The future of farming
Food security expert David Lobell is immersed in the data of agriculture.
He uses satellite imagery, yield data, and advanced computational modeling to analyze the roughly 500 million farms worldwide to increase productivity and ensure global food security – now and in the future. Though food is often taken for granted, feeding a hungry world is our greatest environmental challenge, he says. Lobell goes on to explain how data can do much more than increase yields – it also cuts costs, prevents conflicts, reduces emissions and deforestation, and improves nutrition. Smart farming is key to food security and avoiding the problems that stem from hunger, Lobell tells host Russ Altman on this episode of Stanford Engineering’s The Future of Everything podcast.
Transcript
[00:00:00] Russ Altman: This is Stanford Engineering's The Future of Everything, and I'm your host Russ Altman. Since we started this show eight years ago, it's become an archive of amazing and impactful work by my Stanford colleagues. Research is not something that just happens in the lab, and as you'll hear on this show, the research at Stanford can impact areas like health, technology, law, and business, and many other topics that can affect everyday life. We hope you'll tune in to learn more about how research has the potential to help your life and to help the lives of people you care about in your family and your community.
[00:00:32] David Lobell: It's true that our, you know, society in general is much more well-fed and better off. The last 25 years has not been a success story. We've seen reversals in a lot of the progress. We see the real price of food has gone up. We see the rates of deforestation have ticked up. These scenarios, again, for climate stabilization are, are, are requiring a super optimistic scenario for agriculture, and we've headed in the other direction.
[00:01:00] Russ Altman: This is Stanford Engineering's The Future of Everything, and I'm your host Russ Altman. If you're enjoying this show, if you like what you hear, go ahead and follow it. It'll guarantee that you never miss an episode.
[00:01:10] Today, David Lobell will tell us that the production of food is not just about getting stuff for us to eat. It also is intimately related to political stability, international war, and environmental damage. It's the future of farming. Today, we're gonna continue our feature that we call The Future in a Minute. I'll ask David at the end of our conversation some quick questions. He'll give us some quick answers, and that'll be The Future in a Minute.
[00:01:36] Also, don't forget to follow the show so that you never miss the future of anything.
[00:01:48] So we all know a little bit about farming. Of course, some people know a lot, 'cause they're farmers. But for the rest of us, we know that you plant stuff, you water it, you fertilize it, it grows, you harvest it, you send it to market, and people eat it. But food and food production is a lot more complicated and is actually related to things like political stability, international, conflict, and environmental damage.
[00:02:12] So it's a big deal. We also know that farming comes in many shapes and sizes. There are small family farms and there are huge, large industrial farms. So what is the state of farming? How are we doing? Are we feeding the world? Are we doing our best, or is there significant room for improvement?
[00:02:28] Well, David Lobell is a professor of Earth System Science at Stanford University and an expert at agriculture and food security. He uses satellite imagery, data, and computational modeling to understand what's going on in the world, over 500 million farms, in terms of productivity, the crops they're growing, and how things are doing. They use that data to come up with new hypotheses about how they can help farmers be more productive and ultimately more happy and get food into everybody's belly.
[00:03:01] David, to start out, why have you devoted your research career to understanding agriculture and food security?
[00:03:09] David Lobell: I guess it started, I was a student looking for something that I thought was interesting and important. And, I was a math major, so I was looking for quantitative stuff. A lot of interesting stuff, but I didn't view it as very important. And, and similarly some important things, but I, I wasn't really fascinated by it. And I was very interested in environment, so I went to grad school in the environment, and I slowly sort of came to the conclusion that the most important thing in the environment was how we were gonna feed the world going forward.
[00:03:36] And that got me into the field, and that got me more fascinated. And over time, I just sort of understood deeper and deeper why this is such both an important and interesting topic.
[00:03:45] Russ Altman: As you look back on your, like childhood and raising, does it kinda make sense given the kinds of things you did or the kinds of experiences? Do you, do you have a farming or agricultural background? it's just a very interesting decision.
[00:03:56] David Lobell: Yeah. No, I grew up in, in the suburbs of New York City, so it's about as non-agriculture as you can get. You know, looking back on it, I think I can see sort of indications of sort of interest in, in, sort of... or being taught sort of that it's important to help improve the world, try to think of who the most, impoverished are and, and how you can help them. That was sort of inherent in, in the sort of culture in my upbringing. But it, it wasn't really till I, I, like I said, I got into the field and really understood agriculture that I really sort of got turned onto it.
[00:04:31] Russ Altman: Great. So one thing I wanted to ask for kinda a, as a ground, landscape setting is, farming, we all kind of know what farming is, but I think, it, we could all benefit from a little reminder of how you think about farming. We all think about big industrial farmers, but we also know that there are people who are, family farmers. And, and as you look at this in your work, which one do you focus on, and how do you maybe combine them? 'Cause they seem to be very different.
[00:05:00] David Lobell: Yeah, our work is, is really global, so we work in some very developed countries, some very developing countries. The specifics of agriculture always change where you are. I think there's kind of two general questions that people have. one is just how can farmers be more productive for their own benefit? So how can their yields improve? How can they reduce costs? And you have that question throughout the world.
[00:05:23] The other set of questions is about how can you, improve sort of the public impacts of farming, basically maintaining farmer livelihoods, but nudging them towards things that are better for the environment or better for society. And so, when we're looking at problems, we're typically working with either people who are setting policies or making investments. Or people who are talking directly to farmers and trying to give them advice or provide them with, services. We're very rarely working with the farmers directly, but we do talk to them a lot to get an understanding of what the sort of real problems are.
[00:05:57] So smallholders, large holders, they all have sort of, as I said, their peculiarities, but they're all fundamentally dealing with the fact that it's a very difficult way to make a living. It's a very difficult, system to understand how can you change and, and be a little bit better.
[00:06:13] Russ Altman: Great. So now, in terms of farming, what, what would you say..., you gave us a little bit of hint of this, I think- in your previous answer, but what are the big issues in, in your world that are pressing and need to be, solved?
[00:06:28] David Lobell: So if we take this dichotomy, if you look at the sort of more developing countries, especially in Africa, the big issue is just how do you get productivity higher. We know that most of these areas are, are 50% or less of what their crops could be achieving with good management. But there's all sorts of good reasons that they don't achieve that. And so there, the, the real questions are, for example, what kind of fertilizers do they need, whether planting trees would be helpful. Are there soil amendments that could help? there's been
[00:06:59] We've done work in India, for example, on moving from just hand broadcasting of fertilizers to, spreading it with a handheld like rotary thing. So it's, the, the specifics vary a lot, but it's really about there's always hundreds of ideas that people have about what should work. There's usually very small fraction of that that actually will work, and we wanna know how well things work and where they work.
[00:07:21] On the more developed side, it's really, I think, increasingly about getting agriculture to a place where it is, some people will call it sustainable or regenerative or net zero, but trying to basically really reduce the cost that agriculture has to society. So in, in Europe, for example, there's lots of policies being promoted to, increase the biodiversity of agriculture, try to reduce the nitrogen going into it, try to reduce the carbon emissions from agriculture, or even try to sequester more carbon into agriculture. So this is sort of under the umbrella of, as I said, regenerative or sustainable practices.
[00:07:57] The US also has been promoting a lot of these, and the key is you wanna promote things that help farmers as well, or at least don't hurt them, otherwise they're not gonna take. And so there's a lot of, again, a lot of ideas about what should work, a lot of things that on paper look good, and then when they run into reality, they don't work as well or they work differently than we expected.
[00:08:15] Russ Altman: So, I'm, really interested in your, in your statement that, the, African farmers may be at only 50% of what they could do. And, first of all, how do you even know that?
[00:08:27] David Lobell: Well, you know the seeds that they're planting, so you know the genetics of the seeds. You can run experiments, like controlled experiments in those regions where you give it everything that, you know, you would think it needs, and you can see the yields are much higher. You can also use sort of basic understanding of biology and biophysical models that, that simulate, and you can cross-reference all of those.
[00:08:47] And you can also see that there are some farmers actually achieving two or three times the yields of their neighbors. And so you can get a, a very clear sense that things are not going well. You can also just go into the field and see all the problems-
[00:08:58] Russ Altman: Right
[00:08:58] David Lobell: ... that they're having.
[00:09:00] Russ Altman: And, and can you tell, is this so I'm sure that they are, that they would like to increase I'm, I'm suspecting they would like to increase their yields unless there's like perverse incentives that I, you sometimes hear about.
[00:09:10] David Lobell: Right
[00:09:11] Russ Altman: ... Is it a problem of, resources that they have to actually enact these improvements, or is it lack of kinda dissemination of these good ideas, or are they structural barriers to actually taking them up for, for kind of quirky local reasons?
[00:09:28] David Lobell: It, it depends, and you can imagine there's vast literatures and all those things arguing for each of those. It really if you were somebody who really believed in institutions as the barrier, you could say, "We have all the technologies we need, and we just need to get them out there," or, "We just need to build better infrastructure, better information systems."
[00:09:44] But the reality is, you know, farming is extremely hard, and when you're in a, for example, a tropical soil that has, is very acidic, has very low organic matter, a lot of the things that work on the experiment stations or that work in other countries don't actually work. So, it's a very empirical question about what actually works and what works at, you know, at a good cost level that you can actually, you know, justify it.
[00:10:08] The other thing that's going on in those systems is, is the, the land holdings are so small that even if they knew something with enough effort and and enough inputs would be dramatically better, the returns on that investment just don't really get them out of poverty, so they're better off spending their time trying to, you know, get, get work in the city or, or, you know, find a better job.
[00:10:30] So there's all sorts of complicated things, but, you know, given the world we're in, you know, we're trying to look for the things that on the margins can help kinda get the system going or, or improve things. And there are a lot of creative ideas out there. There are a lot of NGOs and governments trying things out. And what we're trying to avoid is them taking 10 or 15 years to try things out. Because again, the traditional kind of approach is to learn very slowly. And, you know, a lot of our work is about speeding that cycle up and really in almost real time understanding, okay, this thing really looks promising, these other five things don't.
[00:11:03] Russ Altman: Now, I, I do wanna get into some of the, forgive me, for this phrase, but the cool technology that you guys use to gather data to try to, learn what's happening on the ground and then even propose, new, new initiatives. So, so can you tell me how your kind of lab works in terms of gathering the, kind of raw data that allows you then to make inferences about the state of, of a certain region, either it's poverty or it's crop production, and, and, and the efficiency of all of that?
[00:11:35] David Lobell: Sure. The I think the starting point is that the traditional approach, like in a lot of sciences, in agricultural science, is you, you design a hypothesis, an experiment to test that hypothesis, and then you run the experiment. And that is how agriculture has proceeded. Again, the challenge is there's so many factors involved.
[00:11:51] There's a lot of heterogeneity, like different effects in different places, that even if you take the decade to run a whole bunch of experiments, you only have, you know, some ability to draw conclusions. So our basic approach is to, you know, observe the experiments, like understand what they're saying, but take a different approach, which is more of a big data approach of just observing what's happening.
[00:12:11] And the, the key here is that agriculture, whether it's small holder or, or, or large holder, is a, is an outdoor activity, right? We can actually use satellites to look down and see what's going on. We can see how the crops are doing. We can often see how the humans are managing the crops. Not that we can, you know, see the individual humans or their tractors, but we can get a sense of whether they've tilled the soil, for example, or whether they've planted this crop or that crop and what kind of sequence of activities they did, whether they've irrigated, whether they've planted trees, all, all sorts of things.
[00:12:42] So, we're just kind of observing. The key here is that there's 500 million farms around the world. So we can go from a, a space where we have hundreds of very carefully controlled experiments to tens of millions of more natural experiments where we're just- Right ... observing and then we're seeing as things come in and out, what were the effects.
[00:13:00] And so, our lab, a lot of it is focused on how do we observe the things that we want to observe? How do we make sure that we're actually measuring things well enough? And so a lot of our field work, for example, is in taking ground measures to make sure that the things we are detecting from satellite or other, sensors is, is good or good enough to do the analysis.
[00:13:21] And then the, the rest of our lab is really not so much developing causal inference techniques, but trying to use the latest and greatest causal inference, meaning, you know, using observational data to, to make causal statements. And doing that in a context where we know all the datasets we have are not perfectly measured, so we have to be careful about sort of interpretation in that context.
[00:13:43] So the I would say the cool aspect of what we're doing in terms of the, the techy innovative stuff is that we use a lot of cool sensors, that are at this point kind of on a daily basis observing all the farms in the world. And so we can build massive, massive datasets that we can then mine for insights into what, what is working or what might work.
[00:14:03] Russ Altman: It's so attractive, as you know better than me, because we think of satellites as looking out into the world, into the universe and collecting stuff about the stars. And in a funny way, you've just kind of turned them around and said, "Hey, let's, let's see what's going on on Earth." So it is very attractive.
[00:14:18] So, let me just ask a couple of kind of basic questions. are these satellites up there for you and your colleagues and farming and food people, or are you piggybacking on other satellites that are there for other reasons?
[00:14:32] David Lobell: Well, actually, some of the early motivations for satellites back in the '70s was that we were trying to figure out how much grain Russia was growing because there was a couple of episodes where the world markets were really surprised that there was a shortfall. And, and that kind of motivated some of the initial ideas of what's called Landsat, which is the first major satellite.
[00:14:51] But if you fast-forward over time, satellites became used to study everything, and many of the new sensors out in space are designed to look at things like carbon cycling, forest, deforestation, lots of, hydrology questions.
[00:15:05] So, we often find ourselves now looking at sensors. There's a sensor, for example, that measure, that measures gravitational, changes in the Earth's surface. And there's other sensors, for example, that measure, with lasers, they measure the heights of, of forests. But we find ourselves often repurposing that to look at agricultural questions that they weren't designed for.
[00:15:25] Basically, we, we have lots of sensors measuring different things at different frequencies, different resolutions, different temporal kind of cadences, and that, those all have something to say if, if you are asking the right questions about the agricultural systems.
[00:15:39] Russ Altman: Yeah. Great. And, just a couple more because, of course, I, I'm, I'm intrigued by this. What, could you give me, like, a litany of the types of things you measure and also, like, how precise both in space and time? Like, are we get-are we, I think you kind of implied that you're almost getting a daily update on each farm, but I don't know if, if you meant to say that or if I heard that wrong. And then,
[00:16:00] David Lobell: Yeah
[00:16:00] Russ Altman: ... Also, like, what kinds of things would you look at for a, for a given farm? You, you made some reference just now to some of the things you can sense, but I'd love to just get a, an overview of, of these kinds of datasets.
[00:16:13] David Lobell: Yeah. I, I also have to be careful in Silicon Valley, like not confusing the aspiration of where we wanna get to, to where the reality is right now. I think the reality is that we can see large fields every week in most parts of the world. But in the last five years, we have gotten to the point where the both the temporal frequency is getting down to the daily timescale, and the spatial resolutions of these are getting down to very, very small fields.
[00:16:39] But fundamentally, all you're measuring in, in these cases is light reflecting off of the surface, or you're measuring like a, a lidar or radar beam that bounced off the surface. So what we have to do then is translate that to things we care about.
[00:16:51] Russ Altman: Yes.
[00:16:52] David Lobell: And there we've made a lot of progress on some things. So just to give you example, I was, you know, this week working with some European data. So the European, consortium, the research consortium now not only produces great raw satellite data, but they're producing, for every field in Europe what the crop was grown this year, whether or not they, planted a secondary, like a cover crop, what time of year the plant was sown, when it was harvested.
[00:17:22] We've done a lot of work in our lab on measuring yields, so productivity at the end of the season or even a little bit before the end of the season, and we've done this for a bunch of different crops. So I would say that those variables, the ones I'm describing, we have nailed pretty well, and we continue to test them in the really complicated smallholder systems where it's still a bit of a challenge, but they work as well or better than a lot of the traditional ground-based measures.
[00:17:45] And then you get kinda to the more complicated, like the nuances of exactly how are they preparing the soil, exactly, you know, when are they, are, are they growing more than one crop in the field? What kind of trees are on their landscape and-
[00:17:58] Russ Altman: Yeah
[00:17:58] David Lobell: ... And, you know, what kind of effects those might have. So there's a whole suite of things where when students come and they're looking for like real, the technical frontier, that those are the things that we work on. And a lot of the challenge there is actually getting good quality ground data at scale to test. And so we partner often with research partners, either in private sector or public sector to get that ground data. We don't really have the capacity here to do it all ourselves.
[00:18:23] Russ Altman: Are you able to tell what exact crop is growing? Like-
[00:18:27] David Lobell: Yeah ...
[00:18:27] Russ Altman: is the colors or the texture enough to say, "That's corn, that's wheat," et cetera?
[00:18:32] David Lobell: The, with a snapshot, it's hard. So it, there are some things, like if you have a rapeseed or canola field that's in flower, like you can see it's very yellow.
[00:18:41] Russ Altman: Yeah.
[00:18:41] David Lobell: And... but that's typically not what we're using. We're typically using the fact that, crops have slightly different seasonalities. They also have slightly different levels of peak biomass. They have different leaf angles. So for example, soybean with very flat leaves is gonna look quite different than, than corn because of the way it reflects light.
[00:18:59] Russ Altman: Yeah.
[00:19:00] David Lobell: And then there are some interesting things like sunflower, actually, the way it tracks the sun during the day. There are morning and afternoon sensors, and so you actually get a good contrast- for the sunflower plant of how it looks in the morning and afternoon. So there's all sorts of tricks that people have used, but fundamentally, if you have a field growing one crop, we're pretty good at telling what it is. If you have fields growing multiple crops, that's, that's more difficult.
[00:19:22] Russ Altman: Yep. in going over, a lot of the papers that you've published recently, I saw that you're building what they call in AI these foundation models, and I'm guessing it's, like, models that can be used to build all kinds of apps to do these kinds of analyses of, temporal and, and spatial distribution of plants.
[00:19:41] This is The Future of Everything with Russ Altman. We'll have more with David Lobell next.
[00:20:01] Welcome back to The Future of Everything. I'm Russ Altman, and I'm speaking with David Lobell from Stanford University. In the first segment, we learned a lot about the state of farming, in the world. We learned that there are 500 million farms, that they very different problems, and there are probably very different solutions to these.
[00:20:17] In this segment, I will ask David to just remind us how important food production is to world peace and to tell us some examples of his most recent work getting information to the farmers that is truly useful for them. Don't forget, at the end of our discussion, we're gonna have the Future in a Minute, where I will ask David some questions, he'll give me some answers, and it'll be short and sweet.
[00:20:40] So David, for this section, I just want to start out kind of going back to the beginning. You've said in, in, verbally and in your writings that people underestimate the importance of food as a, like, as a phenomenon. And that's a funny thing to say because, of course, most of us are multiple times a day interacting with food. But even with that being true, there's a sense that they, we might not appreciate the importance of this, this whole phenomenon of food. So can you expand on that?
[00:21:08] David Lobell: Yeah. Thanks. I, I, I start often with a Chinese proverb that I heard a while back, which is that a well-fed man has many needs and a hungry man has only one.
[00:21:17] So I think the idea is that in a well-fed society, and many of us are, are well-fed, as you said, we just we take things for granted, and that's, you know, maybe how it should be. But the reality is when people have food, they can be happy or they can at least spend their time worrying about other things.
[00:21:32] When people don't have food, or even if they're worried about not having food, you see lots of bad things happening. You see the direct suffering from hunger, obviously. You see people cutting down forests and, and all sorts of other environmental damages, as any of us would do if we were trying to feed our family, I think. You certainly see social breakdown. You see lots of, you know, rise of, of populism. You see, you know, historically all sorts of wars. You see lots of, social cohesion breakdown and, and that's, I think a very important thing that was understood, you know, many decades ago, but has a bit been forgotten. You see a lot of geopolitical conflicts, you know, that was what a lot of the Cold War was about, was trying to make sure agriculture was sort of improving around the world to, to avoid those.
[00:22:15] And then I think the most recent thing that people, I think, have started to appreciate is that if you don't have a well-fed world, you're, there's no chance really of solving climate change. And what I mean by that is if you look at any scenario of stabilizing climate at about two degrees or even a little bit more than two degrees, there's a large component of that that comes from putting carbon into land systems, basically moving land from a big source of carbon to a big sink of carbon. And the only way you can feasibly do that is if you're very successful in growing food that you can actually devote even less land than we have today, that than, to, to these sort of carbon, accumulation activities.
[00:22:55] And I think the other aspect that people don't get is that although we've made a lot of progress historically, and it's true that our, you know, society in general is much more well-fed and better off, the last twenty-five years has not been a success story. We've seen reversals in a lot of the progress historically. We see the real price of food has gone up. We see the rates of deforestation have ticked up again. So, you know, these scenarios, again, for climate stabilization are, are, are requiring a super optimistic scenario for agriculture, and we've headed in the other direction.
[00:23:24] And at the same time, investment in agriculture is headed in the other direction. So although there is a lot of exciting innovation going on, the, the sort of seriousness with which the world is taking the food problem is I don't think on par with what the actual impacts could be. And if you wanna look at any big problem in society, you can probably trace it back to the fact that, you know, somebody somewhere is hungry or worried about being hungry.
[00:23:44] Russ Altman: Well, thank you. That, that actually is a really good answer because then the, other than world peace, political stability, environmental stability, other than that, we don't have to worry about food. So it's, it's a big deal.
[00:23:58] Tell me about some of the recent research that's been going on in your lab, kind of on the ground, new insights. Of course, none, no single one of these insights will solve the problems that you're, you just described. But the set of insights together give us a way forward. So, tell, tell me what's getting you excited recently.
[00:24:16] David Lobell: Okay. I'll, I'll start maybe in the US 'cause that's, you know, close to home. I think one thing that's relevant here to the climate point is that a lot of, states and governments have been promoting farmers to, grow a cover crop, meaning that when their crop is about to be harvested, they put something in for the winter that covers the ground. Initially, actually, the motivation was to reduce nitrogen runoff into water 'cause that's a big issue, water quality. But it was also looked at as a very important way of taking carbon out of the air and putting it into soils, improving soils, and also helping reduce climate change.
[00:24:48] So there's been a big push. There's been a lot of big enthusiasts. and there's been experiments showing very, you know, different effects, some showing gains, some showing losses. What we did was we used satellite data to look at this as this gets rolled out in the US, we're now at about fifteen percent or so of farmers using cover crops.
[00:25:06] And we showed that actually, and, and we had to sort of check this a couple times, instead of actually improving productivity of the farmers, it actually led to a decline in the productivity. And we understood then further that most of that decline was due to the fact that it was pushing the planting of the, of the cash crop too late because they had to, in the spring, they had to, you know, terminate the cover crop and, and get the other crop in.
[00:25:28] Russ Altman: So just to clarify, the cover crop in general is not a high value, plant?
[00:25:32] David Lobell: No. It would be a, it would be like a rye or a mix of different species. And, and then actually in the US you're not allowed to plant something that you would then harvest something from because it's a, it's part of the rules of getting the payment.
[00:25:43] Russ Altman: Ah.
[00:25:43] David Lobell: They don't wanna flood the market with, with grain. The other thing is that though you see the cover crops do consume water, and though if you're then growing a cash crop in a, in a drier year or drier location, you see losses associated with that. So that's an example to me of a study that had sort of a counterintuitive result, but also kind of paved the way or pointed the way towards maybe more effective ways that it could be implemented.
[00:26:06] We're doing something similar now with rotation. That's a, that's not just in the US, but it's a good example where this is something since agriculture-
[00:26:13] Russ Altman: Yes
[00:26:13] David Lobell: ... Started ten thousand years ago, people have understood that you don't wanna grow the same crop over and over. But the, you know, the specifics about that, when does it really matter, how much does it matter, is interesting. And we've pieced together, because as I we were talking about before, you can see what's growing each year in every field. And we've looked at things like when you're growing wheat in the US, what's the best crop to grow before it?
[00:26:34] And it turns out, like, a bean crop is really good if you're growing spring wheat in Montana. It fixes nitrogen, it breaks the pest cycle, and you actually see spring wheat yields much higher, actually, after growing a bean crop than if they were growing a wheat crop. But then when you go to a winter wheat place like Kansas, we actually saw the opposite. We saw that growing a bean crop, typically it's soybeans there, before a wheat crop actually led to lower yields.
[00:26:57] And the, our understanding of that to this point is that it's actually both because it's pushing, again, pushing the planting of the, of the wheat crop too late. That's often an issue is the timing of the season. But it also has to do with not just the water use of the crop, but the fact that in the winter, if you have wheat straw, it helps to trap the snow. And in the soybean is a very small amount of residue that doesn't really help to get water trapped into the field.
[00:27:22] So there's all these, again, peculiarities that show up that, you know, big data really, help you see in a way that experiments.... Sometimes you can find experiments showing that, but you can find an equal number of experiments kind of in different set of conditions showing something else.
[00:27:35] Russ Altman: I'm really struck by that example because you've in your writings, you've talked about the personalization of farming similar to personalized medicine or personalized education, and that's a great example right there, where the answer for the, for the wheat is, is a, is a personalized answer based on the local context. And-
[00:27:54] David Lobell: Right
[00:27:54] Russ Altman: ... and those kinds of insights I'm sure are of, of great value to the farmers in those areas, and you just need now to do it for 499 million other farms. What, what's going on-
[00:28:04] David Lobell: Yeah
[00:28:04] Russ Altman: ... more globally? What would be an example of a recent kind of impactful observation, maybe either a surprise or confirming a theory that was theoretical?
[00:28:13] David Lobell: Yeah, just on that last point though, I think also part of the goal is that maybe policies could be sort of state or county-
[00:28:19] Russ Altman: Yeah ...
[00:28:19] David Lobell: specific, and so you could nudge farmers in general in the right directions. Right now, almost every country has sort of national policies, and those are a very blunt instrument to try to get, like, the outcomes that we care about. Maybe cover cropping should be in certain states-
[00:28:32] Russ Altman: Right
[00:28:32] David Lobell: ... not others, for example. Another example, just quickly since I already mentioned it, was this fertilizer spreader in India. Very basic technology trying to look at, basically using one of these rotary spreaders as opposed to hand application, which leads to more even, application. And what we saw was, first of all, that it was an effective intervention. It was a good investment to try to help farmers to adopt these things.
[00:28:57] But what we also saw was that you could actually use the historical information on the fields, which we get from satellite, to identify the farmers that were most likely to benefit. Basically, the lower-yielding farmers were much more likely to benefit from this technology. So then we've gone from thinking about using observations simply as an evaluation tool to, like, watch natural experiments, and now in, in addition as a targeting tool. So you could-
[00:29:20] Russ Altman: Yes
[00:29:20] David Lobell: ... go in and again personalize not just the recommendations, but the, the effort to try to get farmers to do things. And so, you could double or triple the efficiency of programs. And a lot of, a lot of development in agriculture is very resource, you know, strapped. Like, you're looking at thousands or millions of farmers, and you have a very small budget. So if you can more efficiently target, the things that we think will work to the people we think it'll work best for, then that could really change the calculus of how difficult it is to, to help agriculture improve in these areas.
[00:29:54] Russ Altman: I'm struck by that example because, you know, in my own work, which is kind of related to personalized medicine, going that last mile to the difference between knowing what should happen and then getting the practitioners and the patients to adopt it is, is a, is a hard road. And it sounds like it's a similar challenge. And, and as you said, you then need to work with policymakers and people on the ground. You obviously, as a professor at Stanford, don't have the resources to contact 500 million farmers and tell them about their personalized, farming prescription, if you, if you allow me.
[00:30:25] David Lobell: Nor should they trust a-
[00:30:26] Russ Altman: Right
[00:30:26] David Lobell: Nor should they trust a Stanford professor.
[00:30:28] Russ Altman: Right. Yeah. So, so it, I guess to, to as my final question, do you how much do you get involved in planning for the actual dissemination of these ideas to the, people on the ground literally making these, decisions about when and how to plant their crops or to, to fertilize their crops?
[00:30:48] David Lobell: Well, I, I personally enjoy getting into the field and, and working both with the practitioners and then the farmers themselves. But I also am very... you know, I, I have to have a lot of humility when I go into these systems. Not, not just as a practical matter because it is more effective, I think, but just because I know so little of the specifics in a situation.
[00:31:08] So, for me, the best scenarios are when partners approach us and say, "We know you have these capabilities. Can you help us answer this question that we have and we've been struggling with?" 'Cause then at that point, you sort of already have the user ready to use the, the answer that you have. And sometimes they also want help thinking about how could they roll things out in a way that would make it easier to evaluate. But there are just so many great people working hard that, really understand the local context and really have the trust of the farmers. So we are, usually well-advised to work through them as opposed to trying to tell them what they should be doing.
[00:31:44] Russ Altman: And that's a principle in personalized medicine as well.
[00:31:47] David Lobell: Yeah.
[00:31:47] Russ Altman: Well, thanks so much and congratulations on this work. Before we finish up, I wonder if you're ready for our Future in a Minute segment, where I'm gonna ask you five questions, and you'll give me basically five answers.
[00:31:58] David Lobell: Let's do it.
[00:31:59] Russ Altman: Okay. What is one thing that gives you the most hope for the future?
[00:32:04] David Lobell: All the great scientists I've met around the world who are working hard and often sacrificing a lot to help the most vulnerable people.
[00:32:11] Russ Altman: What's one thing you want people to walk away from this episode remembering?
[00:32:16] David Lobell: Data can help us farm much smarter, and we really need to continue getting better at farming if we want to avoid a lot of problems that come without that.
[00:32:25] Russ Altman: Aside from money, what is the one thing you need to succeed in your research?
[00:32:30] David Lobell: Smart and motivated students.
[00:32:32] Russ Altman: If all goes well, what does the future look like?
[00:32:35] David Lobell: Everyone has access to a healthy diet, and I'm gonna have to write a history book to tell people about, you know, the times when people went to war and cut down forests because they didn't have enough to eat.
[00:32:45] Russ Altman: And finally, if you were starting over again and you needed to get your degree or certification in a different discipline, what would it be?
[00:32:52] David Lobell: Probably genetics, although maybe history. I do like history a lot. And this is assuming I'm, I'm still six foot and not, you know, six eight, then I would have gone to the NBA.
[00:33:01] Russ Altman: Thanks to David Lobell. That was the future of farming. Thank you for listening to this episode. If while you were listening, someone popped into your head, go ahead and send them a message that they should subscribe to The Future of Everything so they can be alerted to every episode and learn about the future of everything. Please, if you're enjoying this also, don't forget that we have a back catalog filled with old episodes that can keep you busy for hours learning about the future.
[00:33:29] And of course, we want to remind you that we're available on social media where you can find me at LinkedIn, Threads, Bluesky, and Mastodon, where I'm @RBAltman or @RussBAltman. And you can of course follow the Stanford School of Engineering @StanfordSchoolOfEngineering, or more briefly @StanfordENG.
