker 1: than a lot of how we've historically thought about aid 203 00:11:22,476 --> 00:11:26,236 Speaker 1: and structured the sector. So some organizations might have a 204 00:11:26,276 --> 00:11:31,156 Speaker 1: mandate for shelter for food security for children, in which 205 00:11:31,196 --> 00:11:34,316 Speaker 1: case the organization would hope that they'd see a food 206 00:11:34,316 --> 00:11:38,716 Speaker 1: security outcome or an education outcome. I don't have specific hopes. 207 00:11:39,516 --> 00:11:42,316 Speaker 1: I hope this improves people's lives and that you don't 208 00:11:42,356 --> 00:11:44,156 Speaker 1: see any of the things that you might worry about. 209 00:11:44,756 --> 00:11:47,836 Speaker 1: But given just the kind of magnitude of evidence on 210 00:11:47,916 --> 00:11:51,076 Speaker 1: cash at this point, I'm not particularly concerned about that. 211 00:11:51,836 --> 00:11:54,556 Speaker 1: But if you're giving someone a thousand dollars a year, 212 00:11:54,636 --> 00:11:56,596 Speaker 1: or you'd like to see that they are in some 213 00:11:56,636 --> 00:11:59,476 Speaker 1: sense a thousand dollars a year better off, well they 214 00:11:59,476 --> 00:12:02,276 Speaker 1: should be at least a thousand dollars better off, and 215 00:12:02,316 --> 00:12:03,956 Speaker 1: that's sort of it. They will be at least a 216 00:12:03,996 --> 00:12:07,076 Speaker 1: thousand dollars better off. Maybe they invest it in a 217 00:12:07,156 --> 00:12:10,236 Speaker 1: motorbike and they start working, so that compounds over time. 218 00:12:10,916 --> 00:12:14,436 Speaker 1: And one element of cash that people often forget is 219 00:12:14,476 --> 00:12:17,596 Speaker 1: that cash is very pro market. So if I get 220 00:12:17,636 --> 00:12:20,516 Speaker 1: a thousand dollars, I need to spend that thousand dollars. 221 00:12:20,996 --> 00:12:23,596 Speaker 1: So if I spend it on improving my home, I 222 00:12:23,716 --> 00:12:25,756 Speaker 1: might actually be paying someone in the next village to 223 00:12:25,796 --> 00:12:28,636 Speaker 1: do that, and that person may spend the money. And 224 00:12:28,676 --> 00:12:32,076 Speaker 1: there is a paper that is forthcoming that suggests that 225 00:12:32,116 --> 00:12:35,636 Speaker 1: there's a strong positive impact on even those that haven't 226 00:12:35,636 --> 00:12:38,156 Speaker 1: received the cash. It sounds obvious. It's the point that 227 00:12:38,316 --> 00:12:40,596 Speaker 1: you give a thousand dollars and someone gets a thousand 228 00:12:40,596 --> 00:12:43,996 Speaker 1: dollars of benefit. But the benchmark isn't that. The benchmark 229 00:12:44,116 --> 00:12:47,236 Speaker 1: is a thousand dollars spent on aid in the conventional 230 00:12:47,276 --> 00:12:51,076 Speaker 1: aid world doesn't necessarily produce anything like a thousand dollars 231 00:12:51,116 --> 00:12:53,356 Speaker 1: in benefit. In fact, a lot of it is lost 232 00:12:53,476 --> 00:12:56,876 Speaker 1: in the friction and transaction costs of delivering it. It's 233 00:12:56,876 --> 00:12:59,516 Speaker 1: exactly right. It's back to basics. Even that basic question 234 00:12:59,556 --> 00:13:03,116 Speaker 1: of if you start with a thousand dollars on another program, 235 00:13:03,436 --> 00:13:05,716 Speaker 1: how much value winds up in the hands of recipient 236 00:13:06,356 --> 00:13:08,316 Speaker 1: is a question that we really just don't know the 237 00:13:08,356 --> 00:13:12,036 Speaker 1: answer to as a sector. And the other aspect of this, 238 00:13:12,276 --> 00:13:14,516 Speaker 1: I always think of this story. There's a program that 239 00:13:14,596 --> 00:13:18,036 Speaker 1: gave coupons to buy goats, and this was in Pakistan, 240 00:13:18,436 --> 00:13:20,756 Speaker 1: and you take your coupon to the business owner and 241 00:13:20,836 --> 00:13:22,916 Speaker 1: you'd give him the coupon and he'd give you a goat. 242 00:13:23,596 --> 00:13:25,916 Speaker 1: And they sent monitors to evaluate the program, and the 243 00:13:25,956 --> 00:13:29,676 Speaker 1: monitors sitting outside and every person comes coupon goat, coupon goat, 244 00:13:29,676 --> 00:13:32,556 Speaker 1: and it looks great. At some point he says, Tom, 245 00:13:32,716 --> 00:13:35,436 Speaker 1: you know, all the goats just look so so similar 246 00:13:35,996 --> 00:13:39,516 Speaker 1: in this market, and walk around the back and realize 247 00:13:39,516 --> 00:13:41,996 Speaker 1: that after people would get their goat, they just sell 248 00:13:42,036 --> 00:13:44,516 Speaker 1: it back to the shopkeeper. There is one goat in 249 00:13:44,556 --> 00:13:47,196 Speaker 1: the village. And what you forget is that when you 250 00:13:47,236 --> 00:13:50,436 Speaker 1: give people things that they don't want or don't need, 251 00:13:51,076 --> 00:13:53,276 Speaker 1: they can just sell them to buy what they do 252 00:13:53,356 --> 00:13:55,916 Speaker 1: want and do need. And now we spend all this 253 00:13:56,036 --> 00:13:59,756 Speaker 1: time designing the sophisticated program to get people goats. Everyone 254 00:13:59,796 --> 00:14:02,916 Speaker 1: loves a goat, and everyone's just sold their goat for cash. 255 00:14:03,196 --> 00:14:05,436 Speaker 1: How does it actually work in these villages? Is someone 256 00:14:05,556 --> 00:14:08,316 Speaker 1: handing out piles of cash every month? No, they're doing 257 00:14:08,356 --> 00:14:12,436 Speaker 1: this on their phones mostly, so it surprisingly complicated. The operations. 258 00:14:12,436 --> 00:14:15,476 Speaker 1: It seems simple, but there's a lot of work. So 259 00:14:15,516 --> 00:14:18,596 Speaker 1: we have to go find the people that we want 260 00:14:18,596 --> 00:14:21,756 Speaker 1: to target, look for the extreme poor, validate that they 261 00:14:21,796 --> 00:14:23,956 Speaker 1: are who they say they are, and that we're not 262 00:14:24,036 --> 00:14:27,036 Speaker 1: having people try to game the system. People squatting in houses, 263 00:14:27,316 --> 00:14:29,396 Speaker 1: people cheating, we do all sorts of things. We actually 264 00:14:29,436 --> 00:14:32,556 Speaker 1: pay people to try to cheat our own system. To 265 00:14:32,716 --> 00:14:35,676 Speaker 1: understand how robust it is, you have a view of 266 00:14:35,716 --> 00:14:38,276 Speaker 1: white hat hackers, it's exactly what we have. Yeah, wow, 267 00:14:38,556 --> 00:14:40,516 Speaker 1: And that's a bit of putting the recipient at the center. 268 00:14:40,516 --> 00:14:43,276 Speaker 1: It's how prone to fraud is your system. We also 269 00:14:43,356 --> 00:14:47,156 Speaker 1: do customer satisfaction surveys where you treat it with respect, 270 00:14:47,676 --> 00:14:50,636 Speaker 1: and then we pay people and incentivize them based on it, 271 00:14:50,756 --> 00:14:53,236 Speaker 1: because we want to be treating the recipient as the 272 00:14:53,316 --> 00:14:56,356 Speaker 1: customer and not the donor, even though the donor is paying. 273 00:14:56,596 --> 00:14:58,916 Speaker 1: But how does the Kenyon villager actually get her money? 274 00:14:58,956 --> 00:15:01,196 Speaker 1: Does it show up on her soul phone? Does she 275 00:15:01,276 --> 00:15:03,476 Speaker 1: have them all get a text that says you've received 276 00:15:03,476 --> 00:15:06,956 Speaker 1: a thousand shillings from give directly. They then can take 277 00:15:06,996 --> 00:15:10,116 Speaker 1: that to a local shopkeeper or whomever and exchange that 278 00:15:10,196 --> 00:15:13,516 Speaker 1: for physical cash and then spend the physical cash. So 279 00:15:13,556 --> 00:15:15,676 Speaker 1: this is digital end to end. We can sit here 280 00:15:15,676 --> 00:15:19,676 Speaker 1: in this room and send digital money to someone's phone 281 00:15:19,796 --> 00:15:23,076 Speaker 1: in a Kenyan refugee settlement. I mean they're engaging in 282 00:15:23,116 --> 00:15:26,436 Speaker 1: some cases and transactions that people in the developed world 283 00:15:26,476 --> 00:15:29,916 Speaker 1: don't have access to. Right Is this because they had 284 00:15:29,956 --> 00:15:33,156 Speaker 1: Venmo Before we had Venmo, Well, skip some of the 285 00:15:33,196 --> 00:15:37,036 Speaker 1: technology we had and went straight to what were wells. Yeah, 286 00:15:37,316 --> 00:15:39,876 Speaker 1: which is there was no banking. There was no financial 287 00:15:39,876 --> 00:15:43,196 Speaker 1: inclusion or digital finance for a large swath of the 288 00:15:43,236 --> 00:15:47,676 Speaker 1: world's population, and now everybody has an ATM and bank 289 00:15:47,956 --> 00:15:51,756 Speaker 1: in their pocket, and that's completely changed what's feasible. So 290 00:15:51,796 --> 00:15:53,716 Speaker 1: if you go back when we started this a decade 291 00:15:53,796 --> 00:15:56,756 Speaker 1: or so ago, you had the evidence that this thing 292 00:15:56,796 --> 00:15:59,956 Speaker 1: we thought was really silly worked and you had the 293 00:15:59,996 --> 00:16:02,996 Speaker 1: technology to actually make it feasible. But it wasn't that simple. 294 00:16:03,076 --> 00:16:04,676 Speaker 1: I am and I know you had to set up 295 00:16:04,796 --> 00:16:10,356 Speaker 1: essentially a separate company to help facilitate these transfers across 296 00:16:10,436 --> 00:16:14,236 Speaker 1: international borders. Right. Yeah, the opportunity of mobile payments is there, 297 00:16:15,316 --> 00:16:18,396 Speaker 1: as is always the case, the execution and operations is 298 00:16:18,436 --> 00:16:20,956 Speaker 1: more challenging than you would like. So we wound up 299 00:16:20,956 --> 00:16:25,156 Speaker 1: setting up Segovia, which is an enterprise payments company that 300 00:16:25,196 --> 00:16:28,316 Speaker 1: was actually recently acquired by Crown Agents Bank. Now cash 301 00:16:28,396 --> 00:16:32,836 Speaker 1: is a bit of a buzzword now in the development world. 302 00:16:32,996 --> 00:16:37,876 Speaker 1: I think institutions and organizations that haven't traditionally been involved 303 00:16:37,916 --> 00:16:40,716 Speaker 1: in cash transfers are now talking about them. Is what 304 00:16:40,756 --> 00:16:42,476 Speaker 1: they want to be doing or part of what they 305 00:16:42,516 --> 00:16:45,236 Speaker 1: want to be doing. What's really happening there? Is it 306 00:16:45,356 --> 00:16:49,356 Speaker 1: your idea catching on or are you antagonistic to a 307 00:16:49,396 --> 00:16:52,556 Speaker 1: lot of the existing aid at infrastructure. We should take 308 00:16:52,596 --> 00:16:54,796 Speaker 1: no credit for the idea. The idea of giving people 309 00:16:54,916 --> 00:16:58,076 Speaker 1: money goes back millennia. So there's been a real shift, 310 00:16:58,596 --> 00:17:01,596 Speaker 1: certainly in the rhetoric and the commitments people are making. 311 00:17:02,116 --> 00:17:05,036 Speaker 1: I think it is going to be hard to move 312 00:17:05,076 --> 00:17:09,836 Speaker 1: this sector. In many ways. Cash fits everywhere. Cash impacts 313 00:17:09,876 --> 00:17:14,196 Speaker 1: all of the objectives people have, nutrition, education, and so on, 314 00:17:14,276 --> 00:17:16,516 Speaker 1: but it also fits nowhere. It may not be the 315 00:17:16,596 --> 00:17:20,796 Speaker 1: single best intervention for a single outcome, and that's something 316 00:17:21,276 --> 00:17:23,796 Speaker 1: that we're going to have to wrestle as a sector. 317 00:17:24,596 --> 00:17:26,836 Speaker 1: The way I think of it is there is a 318 00:17:26,916 --> 00:17:30,236 Speaker 1: lot of capital going to aid one hundred and fifty 319 00:17:30,236 --> 00:17:35,516 Speaker 1: billion dollars of development assistance now. Historically almost all of 320 00:17:35,556 --> 00:17:39,116 Speaker 1: that has been decided by the donor what we spend 321 00:17:39,156 --> 00:17:41,756 Speaker 1: that money on. Now, you may not think one hundred 322 00:17:41,756 --> 00:17:45,516 Speaker 1: percent of it should shift to recipient choice, but I 323 00:17:45,556 --> 00:17:47,596 Speaker 1: think all of us would agree that it should be 324 00:17:47,596 --> 00:17:50,596 Speaker 1: more than zero percent. They should get to vote and 325 00:17:50,756 --> 00:17:55,916 Speaker 1: choose over some fraction of that capital spend. But it 326 00:17:55,956 --> 00:18:00,796 Speaker 1: points to, among other things, a much smaller development infrastructure. 327 00:18:00,836 --> 00:18:03,836 Speaker 1: There are fewer people I imagine, working for gift directly 328 00:18:04,316 --> 00:18:07,716 Speaker 1: than some of the more traditional organizations we're talking about 329 00:18:07,756 --> 00:18:11,236 Speaker 1: that have large numbers of people on the ground involved 330 00:18:11,276 --> 00:18:15,276 Speaker 1: in the delivery of physical aid. Yeah, that may be true. 331 00:18:15,636 --> 00:18:18,916 Speaker 1: Give directly. We have two hundred and fifty or so employees, 332 00:18:18,916 --> 00:18:22,196 Speaker 1: so it's not a small number of employees, and it 333 00:18:22,276 --> 00:18:25,916 Speaker 1: certainly still takes work. But yeah, you'd be spending less 334 00:18:25,916 --> 00:18:29,516 Speaker 1: time making the decisions. I recently heard a story from 335 00:18:29,516 --> 00:18:32,676 Speaker 1: an AID worker that was a recent cash convert, and 336 00:18:32,676 --> 00:18:34,956 Speaker 1: I said, well, what did it. Well, you know, we 337 00:18:34,956 --> 00:18:38,796 Speaker 1: were just spending months and months internally debating what brand 338 00:18:38,836 --> 00:18:42,556 Speaker 1: of food we should be buying for this settlement. We 339 00:18:42,596 --> 00:18:45,996 Speaker 1: don't need to spend months debating. We can give the 340 00:18:46,076 --> 00:18:48,996 Speaker 1: money and let the household decide what brand of food, 341 00:18:49,036 --> 00:18:51,316 Speaker 1: or maybe they don't even want food. Michael, I wanted 342 00:18:51,316 --> 00:18:54,596 Speaker 1: to ask you about disaster relief. I think there were calls, 343 00:18:54,716 --> 00:18:58,236 Speaker 1: especially after the hurricane and flooding in Houston, for some 344 00:18:58,356 --> 00:19:02,476 Speaker 1: kind of direct cash type model to get help to 345 00:19:03,476 --> 00:19:06,836 Speaker 1: victims of the storm faster, and I know you're trying 346 00:19:06,876 --> 00:19:09,636 Speaker 1: to set something like that up. Yeah, we should give 347 00:19:09,796 --> 00:19:12,316 Speaker 1: Felix credit. Felix Salmon wrote an op ed saying we 348 00:19:12,316 --> 00:19:14,996 Speaker 1: need give directly in Houston, and then Felix Salmon, the 349 00:19:15,636 --> 00:19:18,116 Speaker 1: journalist journalists now at Axios, and then we set up 350 00:19:18,156 --> 00:19:22,196 Speaker 1: and did cash transfers in Houston. I think disasters spend 351 00:19:22,316 --> 00:19:25,436 Speaker 1: is off in some of the least efficient spend in 352 00:19:25,476 --> 00:19:28,156 Speaker 1: the sector that you see. I was in Houston and 353 00:19:28,236 --> 00:19:32,036 Speaker 1: you saw piles of used clothes, piles of water bottles, 354 00:19:32,076 --> 00:19:35,196 Speaker 1: a food truck serving rice and beans. Now that sounds 355 00:19:35,236 --> 00:19:38,596 Speaker 1: great until you realize that the tap is working and 356 00:19:38,596 --> 00:19:42,516 Speaker 1: people can get water from their faucet, that the Walmart 357 00:19:42,556 --> 00:19:46,316 Speaker 1: and other restaurants are open down the street, and that 358 00:19:46,436 --> 00:19:49,436 Speaker 1: what people need is different. Some people need to repair 359 00:19:49,476 --> 00:19:51,316 Speaker 1: their car because it was flooded and they can't get 360 00:19:51,356 --> 00:19:54,516 Speaker 1: to work. Some people need to rebuild their house. So 361 00:19:54,556 --> 00:19:56,596 Speaker 1: we did cash transfers in Houston. What we're going to 362 00:19:56,636 --> 00:20:00,756 Speaker 1: do next and just announced the partnership with Google is 363 00:20:00,756 --> 00:20:04,556 Speaker 1: actually something called prepositioning. It's when we raise the money 364 00:20:04,596 --> 00:20:08,396 Speaker 1: on already in advance of the disaster, and that'll allow 365 00:20:08,476 --> 00:20:10,876 Speaker 1: us to be on the around immediately following the disaster. 366 00:20:11,116 --> 00:20:13,716 Speaker 1: And how will that work? I mean if Houston happened, 367 00:20:13,716 --> 00:20:16,276 Speaker 1: and now, how would you determine who gets aid and 368 00:20:16,356 --> 00:20:18,716 Speaker 1: how would you be delivering it? Yeah, So it's a 369 00:20:18,716 --> 00:20:22,996 Speaker 1: combination of damage from the storm and poverty levels, so 370 00:20:23,036 --> 00:20:26,716 Speaker 1: you want to find high damage obviously and those most 371 00:20:26,756 --> 00:20:30,156 Speaker 1: in need. The way we've delivered it in the US 372 00:20:30,396 --> 00:20:33,676 Speaker 1: was through debit cards, so we didn't use mobile money 373 00:20:33,716 --> 00:20:36,636 Speaker 1: in the US, and going forward will likely use something 374 00:20:36,676 --> 00:20:40,076 Speaker 1: called hyperwallet, which is just a very flexible card product. 375 00:20:40,676 --> 00:20:43,276 Speaker 1: So people get essentially a gift card that they can 376 00:20:43,436 --> 00:20:46,276 Speaker 1: use to anywhere. Feel what's getting the roof fixed or 377 00:20:46,476 --> 00:20:49,676 Speaker 1: whatever whatever. They It's essentially cash, but it's stored on 378 00:20:49,676 --> 00:20:52,676 Speaker 1: a card. But how do you determine who gets how much? 379 00:20:52,796 --> 00:20:55,196 Speaker 1: Is it a function of how much you have divided 380 00:20:55,276 --> 00:20:59,636 Speaker 1: by how many qualified victims or recipients. So I think 381 00:20:59,636 --> 00:21:02,196 Speaker 1: it's one of the hardest questions, how much versus how 382 00:21:02,196 --> 00:21:05,396 Speaker 1: many people. I think historically the sector has always opted 383 00:21:05,396 --> 00:21:07,916 Speaker 1: for a high number of people, and I think we've 384 00:21:07,956 --> 00:21:10,476 Speaker 1: likely gone too far where we want the headline we've 385 00:21:10,516 --> 00:21:13,076 Speaker 1: served a million people. Well, if we've given a million 386 00:21:13,076 --> 00:21:15,956 Speaker 1: people a dollar, we probably haven't done much good. So 387 00:21:15,996 --> 00:21:18,916 Speaker 1: we try to be thoughtful. We try to price how 388 00:21:18,996 --> 00:21:21,756 Speaker 1: much we give to what the investments are that people 389 00:21:21,796 --> 00:21:24,036 Speaker 1: need to make. So what would a car repair look like? 390 00:21:24,356 --> 00:21:26,276 Speaker 1: What would it look like to pay rent for a year. 391 00:21:26,636 --> 00:21:30,076 Speaker 1: Those sorts of things. People react emotionally, which is on 392 00:21:30,116 --> 00:21:34,436 Speaker 1: the one hand, wonderful and understandable, but can produce very 393 00:21:34,876 --> 00:21:39,276 Speaker 1: irrational results. I think people came forward and gave over 394 00:21:39,356 --> 00:21:43,476 Speaker 1: a billion dollars to restore Notre Dame after the fire, 395 00:21:43,796 --> 00:21:46,516 Speaker 1: and probably none of that money is needed because the 396 00:21:46,516 --> 00:21:49,756 Speaker 1: French government would ultimately pay for it. But whether it's 397 00:21:49,796 --> 00:21:52,436 Speaker 1: needed or not, it's probably more than it's needed, and 398 00:21:52,516 --> 00:21:55,556 Speaker 1: certainly money that would be better spent elsewhere. Whether it's 399 00:21:55,596 --> 00:21:58,076 Speaker 1: more or less, I don't know in the specific examples. 400 00:21:58,076 --> 00:22:00,876 Speaker 1: I think the timing is what's really flawed, which is 401 00:22:00,916 --> 00:22:03,476 Speaker 1: you look at some of these disaster funds and they 402 00:22:03,516 --> 00:22:07,036 Speaker 1: still haven't spent the money years and years after the disaster. 403 00:22:08,316 --> 00:22:12,436 Speaker 1: That's awful. People need money immediately to start rebuilding their lives. 404 00:22:13,116 --> 00:22:15,796 Speaker 1: Cash actually provides an avenue to do that pretty quickly. 405 00:22:16,316 --> 00:22:18,236 Speaker 1: We can get that cash out quickly. We don't need 406 00:22:18,276 --> 00:22:21,436 Speaker 1: to wait years to pick a grant recipient who may 407 00:22:21,476 --> 00:22:23,356 Speaker 1: repair a building or whatnot. We can just give it 408 00:22:23,396 --> 00:22:25,796 Speaker 1: to the individuals. I wanted to come back to the 409 00:22:25,916 --> 00:22:30,436 Speaker 1: universal basic income idea and ask you about it here 410 00:22:30,436 --> 00:22:33,636 Speaker 1: in the United states where it's there are some experiments 411 00:22:33,676 --> 00:22:36,436 Speaker 1: taking place, and there's also a lot of controversy around 412 00:22:36,476 --> 00:22:40,476 Speaker 1: the idea, partly because some people see it as a 413 00:22:40,596 --> 00:22:44,196 Speaker 1: kind of answer to the loss of jobs through to 414 00:22:44,636 --> 00:22:48,156 Speaker 1: robotics and AI. Are you involved in that debate at all? 415 00:22:48,196 --> 00:22:49,516 Speaker 1: What do you think about it? I think it's a 416 00:22:49,516 --> 00:22:53,836 Speaker 1: complicated question in the US, and I think how we 417 00:22:53,916 --> 00:22:57,236 Speaker 1: fund a true universal basic income there's a real question 418 00:22:57,276 --> 00:23:01,076 Speaker 1: mark around that. But I think the elements of universal 419 00:23:01,076 --> 00:23:04,596 Speaker 1: basic income I think we can take to current social programs. 420 00:23:05,076 --> 00:23:06,836 Speaker 1: So if you look at some of the poorest people 421 00:23:06,836 --> 00:23:08,916 Speaker 1: in this country, they face some of the highest marginal 422 00:23:09,396 --> 00:23:12,716 Speaker 1: rates because as they earn more money, they lose more benefits, 423 00:23:13,156 --> 00:23:16,076 Speaker 1: in some cases approaching one hundred percent of the money 424 00:23:16,116 --> 00:23:18,276 Speaker 1: they're earning. I think that's a problem that's a real 425 00:23:18,316 --> 00:23:21,236 Speaker 1: disincentive to work. If we could flatten that, make it 426 00:23:21,276 --> 00:23:25,556 Speaker 1: more universal, and remove that disincentive, that's valuable. I think 427 00:23:25,836 --> 00:23:28,516 Speaker 1: food stamps and other programs that may be limiting to 428 00:23:28,636 --> 00:23:31,756 Speaker 1: people and may not be exactly what they need probably 429 00:23:31,796 --> 00:23:34,476 Speaker 1: can be improved. So I think there are the principles 430 00:23:34,476 --> 00:23:36,676 Speaker 1: of universal basic income that we can apply to other 431 00:23:36,716 --> 00:23:39,836 Speaker 1: social programs. While we wait to see what the actual 432 00:23:39,876 --> 00:23:43,116 Speaker 1: impact of a universal basic income is. But you don't 433 00:23:43,156 --> 00:23:45,356 Speaker 1: see it so much as an answer to the problem 434 00:23:45,436 --> 00:23:47,996 Speaker 1: of the loss of the jobs, the decline of work, 435 00:23:48,076 --> 00:23:50,516 Speaker 1: or replacement for work. I think we're going to certainly 436 00:23:50,556 --> 00:23:53,276 Speaker 1: need something if that happens. And one thing I always 437 00:23:53,276 --> 00:23:55,636 Speaker 1: say is I don't know what the likelihood of that 438 00:23:55,676 --> 00:23:58,796 Speaker 1: happening is. I do know with confidence that it's between 439 00:23:58,876 --> 00:24:03,556 Speaker 1: zero and and given that there's some chance that you 440 00:24:03,676 --> 00:24:07,356 Speaker 1: have mass unemployment from automation, we should be starting to 441 00:24:07,396 --> 00:24:10,156 Speaker 1: think about what those solutions are and starting to trial 442 00:24:10,196 --> 00:24:14,156 Speaker 1: them and understand what the implications are unsolvable. We always 443 00:24:14,196 --> 00:24:18,716 Speaker 1: like to ask what people listening can do. In this case, 444 00:24:18,716 --> 00:24:23,556 Speaker 1: it seems pretty simple. It's give cash, right, Give cash, 445 00:24:23,636 --> 00:24:27,476 Speaker 1: I think, learn a bit about what our beneficiaries lives 446 00:24:27,476 --> 00:24:30,236 Speaker 1: are like. Go to live dot give directly dot org, 447 00:24:30,916 --> 00:24:36,196 Speaker 1: which is an unfiltered streaming feed from recipients. Start a 448 00:24:36,236 --> 00:24:40,516 Speaker 1: conversation with friends or family about cash. People love debating 449 00:24:40,956 --> 00:24:42,956 Speaker 1: whether or not giving is a good or bad thing. 450 00:24:43,716 --> 00:24:46,636 Speaker 1: Always looking for really talented people to work at give Directly. 451 00:24:46,676 --> 00:24:49,676 Speaker 1: So there's lots to do. Can you decide when you 452 00:24:49,836 --> 00:24:52,396 Speaker 1: go to the give directly website, whether to give money 453 00:24:52,436 --> 00:24:56,876 Speaker 1: to a village in Kenya or a refugee camp in Uganda. 454 00:24:56,956 --> 00:24:59,636 Speaker 1: I mean, the different programs or places you're involved in 455 00:24:59,676 --> 00:25:02,796 Speaker 1: are all there. So we let people choose which project 456 00:25:02,796 --> 00:25:05,196 Speaker 1: to give to. We don't let people choose which individual 457 00:25:05,956 --> 00:25:08,756 Speaker 1: And it's that's something you've thought about. I'm sure it is. 458 00:25:08,836 --> 00:25:12,716 Speaker 1: But obviously with the more traditional kinds of aids, part 459 00:25:12,716 --> 00:25:14,876 Speaker 1: of the marketing of it and part of the appeal 460 00:25:15,196 --> 00:25:20,276 Speaker 1: is you're helping this person, this child. Here's her picture. Yeah, 461 00:25:20,316 --> 00:25:24,476 Speaker 1: And sometimes that's honest, and sometimes it's less honest. Even 462 00:25:24,556 --> 00:25:27,236 Speaker 1: in the honest cases, I think it's a bit problematic 463 00:25:27,236 --> 00:25:31,436 Speaker 1: because people have a tendency to fund kind of attractive 464 00:25:31,516 --> 00:25:35,116 Speaker 1: people and not the types of people that you necessarily 465 00:25:35,116 --> 00:25:38,716 Speaker 1: design a social program for. So you're in your case, 466 00:25:38,916 --> 00:25:41,676 Speaker 1: you don't see the individuals. You see the play, don't 467 00:25:41,676 --> 00:25:44,756 Speaker 1: see the individuals. We could wind up chasing the attractive 468 00:25:44,756 --> 00:25:47,076 Speaker 1: recipients around ken you to give cash, and that's probably 469 00:25:47,116 --> 00:25:50,596 Speaker 1: a both complicated and bad social policy. To conclude, I 470 00:25:50,596 --> 00:25:52,316 Speaker 1: wonder if you can give me your sense of the 471 00:25:52,356 --> 00:25:56,916 Speaker 1: overall picture. There's another interesting debate going on about extreme poverty. 472 00:25:57,316 --> 00:26:00,716 Speaker 1: There are statistics that show it's gotten dramatically better in 473 00:26:01,116 --> 00:26:05,276 Speaker 1: recent decades. At the same time, it seems in places 474 00:26:05,396 --> 00:26:08,396 Speaker 1: more shocking and worse than ever. Do you think we're 475 00:26:08,436 --> 00:26:11,796 Speaker 1: winning the fight against extreme poverty. We've made a lot 476 00:26:11,796 --> 00:26:15,676 Speaker 1: of progress in extreme poverty. I think it's going to 477 00:26:15,716 --> 00:26:18,356 Speaker 1: be harder going forward because it is concentrated in places 478 00:26:18,356 --> 00:26:21,596 Speaker 1: with conflict weaker states, So it will certainly be harder. 479 00:26:22,116 --> 00:26:23,876 Speaker 1: But as I think about that problem, there are two 480 00:26:23,956 --> 00:26:27,636 Speaker 1: numbers that helped me dimensionalize it. So if you look 481 00:26:27,676 --> 00:26:31,676 Speaker 1: at the poverty gap over the last forty years or so, 482 00:26:31,676 --> 00:26:34,636 Speaker 1: so this is the amount of money that would mathematically 483 00:26:34,676 --> 00:26:37,436 Speaker 1: be required to take every person above poverty. So if 484 00:26:37,436 --> 00:26:39,316 Speaker 1: you're at a dollar and the poverty lines of dollar ninety, 485 00:26:39,356 --> 00:26:42,316 Speaker 1: it's ninety cents for you. So that's been falling, which 486 00:26:42,356 --> 00:26:45,556 Speaker 1: is great news over time, and it's probably somewhere around 487 00:26:45,596 --> 00:26:48,796 Speaker 1: eighty billion today. On the other side is foreign aid, 488 00:26:49,156 --> 00:26:53,076 Speaker 1: how much money we send to extremely poor places, and 489 00:26:53,116 --> 00:26:56,156 Speaker 1: that's been increasing, which is also good news, and stands 490 00:26:56,156 --> 00:26:59,956 Speaker 1: about one hundred and fifty billion today. What happened eight 491 00:27:00,036 --> 00:27:02,356 Speaker 1: years or so ago is those two graphs crossed for 492 00:27:02,396 --> 00:27:05,556 Speaker 1: the first time, which is that there is now at 493 00:27:05,716 --> 00:27:09,556 Speaker 1: double the amount of aid spent that would mathematically be 494 00:27:09,676 --> 00:27:14,036 Speaker 1: required to end extreme poverty via closing the poverty gap, 495 00:27:14,036 --> 00:27:16,076 Speaker 1: And of course there's nuance behind that. Of course, we 496 00:27:16,116 --> 00:27:19,036 Speaker 1: can't just snap our fingers and drop money on those 497 00:27:19,076 --> 00:27:21,876 Speaker 1: that need it most. But just to think about the 498 00:27:21,916 --> 00:27:24,756 Speaker 1: relative dimensions that makes me think that this is very possible. 499 00:27:25,636 --> 00:27:29,276 Speaker 1: Those are fascinating numbers. It suggests that one hundred percent efficiency, 500 00:27:29,356 --> 00:27:33,596 Speaker 1: were it possible, would eliminate extreme poverty if we could 501 00:27:33,596 --> 00:27:36,076 Speaker 1: all do magic and get cash. We can't do magic yet, 502 00:27:36,476 --> 00:27:38,076 Speaker 1: but we can do a whole lot better than we 503 00:27:38,116 --> 00:27:40,116 Speaker 1: did ten years ago at the advent of mobile money, 504 00:27:40,516 --> 00:27:44,996 Speaker 1: new technologies, and we're getting there. Michael, thanks for joining 505 00:27:45,036 --> 00:27:48,676 Speaker 1: us on. Thanks so much. Oh I love to see it. 506 00:27:49,116 --> 00:27:53,156 Speaker 1: As Michael Fay said, the social element of the universality 507 00:27:53,396 --> 00:27:56,676 Speaker 1: is really interesting. Here in the US, we're grappling with 508 00:27:56,836 --> 00:28:00,316 Speaker 1: growing inequality. I'm not saying that it's as serious as 509 00:28:00,356 --> 00:28:03,116 Speaker 1: the poverty in the countries Michael works in, but I'm 510 00:28:03,116 --> 00:28:06,516 Speaker 1: saying that there are lessons for us here too. Also, 511 00:28:06,556 --> 00:28:09,436 Speaker 1: he uses the phrase the beauty of cash. I just 512 00:28:09,436 --> 00:28:11,956 Speaker 1: think it's such a good tattoo idea. Don't you like, 513 00:28:12,036 --> 00:28:14,076 Speaker 1: you would have to have small print too, Stating your 514 00:28:14,116 --> 00:28:17,076 Speaker 1: tattoo is an anti poverty measure, but that only makes 515 00:28:17,076 --> 00:28:22,396 Speaker 1: it more cool. Solvable is a collaboration between Pushkin Industries 516 00:28:22,436 --> 00:28:26,916 Speaker 1: and the Rockefella Foundation, with production by Laura Hyde, Hester Kant, 517 00:28:26,996 --> 00:28:30,756 Speaker 1: Laura Sheeter, and Ruth Barnes from Chalk and Blade. Pushkin's 518 00:28:30,756 --> 00:28:35,716 Speaker 1: executive producer is Neia LaBelle, Research by Sheer, Vincent, engineering 519 00:28:35,756 --> 00:28:39,476 Speaker 1: by Jason Gambrel and the great Folks at GSI Studios. 520 00:28:39,956 --> 00:28:43,636 Speaker 1: Original music composed by Pascal Wise and special thanks to 521 00:28:43,876 --> 00:28:48,956 Speaker 1: Maggie Taylor, Heather Fine, Julia Barton, Carli Mgliori, Jacob Weisberg, 522 00:28:48,996 --> 00:28:52,556 Speaker 1: and Malcolm Gladwell. You can learn more about solving today's 523 00:28:52,596 --> 00:28:58,236 Speaker 1: biggest problems at Rockefella Foundation dot org, slash Solvable. I'm 524 00:28:58,276 --> 00:29:00,196 Speaker 1: Mave Higgins, Now got solve It.