Accelerating Disaster Response with GiveDirectly's Nick Allardice - Ep. 287

0:10Welcome to the NVIDIA AI podcast. I'm Noah Kravitz. Our guest is Nick Allardyce. Nick is president and CEO of GiveDirectly, a global platform that enables donors to send money directly to people who need it most. He's also the former CEO of Change.org, the online civic action platform used by hundreds of millions of people worldwide. Nick's here to talk about his work at the intersection of global poverty, technology, and philanthropy, and how GiveDirectly is using AI in disaster relief and other humanitarian efforts. Nick, welcome to the pod. Thanks so much for taking the time to join. Thanks for having me.

0:45So maybe we could start with a little bit of background for listeners who might not be familiar with GiveDirectly about the organization. I'd love to also ask you about your journey through working with technology and platforms and social movements and all of the intersection points along that path. So I'll leave it to you if you want to start with GiveDirectly or if you want to start with your own background and work into it. Yeah, happy to start with a little bit of my own background. Both my parents were social workers. I think that's a bit where I got my values from. Right. And I think I really had this sense of just extraordinary luck, you know, that because of just the accident of where I was born, I had access to education, to healthcare, to security, to opportunity.

1:30And I just was always just incredibly grateful for that. And so because of my parents, I think I had this sense of service that I wanted to give back. And I started volunteering at nonprofits. And I wanted to work on the biggest, most urgent problems that humanity faced. Sure. And I found a couple of things when I started doing that. I was definitely inspired by the passion, the care, the dedication that I found from people who were working in those spaces. But I also honestly was a little bit frustrated and disappointed. I found all these like small piecemeal solutions that did good, yes, but didn't have like a meaningful pathway to scale.

2:08I found a lot of bureaucratic inertia that meant many weren't moving with the urgency that I certainly felt that these kind of problems deserved. And I found a lot of top down, I think sometimes pretty paternalistic solutions that were kind of based on feelings and feeling good about what we were doing rather than data about what was actually working. Okay. And so because of all of that, I found my way into tech. building software that empowered people to solve their own problems and then scaling that to hundreds of millions of users. And I kind of became convinced that we could make extraordinary progress on the most important problems in the world simply by equipping people with the resources and technology they needed to solve their own problems rather than us solving it for them.

2:52And so along the way, definitely got obsessed with what it takes to build the organizations, the business models, the technology, et cetera, that enables like scale to change. But that's very much how I got to where I am today. And where did you grow up? I grew up in rural Victoria in Australia, a small town called Bendigo, a couple hours north of Melbourne. Okay. And so were you in Australia through this kind of formative time of starting to volunteer and experiencing everything you just talked about with, you know, ambition, meeting what happens when humans try to organize themselves? Initially in Australia, yes.

3:28But then as I started kind of working in the space, I definitely was spending time in different parts of Asia in particular, working across places like Indonesia and Thailand and supported some work in East Timor and places like that. Right, okay. And so how did this lead to Change.org? Yeah, I mean, I had this experience when I started volunteering of working on a political campaign that was aiming to persuade the Australian government to increase the quality and quantity of its international development of its aid program. And it ended up being successful beyond our imaginations. The Australian government committed the next$3 billion to Australia's aid program as a result.

4:11And I had this experience of being like, wow, policy and politics is this extraordinary scalable lever. And I really wondered, like, how do we take that even further? How do we enable anyone, anywhere to kind of be part of and drive that type of change. And so I joined ChangeRov very, very early. You know, a handful of employees. I was one of the first employees outside of the US. What year or roughly what year? This was around 2011. Okay. And then over the course of the next decade, went through all of the ups and downs of the kind of normal startup experiences. Sure. We kind of grew the team significantly, grew to hundreds of millions of users, but along the way, like the business model failed and we had to kind of totally rebuild the technology and the competitive landscape was changing all around us.

4:56And so, you know, I started more on the go-to-market side of things, working on PR and campaigns and things like that. But then I ended up moving to technology and product and engineering for several years. And then I eventually ended up as CEO as well. Was your tech background, your skill set, to put it that way, did you study technology, self-taught, kind of pick it up along the way as you were working? And, you know, I need to build a platform that can do this. I'm going to figure out how to do it. What's been your path to building technology skills? Yeah, I was very kind of self-taught in an entrepreneurial sense.

5:30A number of the things that I worked on earlier, I think I was kind of coming of age, I guess doing this type of work in the late 2000s. And so starting to see what was possible with technology and playing around with it a lot myself, building a bunch of software. And so that part of it was self-taught. At Change.org, you know, I originally took over running our product and engineering teams at a moment of crisis in the organization when we didn't have anyone else to do it. And I was leading another team in the organization. And I was lucky enough to have a bunch of mentors around me who had gone through the entrepreneurial experience and scaled technology several times and kind of learned a lot on the job and honestly just loved it.

6:13And so I ended up just getting obsessed with both the processes and the technology and really, yeah, I just love it. Yeah, fantastic. When did you leave Change.org? How did that come about? It left in 2023. Okay. And the organization had grown a lot and I think was definitely, you know, we'd achieved profitability as an organization. We made a big transition as a platform that initially started out as a social benefit company, raised a bunch of money from investors, scaled a lot. And then we actually transitioned into being the largest nonprofit-owned technology platform to support social change at scale.

6:54And soon after that, it was like the time was right. Right. And so GiveDirectly, let's talk about that. In a nutshell, what does GiveDirectly do? How has it started? And, you know, I'm very curious to ask kind of the, there's a bad pun about the million dollar question, but, you know, how you landed on the model of donors giving directly to the people. Yeah. So GiveDirectly sends cash digitally to people in poverty and crisis and then studies what happens. Right. And so you can think of GiveDirectly as a little bit like a cross between a fintech company, a humanitarian nonprofit and an economics research institute.

7:32GiveDirectly came to be because about 15 years ago, two things happened. First is you have, it's called the mobile money revolution. Starting in Kenya with M-Pesa, but then increasingly across Africa and then other parts of the world, a huge proportion of the world's population leapfrog the banking system and start transacting purely with mobile money where a SIM card is the same thing as a bank account. And then you can kind of transact. And so you've got an extraordinary number of people who are becoming banked for the first time. And also as a result of that can be reached entirely digitally in a way that they couldn't be reached before.

8:08And so you've got this huge volume of people, many of whom are amongst some of the poorest in the world, who suddenly can be reached digitally. So that's like the first big thing. The second thing that happens is it's like the RCT revolution. RCTs, randomized controlled trials, they're like A-B tests. and smart economists in studying development economics started to figure out ways to rigorously measure the types of aid interventions that we'd been doing for decades based entirely on what we thought would work but not actually being able to measure whether or not it worked. And as they started running these trials, we started learning a number of things.

8:49First, a lot of what we thought worked didn't. Huge bummer. and well-intentioned programs made lots of sense, but actually the end effects aren't translating to changes in people's lives. The second thing we learned is when we give people the same amount of money as it would cost to implement those interventions, more often than not, a majority of the time, just giving them money achieves better outcomes by a significant margin. And so we have this RCT revolution where we're starting to do more and more of these A-B tests and learning as a result that giving cash works surprisingly well. And as a result of the intersection of these two trends, we saw an opportunity for a new organization to be born.

9:35GiveDirectly came to be about 15 years ago. Since then, GiveDirectly sent about a billion dollars to people in poverty and crisis. And there's been more than 25 independent studies of GiveDirectly's work. We work in Africa, in the US, and emergency responses around the world. And practically what that means is that if you're in an extremely poor community, or you've just survived a devastating hurricane, you might hear from us via text message or by call center, maybe someone visiting your community, and then receive a one-time transfer that aims to catalyze you out of that situation. And it's entirely unconditional.

10:12You can do with it what you want. And our studies say people spend it really well. It's amazing, you know, we, not to speak for all United States citizens, right? But amazing how I think a lot of us here and in, you know, sort of first world countries, to put it that way, think about the mobile phone revolution and think about, you know, well, I have a supercomputer in my pocket. I have a camera and it's connected to social and I can do my banking and I can do this and I can do that and all of it. But as you know much better than I, the impact of mobile phones and these communities you're talking about and just they can bank for the first time, to put it that way, right?

10:49And it's just, if listeners, if you're not familiar, I'd urge you to go do a little bit of research. It's really eye-opening and makes you kind of think again about recent history from different perspectives. Oh, 100%. And just one thing I'll add there is like, think about what it means for a community that might be hours away from a market, where it might take hours to walk there and be able to check market prices with a phone call or a text message or something like that for the first time, or get weather updates in a way that you previously were totally at the, you know, kind of a victim of just whatever was going on.

11:22So extraordinary access to information. Yeah. So you mentioned this, and I wanted to ask, but didn't want to interrupt you, but why does giving directly work so much better, at least in these cases and in GiveDirectly's case? Why does it work better than, you know, kind of more traditional means of donating and kind of things being organized and administrated by a group and then handed out? I think you used the word paternalistic before. Can you dig into some of the specifics of why it's so effective? Yeah. At the core of why it works is a few things. The first is who has the most information about what is going to be most impactful for you?

12:02And I think we've all experienced kind of faceless bureaucratic systems that, like, why is it structured this way? And why is it making these choices for me? And the reality is that no matter how well-intentioned a group of people trying to understand what a community might need, they just don't have the same level of information, not just about community, but about you specifically. And so you specifically are going to be able to identify your needs far better. That's the first thing. The second thing is it's far more efficient. We can kind of get those resources to you much, much, much more efficiently.

12:37There's not kind of overhead being eaten up by consultants and Land Rovers and like various things along the way. And so you actually end up kind of receiving more than you otherwise would if it was kind of being done in in-kind goods. And then the final thing, and I think this is like extremely important, the level of like dignity and ownership in being like, oh, this is for me. And so I'm going to figure out how I can stretch this dollar the furthest. I'm going to do everything I can to make sure that this is utilized as effectively as possible. and people use it in incredibly diverse ways. I was reading this story from someone who received money from us just a few weeks ago.

13:13She's this 72-year-old woman in rural Kenya and it's this drought-stricken region and every day she's walking to and from the kind of water source, which is more than five kilometers away. And this is like, as a 72-year-old carrying jerry cans and so on, this is extraordinarily burdensome. So she received a one-time transfer from us, almost$1 ,000, which is a fairly significant amount of money. We generally do a one-time transfer that aims to catalyze someone out of poverty rather than doing ongoing. So we'll never come back. And she took her$1 ,000 and she spent almost all of it on a giant 10 ,000 litre water tank.

13:50And now she pays for that water tank to be filled with clean water twice a month. And then she sells that water to her local community. She sells clean water to her local community and she earns a small profit. And so there's no organization in the world that is being like, you know what we need to do? We need to send 10 ,000 liter tanks to 72-year-old women in rural Kenya. Right. Probably because they're not run by 72-year-old women in rural Kenya, right? They don't know. Exactly. But she can identify the unique opportunity that she has in that moment. And so she can make that go far further by providing a service to her local community.

14:23So that's kind of in the kind of poverty context. But in a crisis context, because we do a lot of crisis work as well, speed really matters. And kind of getting support to people really fast is really important as well. And so digital cash is kind of uniquely powerful. You don't have goods getting stuck at ports and then having to figure out who needs tarpaulins and who needs grain. And there's a huge coordination problem there. Instead, you can go directly to people digitally fast and then they can make the decisions about what is it that they need. And in the process, they can kickstart the local economy and then they can support local businesses and things like that.

15:02Right. So in a situation like that, in a crisis or disaster situation, maybe you can kind of paint a picture for the audience and talk about, you know, you mentioned how critical speed is. What happens immediately after a disaster? What happens in those first 24, 48 hours? And why is it so critical to get aid to the people, to the families affected as quickly as you can? Yeah. So if you're an individual or a family that's experienced the disaster of some kind, it could be your community's been hit by a hurricane or devastating floods or something like that. In the first 24, 48 hours, a few things are happening.

15:41One, you're being like, okay, if you need medical attention, how do you get it? How do you get safe access to water, to food, like the basic necessities of life? Do we need to move from your home to an emergency shelter or a refugee camp? maybe even migrate further do you take kids out of school etc and so this is a moment not just of acute vulnerability where bad things happening is just like really bad but it's a moment where desperation can cause people to make decisions that make it much harder to recover long term yeah often folks are forced to do things like sell livestock or property in order to meet their immediate basic needs.

16:22They sell it at a massive loss. And as a result, they aren't in a position to kind of recover long term. And so you want to try and reach those who need help the most fastest because then they're empowered to make decisions that are actually going to help them recover long term rather than be forced to make these like awful trade-offs that ultimately leave them trapped and unable to kind of springboard out of poverty. Right. No, it's much, much less intense scale. I think we've all experienced that, you know, when in hindsight, like, oh, I only did that because I only made that decision because I was under such stress and, you know, kind of didn't know what to do, but knew I needed to do something.

17:04And if only I'd been clearer headed. So it makes a lot of sense. Yeah. And you talked about this a little bit with talking about, you know, you don't need to worry about getting the resources into port and then what do you do from port to distribute them? Are there other ways in which GiveDirectly's approach to disaster relief differs from traditional aid models? Yeah, I'd say the first thing I'll say is there's a lot of really important work that happens in traditional kind of aid response. Absolutely. But often, not always, but often it is slow, it's rigid, and it's disconnected from what people actually need.

17:38So as I said, like shipments of tarps or grain get trapped in ports. Sometimes you have this influx of free goods that flood the local markets and unintentionally kill all small businesses and so you have this situation where communities are not able to recover because they can't earn income anymore. Many times the kind of traditional form of aid is like either free food or vouchers. Vouchers are meant to be kind of like cash but it's cash that can only be used for food. And this is a very popular form of aid that is given in humanitarian response. Now, would you believe that refugees who are given cash vouchers that can be spent on food often sell them for half their value?

18:26Because what they don't need is food. They might need shelter. Or what they don't need is shelter. They need transport to get to a local hospital. The type of needs that you have are so diverse. And the beauty of cash is it's incredibly flexible. It's flexible, yeah. You can't find any problem that you have. Right. And so that's kind of the traditional approach. And so I think our approach is we aim to be super fast. we aim to get in within days, which is extremely fast for the way that these things often work. We just did a response in Jamaica to Hurricane Melissa a few months ago and months after that hurricane hit, most humanitarian response actors were still waiting to deploy types of support and we had been in and out within a few weeks.

19:08Right, amazing. So cash is, it's more effective because it can be applied to more different problems. like you apply to whatever problem is that people have. It's more efficient because you don't have to spend it all on like, you just do the digital transfers. It's very secure because we can kind of trace exactly who it's going to at an individual level. You don't have it sitting in ports for big periods of time or going through lots of middlemen, which sometimes unlock opportunity for people to just take small little bits along the way. And then the speed is just very, very compelling because it does mean that we can move in days rather than weeks or months.

19:44I'm speaking with Nick Allardyce. Nick is president and CEO of GiveDirectly, and he's the former CEO of Change.org. And we're talking about, well, his life at the intersection of technology and philanthropic work, providing aid, helping people have better lives, really, particularly in crisis situations and poverty. And Nick, we talked a little bit about it, but let's dig in a little more to the technology if we can. Can you talk about how GiveDirectly uses AI tools to identify people who need help the most? There's some other things we'll get into, but maybe we can start there. Yeah. So I think there's like three big buckets where we use technology and AI in particular.

20:28So the first is we have to decide whether to respond somewhere in the first place. Okay. And that involves an enormous set of inputs of imperfect data that is moving extremely quickly. And so actually our ability to synthesize, sort through, and then make high-quality decisions at pace is significantly unlocked by generative AI, actually, as you can imagine. Is GiveDirectly a virtual organization? Do you have a headquarters? I know you're in Brooklyn and New York. How's the organization set up? Yeah. So our global team is fairly remote. We have a few hubs. We have hubs in New York, in London, and Nairobi.

21:15Okay. They're kind of three hubs, but we have a lot of remote staff as well. So when you're talking about the first thing we need to do, it's, I'm imagining, you know, the global map with little lights all over the place. And that's your spread out, you're coordinating remotely and in person. Yeah, exactly right. Okay. It's kind of like a virtual war room that's spun up. understand all of the data that's coming in and sorting through that and making high quality decisions as a result of it is the first use case. The second, it's not very intuitive, but one of the hardest problems to solve when there has been a disaster is who do you support?

21:52How do you find them? And how do you then target that group of people appropriately? Data quality in these situations is often incredibly poor. It's not like there's some government system somewhere that has a perfect ranking of vulnerability and impact. Usually government systems have been hit hard by whatever disaster it is that has struck as well. And so we use a mixture of machine learning and AI to help us identify the most vulnerable communities that we want to go then support. And I can kind of dig into that in a little bit more detail, but that's using everything from telco data to satellite imagery and things like that.

22:32And then the final big picture way that we use AI is engaging recipients, people who are actually receiving money from us or who might receive money from us at scale. As you can imagine, we're trying to move really fast. We can't spend a week to train and scale up and recruit a giant call center that is capable of talking to thousands and thousands of people. And so our ability to kind of reach people in language that they can understand, whether that's text or whether that's voice or things like that, is also unlocked by generative AI. So I understand you're also using AI-powered image technologies for things like assessing damage, forecasting floods and other disasters.

23:19Can you talk a little bit about how you're using AI and related technologies in these ways? Yeah, so one of the ways that we will identify the communities that need help is we use satellite imagery pre and post disaster combined with machine learning models that help identify damage assessments, looking at things like roofs and walls and infrastructure, essentially. And then we'll overlay that with poverty data. So to identify the communities that are most vulnerable, to then identify target geographies that we think contain the people who are most in need of support. So we've done this actually in Florida.

24:02We responded to Hurricane Ian and we partnered actually with Google.org Fellows to build a tool that combines satellite imagery, AI damage detection and poverty data to kind of identify the households and the communities that were most in need of support. To do work like that, do you need to broker agreements with governments, with private data collection organizations? You mentioned telcos. How does that work just in terms of getting the data so you can get started? Yeah, doing this work well requires kind of pre-positioning, contractual partnerships, relationships, data pipelines. It's almost impossible to kind of spin these things up fast enough in response to an individual circumstance for it to be useful.

24:54And so, you know, as another example of one way that we do this in the Democratic Republic of Congo, in East Congo, this is a conflict-ridden region. This is one of the most unlucky places in the world to be born. There's been conflict there for the last 20, 30 years with different rebel groups, conflict between countries, etc. And so people are regularly being displaced, having to flee their homes because of armed attacks from militias or various things. So what we've done is we've built a relationship with one of the telcos there that allows us to use a machine learning model that identifies when people have been displaced by violence and are on the run from their homes.

25:38And so we will get a trigger that says like, hey, there's been an attack in this region. We can then run the model on their data for how mobile phones are moving in that region. And we can see, hey, there's like several thousand people who have been in this fixed location for the last two years and who show patterns of their phone usage that indicate high levels of poverty. and they're literally on the run and we can see it. And we can reach out to them remotely via text message or call center and we can say, hey, we can see you've been affected by this attack. We can see that you're on the run.

26:14We're here to help. And just go through this small two, three-minute enrollment process. We'll verify who you are and then we'll get you some supportive cash that you can then use to make sure that you survive this situation. And that's something that having that system in place, It took us months, maybe every year, to kind of build that level of relationship and to kind of get the data pipelines flowing and to test and make debug and all the things that you can imagine. Once it's in place, we can reach people within 24 hours of an event. And that's almost infinitely scalable. And so our approach is that we're putting in place this in different parts of the world at different times to kind of make sure that we have global coverage, to make sure that we can reach people no matter the situation, no matter the circumstances, quickly, efficiently.