Nithya Ramanathan

Industries and governments are marching on towards digitizing our lives, for better or worse. Nithya, co-founder and CEO of Nexleaf, is one of the people working to bring powerful data insights and deep engineering expertise to ensure data is actually used with equity in mind and for genuine impact. Nexleaf’s temperature-sensing technology is just one example, helping millions of kids around the world get the vaccines they need. Other key lessons: thinking about impact in terms of incentives and disincentives; striving for equity and social value, rather than behavior change.

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Transcript

Jim Fruchterman [00:00]

Welcome to the Tech Matters podcast, an audio series about digital technology and social entrepreneurship. I’m your host, Jim Fruchterman. Over the course of this series, I’ll be talking to some amazing social change leaders about how they are using tech to help tackle the wicked problems of the world. We’ll also learn from them about what it means to be a tech social entrepreneur, how to build a good tech team, exit strategies, ethical use of data, finding money, and making sure that when you’re designing software, you’re putting people first.

As more vaccines are rolled out globally, giving us hope that maybe life in the pandemic era will soon look different, today I’ll be talking to one of the people who work behind the scenes to make sure that people around the world get the effective vaccine doses they need. Nithya Ramanathan is the co-founder of Nexleaf Analytics, a tech nonprofit that pioneered the use of large-scale data to advance our response to social problems. Nithya’s work with sensor data gives her a special insight into how data can be used to highlight popular, but sometimes ineffective, global development programs. Nextleaf tackles all sorts of problems, from measuring whether clean cookstoves actually meet their carbon reduction claims, to keeping track of vaccine temperatures around the world.

Welcome, Nithya! I’m delighted to be interviewing you as part of the Tech Matters podcast. And I’d love to start with your story. Tell us a little bit more about yourself and how you came about founding Nexleaf.

Nithya Ramanathan [01:35]

Sure! I started out my career as an engineer in Silicon Valley, and I went into electrical engineering because I was told by a high school counselor that it was too hard for girls. So, of course, stubborn me, that was the first career I picked. I had no idea, I was not one of those kids who worked with computers, I had not written much code going into college. It was a shock to say the least. But I just I love numbers and solving problems, so I ended up as a hardware chip designer in Silicon Valley when I graduated, and this was a time when people were going off to make millions and I was just a, you know, a nerd. I ended up at Hewlett-Packard, and then Intel, just designing chips because I thought it was interesting. But, it wasn’t enough for me, so I did go on to get a PhD in computer science where I found my real love, which was understanding how distributed networks of sensors and better data can help us solve big problems in the world.

Jim Fruchterman [02:41]

Wait, so you were IoT before IoT was a thing? (Internet of Things)

Nithya Ramanathan [02:48]

Yeah! Unlike most computer science grad students, though, I spent my time outdoors in rice paddies in Bangladesh, in forests, in Idlewild, knee-deep in mud Merced, California, because ultimately, I cared about what was actually happening in the real world. And so my thesis actually focused on arsenic poisoning in groundwater.

Jim Fruchterman [03:15]

Big deal in Bangladesh.

Nithya Ramanathan [03:16]

Yeah. I was putting sensors in the field trying to help understand it. I kind of got really close with the village and the communities there through that work. I kind of took myself out of myself, and I realized that people were looking to me to actually solve the problem. At the time, I was a grad student, I was writing a paper—yes, I cared about these things. But I was like, “What, me? Little me, like, what can I do?” And so when I started to realize the responsibility that was actually there, I was taking their time, I was taking resources, valuable resources, I started to realize we weren’t doing enough by collecting data with sensors.

I started to dig in, learned more, we realized that a well could actually solve the problem. In the village, a deep well that bypasses the arsenic in the middle layer. So, I raised $5,000 over, like, a few days. It came together in the last week of one of my field visits. So we raised money really quickly, we brought in the engineers who dug the well, and everybody’s celebrating and I feel great about myself, you know, I’m in my 20s. And I’m like, “Oh, I helped solve this problem”. And literally the day that I left them on the plane, I’m thinking, “Wait, what’s going to happen when the well breaks? Who’s going to fix it? I mean, we had brought in a team from Dhaka to come build this well, so are they going to be able to come back?” So that’s really how I got my start at Nexleaf, because I started recognizing the ways in which we think we solve problems when we’re actually introducing a bunch of waste material and more problems into an area.

Jim Fruchterman [05:01]

Wow. Famously, abandoned water projects is a thing in global development. And so, you were doing it, like, as a student. Did you actually start Nexleaf as a grad student, were you simultaneously trying to finish your thesis and come up with this new enterprise?

Nithya Ramanathan [05:22]

I was wrapping up my PhD and finishing my dissertation. I was starting a different enterprise, which was… having my first kid [laugh] So as I graduated with my PhD, I decided to have a kid, start as a faculty researcher at UCLA, and start Nexleaf all at once. [laugh] That was my big plan. I had the incredible fortune not only to have a life changing advisor, but also to be working with Martin, who was also in my thesis group and graduating, basically, at the same time as I was; so we decided to start next life together. And a year later, Nexleaf was born.

Jim Fruchterman [06:12]

[laugh] And this is Martin… remind me of his last name?

Nithya Ramanathan

Martin Lukac.

Jim Fruchterman

Okay, your co-founder

Nithya Ramanathan

Co-founder and CTO at Nexleaf Analytics.

Jim Fruchterman

Well, cool. So, you had this observation that collecting data and doing research wasn’t enough, and that building a well wasn’t enough. How did Nexleaf actually get going?

Nithya Ramanathan [06:47]

In the first few months, we took on two problems that really came to us. One was clean cooking. That was actually, I think, our very first project that we got funding for from Qualcomm. And we approached it very high level. My father is a well-known climate scientist, and he had come to clean cooking as one of the ways that we could actually make a dent in public health and the environment is actually solving the issue of cooking.

Three billion people right now don’t have access to modern fuels; instead, they burn dung and wood, and leaves, and plastic, in order to cook. Plastic is not commonly used, but yeah, in refugee camps plastic is burned as well. It’s brutal. It’s very toxic, very bad for people. More people die from breathing in smoke from cooking and lighting in their homes than die from HIV, malaria, and TB combined. So, massive, massive global poisoning happening just from people cooking and lighting their homes.

Jim Fruchterman [08:04]

But how can we solve this with clean cookstoves?

Nithya Ramanathan [08:06]

Yeah, that’s a whole other conversation. It has not been solved. Even 12 years ago, when we started Nexleaf, people had been working on this for decades. Researchers, practitioners, engineers… for decades we’ve been working on this.

One of the things that we saw early on was that the way that people were designing cookstoves was by going to women’s households and asking them what they liked and didn’t like. Conversations would go something like this: I’m a researcher from America, I have just built a clean cookstove, I gave it to a woman for free in rural India. And now three months later, I trump into her home, usually still with my shoes on, with my notebook in my lap, and I say, “So. Do you like your cookstove?” And she says, “Yes, I love it. Thank you so much”. And I say, “Great. And I go on to the next household because I’ve got to talk to 1000 households”. So I’ve got a lot to do, I’m busy, and this is how we’ve been designing clean cookstoves for the last some decades. It tends to not be user-centered at all.

Our focus was: How do you bring objective data to clean cookstoves? How do you actually monitor when people use their stoves, when they don’t, why they do it? And one of the things that we’ll share that we learned early on with Nexlea, that I think is actually unique to us, is that we all said: It’s not about the sensors. Yes, sensors can be objective-ish (we all know the ways in which sensors lie to us) but you’ve got this real data telling you that the cookstove is turned on and off. That’s excellent. That’s just the conversation opener. So now that we’ve got the objective data, now we actually know the real questions to ask, and who to ask them, and when to ask them, so that when a woman stops using her stove we can follow up a week later and say, “Hey, you’ve been using your stove for six months. You stopped over the last few weeks. What happened? Tell us more about it. We care”. Those are all the ways that we get the real stories then.

Jim Fruchterman [10:03]

So people did user-centered design as in they interviewed people about what they liked or didn’t like, but, basically, you’re saying the power dynamic was such that when people were asked, “Are you happy with your stove?” The answer was yes because that’s what they’re supposed to say. And your data helped sort of look into the fact that maybe they’d stopped using the stove a month ago, even though they just told the researcher that they love their stove. And so now you can have a different conversation, which is, you know, we know a little bit more, and in some ways, listening more carefully than we necessarily wanted to before… is that what the data is helping you do?

Nithya Ramanathan [10:40]

That’s exactly right. And to your last point, Jim, listening more, you know, these are inconvenient—these learnings and these findings—because we’re learning that after decades and decades and hundreds of millions of dollars, we may not have made a dent at all. It might be that these products that we’re selling women are terrible. And so that is incredibly uncomfortable to learn.

Jim Fruchterman [11:04]

Well, from past conversations, it blew my mind that because of climate impact, donors were buying down the cost of these stoves based on the idea that they’re gonna save all this CO2, and they’re going to have all these health impacts based on the stoves having a life of two years. And what was the average life when you actually dug into it?

Nithya Ramanathan [11:26]

That’s a great question—varies wildly and depends on what you mean by life. But here’s what I’ll say. Most stoves stopped being used, for whatever reason, after a few months. It could have been because they broke, it could have been because they’re not useful. It could have been because, you know, it turns out that asking a woman who’s incredibly busy to actually chop up the wood into very small pieces and then place them carefully into the stove, and fill that stove up, and then put her heavy pot on… and then to have to do that every 10 minutes when she’s trying to boil rice… just isn’t going to work because normally that woman has to stick the pot on the stove, walk away for 30 minutes, and like, do laundry and wash pots and all the other things and then come back.

And, by the way, the thing that actually nobody talks about is, could we have even been making the health worse because these cookstoves? Most of them have to be continuously tended whereas with the open mudstone she’s got to put a big log on there, throw the pot on, like I said, walk away for 30 minutes, not breathing in the smoke. Now she’s in front of her clean cookstove but she’s got to keep tending it every five to 10 minutes.

Jim Fruchterman [12:33]

Oh, wow. Yeah, it doesn’t deliver the climate benefits, it doesn’t deliver the health benefits, and she stops using it because it actually doesn’t solve her real problem.

Nithya Ramanathan [12:42]

Yeah. What we’ve found is that what’s been largely ignored when you have an object that is going to help solve a problem is that we don’t look enough at the design. How is that object designed? What input? How do you get that input? All of that. The second is the maintenance of that object. What’s the supply chain, who’s the technician, where are the spare parts coming from, all of those things that really matter. The third is we don’t tend to look as much at the use once it’s placed in, you know, the setting. So, you know, in the hospital, in the household, whatever, we don’t look at the use, the training, the SOPs, all of that. And then the fourth is we don’t look at the financing enough. So often the incentives are so screwed up around these things. Pardon my language.

I’ll give you a very simple example in clean cookstoves. A lot of the, even, straight donor financing is based on distribution. So, how many stoves did you distribute. And let’s assume, generously, that distribution means getting a stove into a home, which it often does not. But let’s be generous here. If the incentive is to get the stove in the home, then you’re not going to solve those other things around use and maintenance and design. So, in some ways, what we’ve come to with clean cooking is that we’ve actually got to fix the financial incentives. And that’s when you’re going to get the long-term adoption, the reliability, the durability, all of those things, but those are the four pillars that we look at.

Jim Fruchterman [14:17]

So you get what you incent, and what you’re putting out is, we’re incenting something that is incomplete and therefore doesn’t really accomplish what you’re setting out to do. Obviously, you spent a ton of time on the vaccine supply chain and cold issues—topical, topical issue. Can you like the same issues to vaccine refrigerators and how you did that? How you and your team did that?

Nithya Ramanathan [14:41]

Yeah, we learned about the vaccine fridge issue a few years in, actually. We started out with clean cooking, we did a stint on islands with birds [laugh] so we’ve done all sorts of different things! But a few years into building Nexleaf, Martin and I and the team started to recognize that the value we were going to bring was—we hadn’t quite figured out the four-pillar model yet that I described—what we’d started to see was: okay, we know we want to solve big problems, we know that we want to solve issues where data is not part of just the monitoring and evaluation, that data is built into the entire delivery. And that goes all the way from the systems level thinking, the system standards, all of the financing, all the way down to the delivery on the ground, how something is used. We wanted the data value chain to kind of mirror the value chain of whatever was being delivered, the social sector problem.

We learned a few years in about vaccines. I was at PopTech, and I was chatting with Josh Nesbit at Medic Mobile. And he had said, “So do you know about vaccines?” And I had just had a kid. So yes, I did. And he said, “You know, they have to be kept cold”. I did not know that. And we started to, because I was talking to them, I said, “You know, Josh, we figured out how to build the temperature sensor. And it’s really clever. And I can show you”, you know, like, super excited. Martin had developed this really cool gadget to plug in a $1 temperature sensor into most Android smartphones. So it was real cheap to measure temperature all of a sudden, and we were like, we’ve got this thing! We’ve got to do something with it!

And so we learned about the vaccine cold chain. And so got started early, you know, worked with Medic, got a Gates grant. And we had a very different idea. Back then everybody wanted to invest all the refrigeration and data monitoring capabilities into the capital of a country. Because they said, that’s where the really expensive vaccine product is stored, you’ve got, you know, half a million dollars of vaccine product stored at the country’s capital, and then it gets distributed, but who cares about the rural. But the way that my brain worked, and the way that, you know, Medic worked, they started at the last mile. And so we said, well, let’s look at the weakest point in the chain.

We somehow got through the Gates machinery early on, because that was very unpopular. And, you know, all of the people who were working in cold chain at the time said, this will never work, why are you going to invest money, the nurses going to hate it, it’s never going to last. And so we tested it out. And we did the hard work with nurses, like the hard user design work to really understand what were their pain points. And we worked with a district immunization officer and we started working all the way up the chain within the country, and really learned that when fridges call for help, people want to respond. And so, how do you just equip each person at every level the system with the resources and the knowledge and the tools and the spare parts and the per diems in order to actually respond to that call?

Jim Fruchterman [17:51]

So, when a refrigerator calls for help, what you mean is, it’s having a problem. And the idea is that you alert the nurse at the clinic out in the field saying your refrigerator’s complaining,

Nithya Ramanathan [18:04]

Yeah, so we built a IoT sensor. So, a sensor device that monitors the temperature continuously, also monitors the availability of power or electricity to the clinic, and then sends out a real-time SMS alert to the right people, and can escalate those SMS alerts when problems persist. And these SMS alerts actually contain the information that people need in order to respond to failures in the fridge and can do it in a timeframe to prevent vaccines from going bad.

Jim Fruchterman [18:24]

And the problem is, if the vaccines go bad, they may be shooting duds into the arms of kids that are supposed to be protecting them from childhood diseases and such.

What’s happened as a result of you going against the tide in the field, as an IoT enthusiast—you went out there and you figured out, we’re going to insert these into refrigerators, and as a result, more vaccines are going to get in the arms of kids. So what happened?

Nithya Ramanathan [18:55]

Yeah, so it was it was a journey. But the impact, finally, is that, yes, we keep vaccines safe, you have more potent vaccines going into kid’s arms, but it’s much more than that, even. What we look at is, of course the health impact, but what we’ve come to learn is how important data is to decision making and how important that culture of data is, and helping to strengthen that culture of data. I mean, we’ve all got data, you know, we all access data throughout. You don’t need a sensor to suddenly inject data into your lives. But what the sensor did was it started to reorient and realign conversations at every level of the health system and give us an opportunity to start to better understand how decisions are made. Ultimately, health is delivered because of the decisions that people make.

And so this sensor data, again, going back even to everything we’ve learned, because there’s this belief that sensors don’t lie, it suddenly helps to open up new conversations, helps level playing fields. And so, nurses didn’t hate having sensors. In fact, they loved it, because suddenly they could call up their district immunization officer and say, “Hey, you remember that fridge I’ve been telling you about that keeps dying on me every week? Well, here’s the temperature trace. And now I’m showing you that it dies on me every week, you know that it’s not just because I’m putting a coke in there, or I’m lazy”, or any of these other things that people get blamed for. And yes, of course, you know, there’s bad apples everywhere. But, you know, the sensor data has really helped change the conversation. We’re now at the point where ColdTrace as a technology is in over 25 countries, and is protecting the vaccine supply for one in 10 babies that are born every year on Earth.

Jim Fruchterman [20:44]

On Earth. I’m guessing that’s… millions. Every year. You must be really proud of that kind of impact!

Nithya Ramanathan [20:53]

It’s, you know, it’s an incredible team that has delivered it at Nexleaf. But we’re all incredibly humbled to be part of something like that.

Jim Fruchterman [21:01]

So, let’s shift gears to what you were alluding to just now, which is decisions—changing a system, getting people on the ground paid attention to in a way that actually affects the world in a better way. In other words, that more kids are getting better vaccines. You and I have talked a little bit about this idea of data colonialism. And I remember you saying that we need to decolonize data! And I was like, wow, tell me more about that. So, how did vaccine refrigerators and maybe clean cookstoves get you thinking about these large systems issues, about power, about decision making. Because I think these are really key insights that you’ve had.

Nithya Ramanathan [21:50]

Yeah—we’ve seen throughout how data is knowledge is power is money. And we’ve just seen that play out both in the sectors that we work in as well as in other sectors, we’ve seen a number of patterns where data gets used, data is collected from a fridge in a country in East Africa, but that data doesn’t actually get made available to the government decision makers who have paid for that device, and who should certainly be the ones who have access to that data first.

We see so often, you know, good intentions, bad intentions, it doesn’t matter. Let’s take the intentions off the table. And what we see get played out is that this data gets shipped out either to companies who manufacture the device, or researchers, or social enterprises or other organizations who are working in that, and because they have the tech savvy or the credibility are able to actually get this data. And what does that mean, finally? Well, it’s just a vaccine fridge, you know, why does everybody care so much about this data? You’re not going to sell it to Google, you know, they don’t care. But what ends up happening is a very vicious cycle where data is knowledge. What does that mean? It just means that, with data, you start to uncover where are the real problems, where are the problems that matter. We all know, Jim, you and I know more than many that the framing of the problem is really finding the right question. The right problem can get you to the right answer.

Jim Fruchterman [23:39]

Yeah. And better data enables you to ask better questions, because suddenly you learn something and go, “Why is that? I guess we better figure that out”.

Nithya Ramanathan [23:47]

That’s exactly right. And when this data is being held hostage to preserve somebody’s business model—nonprofit or for profit, we all have business models—and when business models are based on proprietary, coralling data and information so that only one institution or organization has access to that data, whether you’re a founder or an enterprise or researcher, whatever, it gets to this final thing of keeping the knowledge and the power, the power to ask the right questions, the power to find the solution, it keeps it out of the hands of the people on the ground, the communities, the country governments, the people who really are the ones who need to be owning these.

This happens in a number of ways. I mean, a really simple example is, you know, we’ve talked with Ministries of Health, who talk about being at conferences, these conferences that we all attend, and sitting at a conference and seeing data about their country and the performance of their vaccine supply chain for the first time, presented by another researcher, about their country. And this could be the decision maker, the person who actually owns the supply chain for their country. When they’re not getting to see this data, let alone actually be the ones who are analyzing, making sense, and bringing their context, there is something very wrong, and it’s humiliating. It’s disempowering. But it also, again, it gets back to that vicious cycle I was talking about where they’re not the ones bringing their context. And at times this data then gets used to punish people, so… funding can stop…

Jim Fruchterman [25:10]

Let’s talk about both of those. Right. So, first talk about why is context important. How does that actually play out in the real world? And then we’ll talk about the money thing.

Nithya Ramanathan [25:17]

Sure, yeah, so, we know, and this goes back even to my clean cookstoves example, quantitative data alone, sensor data is not that useful, right. A time series plot without the context, without the understanding, means very little. So when a vaccine fridge stops working, we actually don’t know why it stopped working. Did it stop working because it turns out there were no vaccines at that clinic? They intentionally unplugged the fridge? Did it stop working because the electricity went out—and actually, this is an issue that we’ve got to take up with the person who runs the grid? Or did it stop working because, simply, it needed a spare part, that spare part is on backorder.

So that context is actually what matters, the real problem, the real data is in the context. It’s not just in the sensor data. When you take that sensor data and you take it out of context, the wrong conclusions are most certainly being made.

Jim Fruchterman [26:09]

Wow. Okay. And I think that’s the same thing as, you look at something that happened, you say why, and you can imagine different stories. But if you don’t ask the people on the ground in the region who actually know what the story is, then you often leap to the worst conclusion, which is: they’re competent and they don’t deserve money. And you’re saying that people actually do this, now, this is the status quo. People will leap to the worst conclusion and then screw these people by taking away their money.

Nithya Ramanathan [26:27]

That’s right. And then you eliminate even the few resources that were there to actually solve the problem. So this isn’t just about credit. This isn’t just about a paper. This isn’t just about, you know, building a legacy. This is real, hard, bad outcomes that can happen for people on the ground, and they’ve not been involved. And not only are you reinforcing the system, you’re setting people back decades potentially.

One of the things I think is we all need to just pause and think about more is social enterprises rooted in-country, built in-country. That’s why I say, you know—it doesn’t really come from identity per se, and I will be the first to say, Nexleaf is based in the US, it is run by me, an American. But I think it’s time in our sector to really start to think in terms of how money flows, how do we really create an environment that nurtures social enterprises in-country.

Data is a part of it. When data keeps flowing out of a country, and social entrepreneurs on the ground don’t get access to that data, it becomes real hard to start to identify and build towards the real problems. But that’s just a small part of it. And actually, to this extent, I do think there’s an intent I see—within philanthropy, within investing—there’s an intent to actually change this conversation. And I very much want to be part of that movement, because I think that that’s finally how we’re going to get to equity.

The second thing I will say about this is I think we need much more work like Gavi. The way that Gavi works, they disburse is something like a billion dollars a year, but that number varies a lot depending on the year, just to give you an order of magnitude. And that money primarily goes to governments—I think that’s another part of this equation that we need to be thinking more about. The narrative in the social sector, and I’m talking, you know, this is decades old, but there is this narrative around that government bureaucrats are lazy, they can’t be trusted, they’re corrupt. Women on the ground need to just change their behavior, right, like, if you look at clean cookstoves. And I know that this puts me at odds with most people, I know behavior change is really popular, but I have seen in the clean cookstoves space the narrative has always been, “Women have to change their behavior”. And my example to that is always: I live in Los Angeles, and I put my kids on the back of my bike all the time; I know that LA is a crazy place in terms of traffic, in terms of air pollution, but guess what, that’s how I get my kid to their daycare, you know, like, I don’t have access to a car or I didn’t at the time, so that’s what I have to do. So yes, you can tell me that I don’t care about my kids, that I don’t love them enough, that I have to change my behavior. But until you build a public transit system in my city that I can use, this is what I got to do.

There’s just all these ways in which these narratives are created that I think shift blame in ways that just aren’t productive. I want us to talk about equity, and that means if we’re going to work in a country, well, we better trust the government enough in terms of the health system to actually have the resources go there and have the government decide which manufacturer they want to work with. Yes, we need standards, yes, we need the “who” and all of that. But if we keep the locus of power, decision-making in DC and Geneva and Los Angeles, where I am, we’re not finally going to achieve that equity lens. Equity is not just about saying that we have to make sure that every country on Earth gets a Pfizer vaccine. I’m sorry, that is not equity.

Jim Fruchterman [30:23]

Well, this is I mean, I call this the defective customer paradox. Everyone in business does not believe in the idea of a defective customer, right—either you’ve built a product they want, or they don’t want your product. And suddenly, when you go to the same people and you think they’re beneficiaries of the social sector, they all become “defective”! “Those women should have fewer kids, wash their hands, they should cook a different way”. And it’s like, you never wag your finger at your customer, saying “You defective customer, you didn’t buy my product, you should buy my product, because I’m angry with you”. People say, how do I change the incentive or the disincentive structure so that people are more likely to buy my product, you know, because I lowered the price, or made it a better value, or whatever it is. But the nonprofit sector does not think that way. And the donor system, the global development system, has these, you know, traditional charity and potential colonialism roots that have us wagging our finger a lot more often than we actually like to think.

So, as we wrap up, Nithya, I just wanted to thank you for being so generous with your time and your insights from the front lines of using data and Internet of Things to actually make an impact in the world. So, really appreciate it, and hope that you have some final words before we wrap up.

Nithya Ramanathan [31:54]

Well, thank you so much, Jim, thank you so much for just holding this space and the ways that you’ve helped the sector have conversations. Actually, one of the things that I didn’t get to share—I’m going to wrap this up on a quick story, if you don’t mind.

Jim Fruchterman [32:12]

Go for it.

Nithya Ramanathan [32:14]

I came into this space because of Jim. I bet you didn’t think I was going to tell that story. [laugh] So I was early on in my PhD, and I was going to drop out. And I don’t think you know this full story actually, Jim.

Jim Fruchterman [32:31]

No, I have not heard this.

Nithya Ramanathan [32:32]

Yeah, so I was in my PhD, like I said, in computer science. And after my first year, I was going to drop out because I had been surrounded by people who were really excited about this one class I took where people talked about making landmines, automating them so that if there was movement the landmine could actually propel itself automatically to where the movement was to explode and kill more effectively. These were just some of the conversations that were happening in my PhD program. Anyways, I just was like, oh, I’m not cut out for the space. I’m not gonna fit in here. These are not my people. These are not the problems I’m trying to solve. I don’t know what I was doing. I had applied on a whim anyways, and so I was ready to drop out.

My husband had convinced me to just take a summer off and just, you know, just take some space, just cool your jets. And so, I took a summer off and I just started researching what were some of the ways that technology was being used for social good. And this was roughly 2002 so, you know, we weren’t where we are at today. And I was volunteering locally, not really doing stuff that I was great at, I kind of sucked at it, you know, I was helping teach kids technology and computer skills—not a good fit for me. But I remember the day where I was sitting and I learned about Benetech. And I read about you, and I just was like, “Oh my gosh, this is somebody who’s solving problems that I want to be solving. I want to work there. I want to know this person, I want to do whatever I can to do these types of things”. And so I actually I think I tried to get an internship with you or something—I got rejected [laugh]. But, you know, I just kept that in mind. And I was like, “No, there’s somebody out there who is solving these problems”. That really changed my trajectory. And so, I went back to grad school. That’s when I started to work harder. I found the work in Bangladesh, I made it happen with my advisor. And then I remember not that long ago when I won a—oh my gosh, I’m spacing on the tech museum award…

Jim Fruchterman [34:51]

Oh yeah, the tech for good awards they had.

Nithya Ramanathan [34:55]

Yeah. And, then I got to meet you because you were there!

Jim Fruchterman [35:00]

I think that was 10 years ago! [laugh]

Nithya Ramanathan [35:06]

It was about 10 years ago. And I tried to tell you the story, and you know, we hadn’t met before. And I was like, I’m so excited to meet you, and you know, you got me into this space. And I remember you were like, “Oh… great!” And you were, you know, happy but like so confused.

Jim Fruchterman [35:17]

I was stunned, I’m like, “How has anyone from UCLA ever heard of me?” was sort of my reaction.

Nithya Ramanathan [35:29]

Yeah, I remember. But anyway, since then, you know, we’ve gotten to really evolve our partnership. So, thank you! And I really mean that from the bottom of my heart, Jim. Thank you for having me on the podcast and for all the work that you have done in this space.

Jim Fruchterman [35:45]

Well! I’m delighted to have been part of keeping you on track for your PhD, something I did not manage to pull off myself, so I admire anyone who’s gone through that. Again, thanks a bunch and looking forward to more conversations, and changing the course of the tech for good field by being smarter and better informed, and mindful of the things that we really need to be doing to shift that power and money to the people who need it the most.

Nithya Ramanathan [36:11]

Awesome.

Jim Fruchterman [36:14]

For more about Nithya’s work, check out Nexleaf’s Twitter handle @Nexleaf, as well as nexleaf.org. To read more about this interview or to learn more about what we do at Tech Matters, go to techmatters.org and check out our blog. This podcast is funded by the generous donors of Tech Matters, especially Okta for Good. Thanks! And see you next time.

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