 All right, guys, welcome to tonight's Technical Critical Assemblies with Dr. Ruth Fries. She's a professor of sustainable development in the Department of Ecology, Evolution, and Environmental Biology at Columbia University. So for us, it's such a treat as a group of architects to engage in dialogue and conversation with her and really understanding our roles with her expertise on planetary processes that's shaping true climate realities that we're working in today. Her work is very well known in the sense that it combines this deep knowledge of Earth processes and knowledge with the precise use of technological tools and imagery while maintaining perpetually a critical understanding of human and non-human policies, politics, communities, entanglements across multiple skills, ecosystems, and spatial conditions. So also, using the satellite imageries and field surveys in conjunction, she's able to, through her work, examine these critical issues like agriculture or human modifications of the planet, land use, food demand, biodiversity, et cetera, et cetera, and really giving us that as the situated context in which our work is part of this large network of activity. She publishes widely scientific and mainstream venues. She'll be discussing her book today with us, What Would Nature Do? A Guide for Our Uncertain Times. And in addition to her many, many actuaries, she is a member of the US National Science and Sciences of the Crop Reveller, the Board of Trustees, as the environment is funded by science, nature, and people, the world's wildlife fund, and she does a lot of work for conservation efforts in central India. So tonight, I'll stop talking here. We're so thankful for her time and expertise. And we welcome Ruth to tonight's technical assemblies. OK. Well, I'm going to echo. You sound fine to me. Sound OK? Yeah. OK. That's strong. OK. Everybody here OK? So it's really fun to be with you and share with you some thoughts that I've been thinking about for quite a few years and encapsulated in this book that I want to talk about and particularly fun to talk to you who are so engaged with the design of the human world and think together about what we learn from nature about how to help us think about how we design our human world. So I am going to. Hope this works. Get the chat up so I can see chatting. OK, does that look OK? Yes, we see your we see your slide. We see maybe your notes, too. I don't know if that matters. Oh, you see the notes. That shouldn't happen. Hang on. I'm so sorry. OK. I've done this 500 times. And I have to mess it up about that time. How about that? Now it's perfect. OK, great. Let me get the chat box up. OK, good. So so, you know, it's not. Doesn't take a lot of convincing after the year that we have had that we live in a very uncertain world, all kinds of shocks coming our way and that it is also not surprising after the year we've had that humanity is not particularly well equipped to to foresee to prepare for or to deal very well with the shocks when they happen. So what I wanted to do was think about how nature deals with prepares itself for shocks and has been able to survive for billions of years through shocks. And what we learn from that, those strategies for our own human constructed world. So I want to share those thoughts with you. But just to just to emphasize the point about how uncertain and unpredictable our world is, this is just pretty astounding that in 2019 pre pandemic, there was this rating of preparedness for global pandemics, the higher the value on the X axis here, the more prepared, the lower the value, the less prepared. So which country is most prepared according to this rating? The US. Which country is second most prepared? The UK. We all know what happened. So we don't do very well with foreseeing how well we can deal with shocks. Somalia at the very bottom here has reported something like only 260 deaths. So lots of shocks in store. So this pandemic was certainly a big one. The irony is that I wrote this book over the last five or six years or so, and I was just sending it into the publisher final version when the pandemic hit last March. So it was a bit of a scramble to put more in the book, but certainly proved the point that we live in uncertain times. Every time I turn around, there's another example of the uncertain times that we live in. We have Texas from the last couple of weeks and the climate extreme that happened there and the lack of preparedness and inability to deal with that situation very well. Of course, that resulted from a whole bunch of political issues in addition to the climate extreme. So there's many other examples of the uncertainty that we live in with fires in North America and Australia in fire-prone places. We know we have a future of climate extremes, hopefully not pandemics like we are going through now, but certainly there will be emerging diseases in the future, all kinds of uncertainties, political upheavals, and all of that becomes so much more intertwined and complex because of this incredibly interconnected world that we live with. And that is really how quickly goods and ideas and information, food, moves around the world is certainly nothing new that there are interconnections and trade and movement of ideas, but the degree to which the world is interconnected is a very new experience for humanity. This is just if we think of the existence of our species over the last hundreds of thousands of years. The way we live as an urban species, most people living in cities, meaning they're relying on someplace else to provide the food and the water and dispose the waste, this interconnection is new to humanity and creates what complexity scientists call a complex adaptive system, which means that basically unpredictable, all kinds of feedbacks and unintended consequences of any action we might take. So what I wanted to think about in this book was how nature has been able to persist over billions and billions of years with all kinds of shocks coming its way, asteroids crashing into the earth, extinctions, diseases, all kinds of uncertainties. And nature has persisted. It's not a foregone conclusion that life on Earth would persist and it's certainly not intentional or designed by some super being, but through evolution, these strategies have worked in nature because they work, because they allow nature to persist through uncertainties. So that's what I wanted to get out in the book and particularly think about how these strategies might apply to our human constructed world and how people are learning and incorporating their strategies in the economy and business and all kinds of different ways. So there are four strategies. So what I'm going to do is quickly go through them and maximize the time that we have for discussion. And some of them might be more or less applicable to what you all do, which is so amazing, you design the world. So the first strategy in nature that has a lot of implications for us is about how nature constructs its networks. So human civilization is incredibly reliant on networks of trade and movement of goods and movement of ideas and the internet and all kinds of networks that allow this urban world to supply itself with food and water and so on. Nature also is very dependent on networks from at all kinds of scales. So if you pick up a leaf vein next time you're outside, pick up a leaf vein and you look at it carefully and you will see that there's a lot of veins, a lot of very small, almost microscopic veins in a leaf. And that is a critical, like networks are critical to human civilization, that network in the leaf is critical to the survival of the plant because water needs to move throughout the leaf and sugars need to come back from chlorophyll photosynthesis that's going on in the leaf and back to the plant to supply sugars for growth. So it's critical that this network functions and it's also a cost to the leaf to build that network, those veins, because that's the supply materials and energy to construct those veins. So the problem with networks is they're fantastic unless something goes wrong. If there's a disruption at some part in the network like this inside, this is a kale leaf from my garden. If an insect takes a bite out of the leaf then the network, the movement gets disrupted and that's a real problem. So early in evolution of leaf veins, the strategy for the ginkgo tree, the oldest tree, is that you see this under here where it says early, a kind of not a loopy network. You see a very efficient network where there's a branching of networks but not this kind of loopiness and redundancy in the network that evolve later on in leaf veins. So what's the point? And that's a cost that doesn't look very efficient to have all of those leaf veins and invest in that redundancy in the network. But physicists have done work on this topic and shown that what those this loopy networks, redundancy in the networks is doing, it's providing resilience when there is a disruption somewhere in the leaf. So there are not just an alternative to get from point A to point B but multiple alternatives, many, many different ways to get from point A to point B. So if there is a tear or a bite taken out then there is still some redundancy in a different way to get around and to minimize the disruption. So interestingly enough, that is a concept that humans have figured out over time, was not always so. So this is Paul Barron, who is one of the famous people for his work that led to a functional internet. But when he was a young engineer at the RAND Corporation, his task was to advise the Defense Department and the communications, AT&T, this was doing the Cold War, on the communications network. So the problem was that there could be an attack somewhere in the network. So how do you design the communications network to be resilient against attack? So the thinking at the time was this centralized strategy where there's a center hub of communications, central command, and what Paul Barron worked on was the idea that that creates vulnerabilities, kind of like the Ginkgo Tree leaf strategy, where if there's an attack on that central hub, the whole network goes down. So what he advised, he looked at this decentralized strategy, which is kind of a hub and spokes kind of strategy, and a distributed strategy, which is a looping network, likely feigns, where there is, no matter where there would be an attack or disruption in the network, there would always be, once the whole thing comes down, there would always be an alternative route to get from point A to point B. So he went and presented this to the Defense Department and AT&T, and he was just laughed out of the room. This is just that he called them the graybeards. The graybeards just did not take him seriously. They said, this is a ridiculous idea. It costs because you have to invest in that redundancy. It just didn't. They didn't see that it made any sense. But Paul Barron continued to work on this strategy. And a decade or so later, the founders of the internet, when they were developing the ideas about how to create the communication structure for the network structure for the internet, they came upon his work and realized that this distributed strategy, likely feigns, is really what is needed to be able to have a functional internet. And that's what came to be. So over time, people are realizing that some inefficiency, some redundancy, is worth the cost. So in engineering now, this is quite an accepted concept. Redundancy in engineering to have multiple engines on a jet liner. And I don't think any of us would feel quite safe getting on a big airliner now, unless there was some redundancy in the number of engines in case something happens to one, then there are others to hopefully keep the plane flying. And that is a very accepted strategy. And even the idea of some design redundancy where engines are slightly different, design slightly different, or designed by different teams. So there is some insurance that there is some redundancy, and they don't all fail at once. So humanity is learning this lesson about some investment in redundancy, even though it's inefficient, and even though it's an extra cost, is worth it when the risk is high. There are other parts of our human constructed world that we haven't quite yet taken on that lesson about the value of redundancy in networks. And that is in our global food trade, which is actually going in the other direction, is becoming more concentrated so that more and more food is produced for the world in less and less places. And while that is efficient and makes food cheap and inexpensive and all of that is good, it also creates this vulnerability. And we've seen this vulnerability, if you remember, back to the price spikes in 2008 and 2011 when there was some climate extremes that occurred, droughts that occurred in these high producing areas of the world. And then the repercussions just cascade and ricochet throughout the world, leading to escalating prices and real hardship, and also feedbacks in the sense of being a complex system that then once the production goes down, the political response is to restrict exports. So then that's just a spiraling bad situation where food prices increase. And that's exactly what happened with the droughts, which led to price spikes, which led to export restrictions, which raised prices. And then there are urban consumers, particularly the urban poor, who spend a huge proportion of their income on food resulting in food riots. So this network, our global food trade network, is both good from the point of view of producing a lot of food and making food inexpensive by producing where it's efficient to produce, but also fragile. So how do we think about constructing our networks, all kinds of networks, whether they're communications networks or global food trade or the internet or all kinds of networks where it's possible to build in some redundancy so that in the case of the global food trade, countries are not solely reliant on a source that could be subject to extremes and lead to problems like how been doing these food riots. So that's one way of thinking about networks. Another way of thinking about networks is the other way. Networks can also be dangerous. I mean, we've seen the danger in information networks when disinformation can spread rapidly throughout a network. And we've certainly seen the danger of networks when we have a virus that emerged in a town in China spreading around the world in just a matter of days. So networks can be great for making things flow, but there are situations where you want to shut down a network when it's dangerous for materials, pathogens, information to flow across the network. So how do the social insects do this? They have this problem, like the ants and the termites who live millions and millions of individuals like cities in colonies. So they have the problem that if a pathogen gets into a colony, and it spreads, they would be devastated. They have ways to deal with this, like things that we wouldn't think about doing, like hauling away the sick and things like that. But they also have some really clever network strategies to minimize the spread of pathogens. And pandemics or epidemics don't happen all that often in beehives and termite colonies. And one of the reasons why not is because their social structure, their social network, is modular. So they have specialized tasks. And the ones that have the same task just have their own module, have their own part of their social network. So as soon as there is a pathogen that comes into the colony, they can shut down the whole module. So they have to shut down a few links rather than everybody being connected to everybody else. And leading to spread of the pathogen. So this is the same idea as constructing our pods of family and friends and only communicating or interacting with them during the pandemic. Same idea of a modular structure or banning travel between countries. Same idea of trying to find those links to cut that would stop the transmission. But the social insects are much better at it than we are. So the thinking here about networks is how to think about the structure of networks, modular structure, or loopy structure, or small world structure, different kinds of structures of networks that are appropriate for the benefits of networks, which is to keep the things flowing that you want to flow and also able to shut down when there is danger from networks. So keeping the benefits and minimizing the downside. So nature has figured out some ways to construct or have the architecture of networks that can persist through uncertainty. So that's one strategy. There are four strategies. I'll go through them quickly. A second strategy is what everybody knows and loves about nature is that nature is so diverse. We have millions and millions of species. We don't even know how many. But we know that there is a lot of diversity on this planet, diversity of life forms and genetic diversity and all kinds of different diversity. And it also is pretty clear that we don't really need all that diversity to survive. We could do without it for our function. Some species are really incredibly important, like pollinators and microbes in the soil that decompose waste. But we could probably get away without all of this diversity. So what's the value of this diversity? The value is that this diversity keeps options alive. It keeps like a library of options. So if one species goes extinct from a disease or some predator or some cause, then there are other species there to take its place. So this diversity has served nature well for billions of years so that when, for example, the asteroids crashed into the earth and created a blocked out the sunlight, then other life forms could become more prominent like mammals after the dinosaurs. So this diversity is a key feature for nature's ability to persist through uncertainties. And in many ways humans have taken that lesson on board, certainly in the world of finance where everybody knows that a smart investor will diversify his or her portfolio and not only diversify the investments but diversify the types of investments. So this was the Nobel Prize winning idea about a mixed portfolio so that you don't want a portfolio where you might have a diversity of, say, different railway securities, but they'd all be subject to the same shock if something occurred, so to invest across different types of investment that would be subject to different types of shocks. So that's the idea of diversified bed hedging very well accepted and also in the natural world, this diversity is important for example, these lizards in Hurricane Maria. So remember back in Hurricane Maria and the Caribbean a couple of years ago and the lizards, there are some really fascinating studies that have been done about which lizards survived the hurricane because it was really, really a big hurricane. A lot did not survive. So what was the difference between the ones that survived and the ones that didn't survive? The ones that survived had stickier topads so they could hang on better and they had thinner thighs so their thighs didn't billow as much in the wind so they were less likely to get blown away and they were more able to hang on. So that diversity within lizards, that diversity of characteristics within lizards, it was critical to the ability to survive through uncertainties like hurricanes. If there's not an extreme event, it doesn't matter but when extreme event occurs like Hurricane Maria then that diversity really pays off. Again, in our global food system, I do a lot on food systems so that's why all these examples of food systems, we're going in the opposite direction. That the diet for humanity is becoming more and more homogenized and more and more reliant on a small number of globalized crops. So just a handful of crops, a handful of species. We, rice, maize, a couple others provide most of the calories in the human diet. So we are putting ourselves at some vulnerability by not paying more attention to the diversity in the foods that we grow, the foods that people know how to cook, the foods that farmers know how to farm, different land races that are adapted to different kinds of conditions. We're going in the opposite direction of what we learn from lizards and what we learn from diversified bed hedging. So in some cases we're learning the lessons from nature and or realizing that that strategy is beneficial and in some case we go in the opposite direction. So third strategy is that nature is full of these just incredible examples about the ability to self-correct. And that is that these self-correcting mechanisms are embedded in many aspects of nature from global scale cycling of carbon in and out of the atmosphere to all the way down to cells and physiology. So in the carbon cycling, I won't drag you into the details of the carbon cycle, but the main point is that the amount of carbon dioxide in the atmosphere over geologic timescales is dependent on temperature because that determines how much rain dissolves in rainfall and takes CO2 out of the atmosphere. So when it's hot, there's a lot of evaporation. It rains a lot and there's a lot of CO2 that's pulled out of the atmosphere, so then it cools off because there's less greenhouse gases. When it's cool the other way, there's less rain, so there's more greenhouse gases that build up from volcanoes in the atmosphere and it warms up. So this is over geologic timescales and when you look at the long-term record of CO2 in the atmosphere, you see this homeostasis just within bounds, sort of cycling, not staying within these bounds. Unlike our neighboring planets, Venus, who has a runaway, had a runaway greenhouse effect and Mars that has all its carbon blocked up and it's too cold. So this self-regulating mechanism is really the reason why we're all here. Otherwise, life would not have been able to persist for so long. So we see these kinds of self-correcting features in predator prey dynamics. Everybody learns that in biology and in physiology, like the way our bodies regulate the amount of blood sugar through insulin, through different hormones that are released when blood sugar is too high and other hormones that are released when blood sugar is too low, so we have within bounds to stay within a safe zone. So nature is full of these examples of self-correcting features. And again, the finance world has really taken this lesson, not necessarily from nature directly, but realizing that this strategy is one that is really important to have stability when uncertain events happen. So we all know, now we all know, because a year ago, we were all hearing about the circuit breakers in the stock market that got tripped when the stock market started to plunge. So amazing how anyway, that's a whole other story about what's happened with the stock market during the pandemic, but it did at the beginning start to plunge and trip these circuit breakers. So what a circuit breaker is when there's too rapid of a fall in the stock market. Automatically, there's a shutdown and a halt, a pause for the market to stabilize and correct itself. So this mechanism of circuit breakers in the stock market came into being not that long ago. In the Black Monday, the crash of 1987, and you can see an example here when there was called flash crash in 2010, where if it had not been for that circuit breaker that got tripped with that rapid decline, then there could have been a worse outcome for the financial market. So we all read about the circuit breakers that went off last March, and they kept getting revised and they kept getting tripped. But this is really the same idea as the global carbon cycling or predator prey dynamics, that there is a self-regulating feature that automatically keeps within safe limits. Now in the stock market in our human constructed world, we have to build those self-correcting features. And we also have to maintain those self-correcting features when they exist in nature. So the fires that have been so devastating out west is an example of what happens when we ignore these self-regulating feedbacks that exist in nature and exist in this case, indigenous knowledge. So the fires have not been so extreme and damaging until European ideas of how to suppress fires came to the American West. And that was the Forest Service, who previously had this policy and this comes from Europe, that all fires are bad. They should all be put out by 10 AM the next day. And Smokey Bear, Smokey the Bear, some of you may know Smokey the Bear, he's very adorable, brought that message and propagated the idea that all fires are bad. But in nature, there's a really beautiful self-regulating mechanism where when the fuel load builds up, then there's always lightning or some cause for fire. Then there is a small fire which reduces the fuel load and then it builds up again. So there's this kind of homeostasis. But with the fire suppression that Smokey the Bear tells us about, the fuel load has built up over a century and we see the effect today combined with climate change and drier conditions. So we have some more uncertainty in store. So we kind of ignore these self-regulating feedbacks at our peril. Indigenous management of forests and fires, it was exactly that, having these small fires and then not having these large, big, devastating fires. So how do we think about building these kinds of self-regulating feedbacks into our human-constructed world? We see it in the finance. And how do we build that into other aspects of our civilization? So last one, then we can have a discussion, is this idea about enabling decisions from the bottom up. So you probably heard a lot about the tragedy of the commons, the idea that if there's common property, like common forests or common fisheries, then, and people can use them but don't own them, then that's going to result in disaster, the tragedy of the commons. That's the idea of Garrett Hardin from the late 60s. And that is certainly true. We see that with the atmosphere today, which is the common property and it's certainly a tragedy for all the stuff that gets dumped into the atmosphere. But Eleanor Ostrom, who was just this amazing person who won the Nobel Prize in economics, amazing for many reasons for her work and she was the first woman to win the Nobel Prize in economics and she's not an economist. She was a political scientist, passed away, sadly. But her work challenged this idea, challenged the idea that common resources are always going to get trashed. So she studied many, many different examples of where people self-organize to manage themselves, decide on the rules and manage themselves how to sustainably use the common properties. So she documented these examples with all kinds of things, starting out with groundwater in Los Angeles, community policing, fisheries, forestry, irrigation systems. She did not say that there is never a tragedy of the commons. What she did was she identified these conditions under which these decisions from the bottom up, self-organizing behavior can result in sustainable management of resources. And she has these eight design principles that lay out having the ability to control your own resource and enforce and these different principles that make it possible for these decisions, collective decisions designed from the bottom up, self-organized that can lead to very positive outcomes. And we see this and I think we see this more and more that we have so many examples of top-down central command, legislation and dictating from some far away place about how management should take place, whether it's a forest or whatever it is, and how that kind of top-down management isn't always the most effective because it's really not based on the reality of people on the ground who are in the best position to know their surroundings. So in nature, I don't think you can find any example of this top-down kind of strategy that seems so attractive to our species. A queen ant labeled the queen, that's a misnomer. A queen ant in the middle of a hive is not telling all the individuals where to go. She would not be able to do that. First of all, she wouldn't have that information and she wouldn't have the ability to know how to direct every single individual. So what has evolved in nature is many examples of self-organizing behavior like when you drop a crumb and ants first scramble around, it looks very disorganized and chaotic and then after just a little while they're marching in a straight line. It looks like there's an army, it looks like there's a queen or a general who's telling each individual to line up, but they're not. They are self-organizing just based on their own perception of their local situation. So they are following pheromones that are dropped by the ant in front of them and they are dropping pheromones for the ant behind them and just following their local conditions which results in this kind of self-organizing behavior. So there are many examples that Eleanor Ostrom has identified and others have identified where this kind of bottom-up self-organized behavior is works for human decisions. And if we think about our international climate negotiations which really are far from solving the problem of climate change, there were decades and decades of a kind of top-down thinking, dividing up the pie, some central authority, saying how much each country is able to omit, and then there was Paris which was a completely different strategy. That was a more bottom-up strategy where there was not a pie to divide up. There was bottom-up countries came to the negotiations with their own commitments about what they thought based on their individual circumstances they could commit to reducing their emissions of greenhouse gases. Now we all know that that's far from sufficient even if they did, even if all countries met their commitments that they brought to Paris it would still not be sufficient but it's the only time out of decades of lots of international negotiations where countries actually agreed. So this approach of bottom-up decisions is I think something we learned from nature we don't find top-down commands central authorities in nature. So that's my take on four strategies or secrets, not really secrets that has served nature well and that perhaps there are some lessons in there for us and it is certainly the case that we should think hard about how we're going to construct our human world for the uncertainties in political upheavals and climate extremes and pandemics and all kinds of ways that we can't even imagine that we face uncertainty in the future because we're such a complex interconnected system. So that I will thank you, I will stop sharing and look forward to any thoughts particularly about whether you think that these sorts of ideas are relevant for the kind of work you do which is so important in designing, designing how we live. Do you guys have any questions to start? Yeah, thank you so much for sharing that with us. Great, great content. I was also expecting number four, I have to be honest. I kind of saw some of the one, two, and three, once you said it was the other makes sense but bottom up, it makes sense in some elements but I wonder how it applies in the sense of averting disaster in the grander scheme of things. I can see how like a bottom up approach would be closely tied with a redundant network of sorts. Well, you don't have a centralized power dividing up the system, if you will, or whatever we're dealing with at the moment but if you could speak a little bit more about how bottom up is as a system in avoiding disaster. Yeah, thanks for that. And I think the way to think about it is that not every decision or investment that humanity needs to make should be bottom up because there's certainly some things that just don't make sense to be bottom up. Like for instance, developing a vaccine. I mean, there's no way that could happen in a bottom up sort of strategy. But then there are some aspects that might be more successful if it were bottom up. I don't know, I wanna think about what would happen if instead of this total crazy thing about wearing masks became so politicized and people locally got together had the right kind of information, had their own interest at stake and could develop their own rules of behavior. Would we have seen a different outcome? I don't know, maybe. Maybe people don't like being told what to do. So I think that's what our challenge is, is to identify what are the decisions and investments that humanity makes that need to be top down and what might be more successful with a bottom up strategy, like enabling a bottom up sort of strategy. And to me, that seems like what leadership is. Like being able to tell the difference. And when it makes sense to have bottom up self-organizing kind of behavior that would lead to potentially more successful outcome to allow that to happen. But then when it is required to have a top down strategy like investing in vaccines or building roads, I guess, things like that, then be able to tell the difference. I said building roads, but maybe I don't mean that. I think maybe communities should have more of a say in what roads get built in their communities. And David, yeah, definitely the whole power dynamics in human civilization is a confounding role here. But there are many examples that Eleanor Ostrom identified. Some of them being very local, like how self-contained communities, but some of them not. Like her first example that she studied in the 50s was about groundwater in Los Angeles and how it was really on its way to depletion. And the many different users of the groundwater the municipal and farmers and many different institutions got together and figured out how they're gonna collectively manage their groundwater because they all depend on it and they all depend on each other. So in a way Eleanor Ostrom's ideas seem a little quaint because she studied a lot of very self-contained like subsistence kinds of communities that are less and less prevalent in the world today. But she also studied community policing, for example, where it's not all subsistence type situation. So I don't, to me, that's what the leadership is, is being able to tell the difference between when bottom up could lead to enabling some bottom up self-organizing behavior could lead to possibly good outcomes. Thank you for that. I was sort of, I really loved your, I know you were saying you work a lot with food and especially some of the work with satellite imagery. I just wonder what, from your experience, what role does technology and how has it evolved in understanding sort of these networks where relationships say, sure, like maybe potentially using satellite imagery to understand land coverage or use, but especially since oftentimes technology seems like such a top-down tool, right? And oftentimes, how does that sort of reconcile maybe more of the sort of granularity and the intent of some of the policies even that we're trying to pursue? Yeah. So technology, meaning like remote sensing technology, satellite imagery technology is, it's becoming more and more public and available, but there's still an enormous barrier for people to benefit from it, but there are a lot of potential, a lot of benefits in the kind of food system arena around precision agriculture, which at this point is, you know, it's expensive. So well-off farmers can do it. That means having a sensor where you know exactly where your crops need fertilizer or exactly where to put water. So you're not just blasting it all over so it's more efficient. And that's a kind of technology that can really benefit lots of farmers around the world if it were available to them and more and more it is. So technology plays a huge role. Technology also, the other has created a lot of the problems that we have in the food system, the mechanization and, you know, irrigating crops where groundwater is getting depleted and all those things that technology has enabled is a double-edged sword. Technology is always a double-edged sword, but it's not the technology itself. It's how is it used and who's making the decisions about how it's used and who gets to use it. I wonder if there's like sort of examples, you know, like in which almost like technology adjusts to the community needs, like, you know, like the feedback loop is going the other way or if like special, especially, I know I see some of your papers where you study a lot of fires right in the Amazon. And, you know, especially with probably like indigenous communities, I wonder if there's sort of, you know, sort of a top-down approach on technology to community. There's examples in which communities sort of sort of collaboratively create technologies that maybe could even, you know, move a different direction. Yeah, I mean, there are indigenous communities in the Amazon who really embrace technology and embrace satellite data and being able to use it for all kinds of things to see where there's, you know, being able to enforce their own, you know, their land. So there's some real advantages to that. The fire issue is really a lot about health and what people are breathing. So all those emissions that go into the air and then people are breathing them. So this is the issue in Southeast Asia and huge issue in the Hays and Southeast Asia problems. Probably some of you are familiar with that because every year, especially during a dry season, when there are fires in Indonesia, they blow throughout Southeast Asia and big political transboundary problem and a really big public health problem. And similarly in the Amazon. So the ability to sort of track the fires and figure out where they're coming from, why they're happening and reducing them is certainly something that I think communities, benefit communities from the health point of view. Yeah, I mean, it seems like even examples that you like about, you know, traveling the health effects of fires, now there's like technology, we can sort of quantify how those movements, that those processes happen. And I guess there's probably, I mean, because of the new sort of visualizing of data, that there's new governmental, like governing structures and or sort of in how to even start to approach those questions. That's not by country or something. Yeah, yeah, so, but you know, it all, I've worked a lot on these issues and like try it, you know, figuring out how you can trace backwards and see where the fires are starting and all these sorts of things. But in the end, in the end, for real change to happen, I think the bottleneck is on the governance, the way we govern ourselves, the institutions that we create, how we use this technology, you know, we could have the best ability to observe everything and know all of these risks. We did, I mean, infectious disease scientists have been warning about a pandemic like this for a while. And it's not for their lack of identifying that this would eventually happen. It's the way we construct our institutions, which is a kind of a lot around the assumption that uncertainties and shocks, well, cannot happen. And if they do, we'll figure out a way to deal with them. Maybe since we're, you know, we're one minute left, but maybe we'll end with Emily's question. Emily, do you wanna pose your question to Ruth? Sure, you may have actually just answered it, but so you had mentioned COVID and that you had basically added or changed part of your book before releasing it. And I was wondering what exactly had you added or changed from the advent of COVID? Yeah, so it's funny that really it was, it was just a real mind-bender that I was sending in, literally sending in the final manuscript. And I had already had in the book the thing about the story about the social insects and the modular network structure to stop the spread of pathogens. So that was already in there. But how could I not add the example of coronavirus? So I quickly just, I added some more examples and I added something about the 1918 pandemic and I added of something more about the circuit breakers. So it wasn't that I changed any ideas, it was just that I had to incorporate what was happening into the examples, otherwise it would have looked very outdated. Okay, well, thank you everyone and especially to Ruth for joining tonight. Yeah, I would encourage everyone to check out the book in case you haven't already. And thank you so much Ruth for, I mean, some of these examples are just incredible. I love the LA Groundwater one and even those certain diagrams that you've shown with food security is just something for all of us to chew on. So yeah, have a good night everyone. Okay, thank you. So I hope the book is readable. The point, the idea was to take these concepts about complex systems and find narratives and make it accessible. And I don't know, it's somewhat fun to read but you can be the judge of that. Thank you everyone, good night. Okay, thanks a lot. Thank you.