Pushkin from Pushkin Industries. This is Deep Background, the show where we explore the stories behind the stories in the news. I'm Noah Feldman. Today I'm speaking to one of the most influential and extraordinary scientists I know, Eric Lander. Eric is the president and founding director of the Broad Institute of MIT and Harvard. He's geneticist, a molecular biologist, a mathematician by original training, and he's also the host of a brand new Pushkin podcast called Brave New Planet. Eric has been at the epicenter of a great transformation in biology and indeed of science that's taken place over the last thirty years. A transformation focused most fundamentally on what can be done with the gathering of greater and greater and greater amounts of data about biological systems, including the human body. These developments are crucial to how science is being done every day, and they're absolutely crucial as well to how science has responded to COVID nineteen. It's a thrill to have Eric on the podcast. Eric, thank you so much for joining us. I want to start with the role you've played in really a transformative period in the history of modern science, a period which in certain ways, is being reflected in the cutting edge developments that are happening every day that we all care about most in science, including indirectly in the context of the vaccines for COVID nineteen. And that's a period in which big data has come to be a fundamental, some would say, the fundamental tool for solving our biggest scientific problems. You came across this already when you're working on the human genome project, but then it's been your central focus and your creation of the broad Now. I know this is a big picture question, but I wonder if you would just how a few bars, if you would for the audience about how this transformation in the way we think about what science is and how it works has come home. Now, Wow, what a small question to start with. No othing. I think there's a kind of high school cartoon version of what science is which runs something like this, Scientists make a hypothesis and then they set up a test, and then they test their hypothesis and see if it holds up or they should reject it. I think it misses a fundamental question where do hypotheses come from? Anyway, And many of the most important hypotheses come from just looking at the world. And what's happened in the last twenty thirty years in biology is we've been able to take almost entirely unbiased looks at parts of biology. The human genome was the first great example of that three billion letters of human instructions, and rather than diving in with a hypothesis I think this gene causes cystic fibrosis or some other aspect of a disease, you can ask questions like, amongst every gene in the genome, which ones show an inheritance pattern that matches up with cystic fibrosis, And instead of being limited to hypothesis driven science, you can do what some people you know call hypothesis free science. We're never free of hypothesis, but the limits are removed so much it's changed the way we approach biology because it's sort of big data. But what I really think about it is the big data is that life keep notes in its lab notebook, the genome, and in this generation, we've got access to that lab notebook and we can read and the questions we can ask are only limited by our creativity. Translating that into practical terms, how for example, today when scientists can affronted sars Covi two and said, okay, let's figure this out and then let's find something to do about it. How did their approach differ from the way it would have looked, say twenty five or thirty years ago, or four years ago actually in this case, so let me give you an example. There is something called the Human cell Atlas. It's probably this generation's successor to the Human Genome Project. The Human Genome Project was reading out all the genetic information in a human The Human Cell Atlass was reading out what are all the cells in the human body? By asking which of the twenty thousand genes are turned on in this cell or that cell. It became possible and eight years ago to start reading at a single cell basis the genes that are turned on and by how much in first dozens of cells, then thousands of cells, then millions of cells, and eventually it'll be billions of cells. And an international catalog. International program to create that catalog describing all possible cells and their expression patterns of genes and the states they find themselves in just caught fire around the world. So then stars comes along and people ask what cells might sars Covie two in fact, well, it was known that the previous coronavirus SARS, infected cells that had a particular gene that was active goes by the name ACE two. But that doesn't matter. People quickly figured out that the same gene was used as the receptor for the new coronavirus. And then you wanted to ask the question, what's every cell in the body that expresses the receptor for the new coronavirus. Well, in ancient times, meaning four years ago, one would have had to have done thousands of experiments to figure that out. Instead, the scientific community came together and then a matter of two weeks, sifted through all the data about which genes are on and off in which cell types to say, oh, yes, here are the different cell types that might be infectable. And you know, one of the things they found was the smell receptors in your nose. They made that discovery and then three days later people reported that people were losing their sense to smell when infected by the virus. Bingo. The idea that we have lookup tables, Yeah, pretty good now, but much much better in the coming years. For every cell in our body is going to mean that any process, whether it's a virus that's infecting us or some other physiological process, we're going to be able to look up signatures for it. It doesn't solve all problems, that doesn't make a disease go away, but maybe it cuts a year or more off the work. I guess an older example would be chemistry before there was a periodic table of the elements. In chemistry, after there was a periodic table of the elements, didn't solve all chemistry, but no chemists thought about chemistry the same way after the periodic table was in evidence. Do the mRNA vaccines that are in development and that have been so far attested in what looks like a very promising way to address SOARS covy two infection themselves owe something to these revolutions in biology My impressions that they do. Oh yeah, of course, How did anybody find this sarscovy two virus so quickly? You know, establishing what was the virus behind AIDS HIV took quite a long time. Even establishing some of these other more recent novel virus that have appeared have taken a long time. Now, with kind of a hypothesis free brute force sequencing approach, you could take cells from infected patients, sequence the genes that are getting expressed, and say, WHOA, are there any genes here that aren't supposed to be in humans? And when you sift the genes you see in the cells versus the genes you expect in the cells, the difference kind of turns out to be this virus that's infecting you. You didn't need to go in with the hypothesis that it wasn't necessarily a coronavirus, or that you were looking for a particular kind of gene. You could go in saying I think there's a virus to look for what novel stuff is getting expressed. So it's a great example of the ability to make discovery science by looking at the big picture in a comprehensive way. Kind of global views of biology have become possible, and they depend on people generating data, making those data freely available, a whole new generation of scientists growing up who live to analyze those kind of data, and incredible creativity because you'd think, oh, there's a big pile of data, you just crunched it through the computer. But given a big pile of information, you can ask a thousand different questions and it depends on the perspective you're bringing. So I'm just in awe of the creativity that people bring to these questions. I think at the beginning people thought, oh, all this data are boring, But of course they're an invitation for incredible diversity of intellectual questions. This is a philosophical question. But do you think that the changes that we've seen in these recent decades count as not just an evolution in the way the biology has done, but in fact as a revolution, especially with respect to being able to do something different than saying, here's our hypothesis. Now, let's search instead being able to look at a huge body of data and say, well, what are the associations? What are the associations across the genome. Let's drill down and see which ones turn out to be real and which ones turn out not to be real. At that point you can form my hypothesis. But as it were, the hypothesis comes from the associations. Yeah. I think people can fight over whether you should choose the word revolution, but it seems to me anything that radically changes your perspective deserves to be called a revolution. And this idea that we used to have that we'd be good at guessing what are the processes responsible for cystic fibrosis, or heart disease or schizophrenia, you know, just a mystery locked in people's brains. The idea that we're supposed to guess that based on some prior knowledge of biology was I think, doing biology with your hands tied behind your back. The idea that we could range across the genome and ask why there genetic variations anywhere more frequently found in people who have schizophrenia, Well it turned out that instead of finding one gene, it's pointed now to two hundred and sixty five genes across the genome that play roles. But no forward make a hypothesis based on prior knowledge could possibly have produced that picture. And biologists at some point argued over this new way of thinking, and now, as usual, they've just absorbed it into the way biologists think. But looking back, it was a shift that took place in the eighties and nineties and really took hold in the first decade of this century. You know, intellectual shifts like that are quite amazing. You know. I were still run a laboratory, and one of my students at some lab meeting a couple of years ago, was listening to a description and he just turned and he said, before you knew the sequence to the genome, how did you do anything? Of course lots got done, but it was the sign of what what intellectual progress is, which it so completely infects the way you think about things that you assume it's been in the woodwork forever. We'll be right back, Eric. I want to ask you about how the institutions that enable science to be done have been changing as a consequence of the apocal change in the cognitive part of science that you're describing. Your institute that you're the founding director of, the Broad Institute is a great example. It's tremendously influential throughout the areas of science which it touches upon, and it touches upon many areas of science. It's extremely well funded, it's not subordinated to the universities that it's affiliated with Harvard and m T the way a traditional institutent have been. And to be blunt, it's enormously powerful in the world of science. How coincidental is the evolution of the Broad to the developments you're talking about. I mean, had you started the Broad and it's not been the way science was done would it have been as significant? And similarly, had you not started the Broad But had these scientific developments occurred, could they have occurred with the same speed and efficiency Starting the Broad Institute it was a response to these scientific changes. The Broad was an answer to these new intellectual possibilities. But the word that you didn't mention, which I think, is that the heart of all of it is collaboration. We use the word collaboration lightly. It's doing anything as we collaborate with somebody. No, no, there's a sense of deep collaboration that underlies this new era of science. So you know, what the Broad really is is an intellectual meeting ground. What the Broad is about is a collaborative spirit that is I think necessary to take full advantage of where science is going right now. Everything else follows from that. I totally buy that collaboration is kind of the special sauce. It's also true, though, that once there is a site of collaboration, that site of collaboration can become tremendously empowered. I mean, think of a trading zone in ancient civilizations or even in modern civilizations. So if you find a spot where cultures converge in collaboration becomes possible, that place becomes enriched and becomes powerful. You know, Venice might be the classic example. It's a kind of crossroads of East and West a certain moment in history, and then tremendous wealth and power accrue in Venice. And I guess what I'm wondering about is as the resources needed to do biology at the highest level have become greater and greater, doesn't that empower the institutions that are at the center, that are the collaboration crossroads that can raise the funds and then everyone really wants to get a part of the action, which seems justifiable and good for science. I'm not objecting to this, I'm just trying to describe it. And no, I think biology is just much more diverse than that. There are so many different ways to do biology. As much as I champion the rise of the ability to generate large data and learn from it, it's one lens on biology. It's probably fair to say that ninety five percent of biological discovery today still is going on in traditional laboratory structures, and they are dramatically empowered by the fact that the five percent of places that are really into the let's generate large data and analyze it all that put the data freely out there because they use it. So the traditional biological laboratory, which remains an incredibly powerful model, it becomes a solid foundation that saves them tons of work. I think what this has done is this has allowed different approaches to grow up and interact, and it will continue to change. I don't see anything close to a monopoly of approach or a monopoly of power in modern biology, because a biology is way too rich for that. One of the consistent themes in your fascinating career, Eric is that you've been constantly in touch with as an advisor to or interacting with government. You've also been part of the broader field of academic science, always centrally, and you've also touched on the private sector corporate part, which is one of the three legs, as it were, of contemporary science. How do you see the relationship between those different moving parts changing. We all still very much have the COVID vaccine race in our minds, in which you've had government playing sum roble, you've had private sector, you've had academic centers. So that might be a concrete example to use, although you feel free to use others too. You're describing a model that was laid out in the closing months of World War two. Very famously. Franklin Roosevelt, a couple of weeks after his reelection in nineteen forty four, wrote to his science advisor Veniva Bush, saying, boy, this science and technology stuff's been pretty helpful in bringing the war at least a successful direction. Then and eventually conclusion, how can it make a big difference in peacetime? And Bush wrote this report that is sort of known as a foundational text, Science, Science, the Endless Frontier, and it laid out and eventually shaped a world in which we have three pieces. We have government, we have academia, we have industry. And there's this virtuous cycle where Bush said in this report scientific discovery, which during the war had been going on in government labs, it should go on in universities, and it should go on in the context of training the next generation. And governments should fund academia to make basic knowledge fundamental knowledge and make it broadly available. Industry is then able to pick up that knowledge and turn it into private goods, private products. And this virtuous cycle I've written about it, and I called it like this miracle machine is something that the United States perfected before and better than any other country of how these pieces work off each other. As an academic, I understand that our goal is create knowledge and make it broadly available. But I also know that it's never going to complete its mission if it doesn't get to patients, and so academia has to work with industry and government tests to think about what should its policies be on funding. But understanding that balance of those three partners in trying to create social products to make society healthier, wealthier, and more secure, I think it's really important to think about that. You depict a somewhat rosy picture there, and I think for those of us just coming out of we're not quite out of it yet, but a Trump administration viewing an administration that was deeply skeptical of science in a whole range of ways, from climate ultimately to the epidemiologists advice on how to handle COVID, and then which finally circled back to but we're doing such a great job because we're facilitating the emergence of vaccines. Left a lot of us skeptical about the productive role that government can play, and then apart from that, a lot of us have independent skepticism of the tremendous power of private companies. Is there anything you would say that's more critical about the relationship rather than that it's it is still the miracle machine that it was depicted as being in the rosy, good old Dask Miracle machines need a lot of tending and repair and care. They don't always get them right. I think, you know, we'll stand back with enough distance and see what things got done wrong and what lessons we can learn and what things got done right. I'm thinking at a broader level, do we have the model right? And I think the model surely needs repair at many levels, but I don't think it's fundamentally wrong. I think more fundamental science is getting done in industry that's really important. I think, yes, we've seen instances where the government has engaged in denying obvious scientific facts. Not a good thing. But I don't think there's any reason to think that that's a permanent condition. I would point to a constant revision of this model. Science does not sit on its laurels. It's always edgy, and as soon as Veneva Bush laid out his early model, there were efforts to rethink it and change it. If you ask me, do I think we're in for a period when there's both enormous need an enormous opportunity to rethink those things. Yes, absolutely. But the fundamental idea that this is one of the great engines of producing progress for society I very much agree with, and that makes it worth the trouble of figuring out how it needs to be fixed and changed and improved. Eric, You've done something pretty unusual for someone in your August position, which is that you started a podcast, Brave New Planet, I should say for disclosure purposes, produced by Pushkin, which also produces this show. Tell me why I have to say, I mean, it's someone who's relatively new to podcasting figures. I'm learning a little bit every day, make two mistakes for every step forward. I was kind of heartened to hear that you were doing it because I know that whatever you do your due to the highest standard. And sure enough, it's a great podcast. But why why did you decide to devote significant time to that pursuit. Well, it's actually related to what we're just talking about. I really do believe in this compact between science and society, and I do think it's frayed in certain ways. And so for me, Brave New Planet, which is seven episodes that try to take on really hard problems where I don't know what the answer is, deep fakes, for example, solar geoengineering. Should we engineer the Earth's atmosphere to mitigate climate change? Lethal autonomous weapons? Should we have killer robots? Biases? And predictive algorithms? And new technology is called gene drives to reshape species in nature. And what Brave New Planet is about is smart, thoughtful, passionate people trying to grapple with what should we do? People who agree on the facts, agree on the societal goals, and then don't agree on the solutions because they're hard. Brave New Planet as the tagline utopia or dystopia. It's up to us, and I think that's right. I mean, there are gonna be a lot of consequential decisions about science and technology that if we make wise choices, could leave us a lot better off, and if we don't make wise choices could leave us a lot worsolve. Brave New Planet was an invitation for that kind of a conversation and I hope we're gonna have a lot more of it. Eric let last question, and it derives from that tagline utopia or dystopia. It's up to us. There's a theme that I sense in you are thinking about your work over the last decades and in the direction where things are going now. I see you as on the whole an extremely optimistic, positive person. But I actually wonder if that might be one of the many secrets to your extraordinary success, that you're looking optimistically and what can come next, and how change can be productive, and how institutions can be evolved to make them better. And yet that word dystopia is still lingering there as a much more potentially You're not saying it will be dystopic, but a much more potentially worrisome picture of how our world is evolving, and particularly coming out of extraordinary technological innovations, of which big data biology is only one. So how do you think about the big picture risks that we face really as a society or as a civilization, which you know, at least when you go to Silicon Valley you hear a lot of smart people with a big steak in the future, very very worried about what their technologies are capable of producing. Look, I am an optimist, but I am a very realistic optimist. I'm not Poyanna that everything works out well automatically. You have to work really hard to make sure that you get the upsides. So, as a realistic optimist, every one of the episodes of Brave New Planet starts with all of the upsides that could come from something, and then pivots part way through the show to exactly the same question what could possibly go wrong? And it then unfolds layer after layer of how things can go off the rails, and in some cases are going off the rails. I try to be just completely clear eyed. There aren't quick fixes, but we do need fixes, and so that balance is something You're right. I could not do what I do without being deeply optimistic, and I couldn't do it responsibly without being deeply realistic. Eric. Thank you for the extraordinary work that you have been doing, that you're still doing, that you're going to continue to do. And thanks for coming in talking about it with me on deep background. Thank you a real pleasure. Noah, take care. Eric Lander is not only a tremendously influential figure in science, He's also a very, very talented science explainer, and I was thrilled that we had that on display here in the podcast as he talked about the transformation in biology, the emergence of what some have sometimes called hypothesis free science, which is really about forming hypotheses in new ways. For scientists and for me, listening to him describe these developments, it is really extraordinary to hear just how basic they've become, to how biologists can respond to real time crises like the crisis caused by Czars Cove two. At the same time, all transformations in scientific institutions drive changes in how power is deployed and how power functions, And although Eric preferred to emphasize the ways that power is spread out across the biological community, it's also true that big data science inevitably has some concentrating effects on those people, places, and institutions where the best and most cutting edge techniques can be found and consolidated, and Eric has been at the center of that development as well. Finally, I was very struck by the carefulness with which Eric addresses the problem of whether science is on the whole today bringing us in a better direction, or has the capacity to throw us into dystopia. I think it's highly significant that for his podcast Brave New Planet, Eric is exploring specifically technologies and scientific developments that have the capacity to go very, very wrong. He's a realist about how to try to fix those developments because they can't be put back in the bottle. I tend to agree with that instinct towards realism. Yet he knows that we cannot do the right thing unless we think hard about what the right thing to do, in fact is. In this moment, we're feeling or about to feel, tremendous gratitude to science for what it's accomplished with respect to a vaccine for Stars Covey two. Maybe we're not quite there yet, but it's entirely possible that we will be very grateful to science relatively soon. That gratitude will also call for common sense analysis of what the risks are and the downsides are of trusting the scientific community too much in terms of its response to a range of the most difficult social, political, and health problems facing us today. Until the next time I speak, you, be careful, be safe, and be well. Deep background is brought to you by Pushkin Industries, our producer is Lydia Gencott, our engineer is Martin Gonzalez, and our showrunner is Sophie Crane mckibbon. Theme music by Luis Gera at Pushkin. Thanks to Mia Lobell, Julia Barton, Heather Faine, Carlie mcgliori, Mackie Taylor, Eric Sandler, and Jacob Weisberg. You can find me on Twitter at Noah Arfeld. I also write a column for Bloomberg Opinion, which you can find at bloomberg dot com Slashfelder. To discover Bloomberg's original slate of podcasts, go to Bloomberg dot com slash podcasts, and if you liked what you heard today, please write a review or tell Afrah this is deep background

Pushkin from Pushkin Industries. This is Deep Background, the show where we explore the stories behind the stories in the news. I'm Noah Feldman. Today I'm speaking to one of the most influential and extraordinary scientists I know, Eric Lander. Eric is the president and founding director of the Broad Institute of MIT and Harvard. He's geneticist, a molecular biologist, a mathematician by original training, and he's also the host of a brand new Pushkin podcast called Brave New Planet. Eric has been at the epicenter of a great transformation in biology and indeed of science that's taken place over the last thirty years. A transformation focused most fundamentally on what can be done with the gathering of greater and greater and greater amounts of data about biological systems, including the human body. These developments are crucial to how science is being done every day, and they're absolutely crucial as well to how science has responded to COVID nineteen. It's a thrill to have Eric on the podcast. Eric, thank you so much for joining us. I want to start with the role you've played in really a transformative period in the history of modern science, a period which in certain ways, is being reflected in the cutting edge developments that are happening every day that we all care about most in science, including indirectly in the context of the vaccines for COVID nineteen. And that's a period in which big data has come to be a fundamental, some would say, the fundamental tool for solving our biggest scientific problems. You came across this already when you're working on the human genome project, but then it's been your central focus and your creation of the broad Now. I know this is a big picture question, but I wonder if you would just how a few bars, if you would for the audience about how this transformation in the way we think about what science is and how it works has come home. Now, Wow, what a small question to start with. No othing. I think there's a kind of high school cartoon version of what science is which runs something like this, Scientists make a hypothesis and then they set up a test, and then they test their hypothesis and see if it holds up or they should reject it. I think it misses a fundamental question where do hypotheses come from? Anyway, And many of the most important hypotheses come from just looking at the world. And what's happened in the last twenty thirty years in biology is we've been able to take almost entirely unbiased looks at parts of biology. The human genome was the first great example of that three billion letters of human instructions, and rather than diving in with a hypothesis I think this gene causes cystic fibrosis or some other aspect of a disease, you can ask questions like, amongst every gene in the genome, which ones show an inheritance pattern that matches up with cystic fibrosis, And instead of being limited to hypothesis driven science, you can do what some people you know call hypothesis free science. We're never free of hypothesis, but the limits are removed so much it's changed the way we approach biology because it's sort of big data. But what I really think about it is the big data is that life keep notes in its lab notebook, the genome, and in this generation, we've got access to that lab notebook and we can read and the questions we can ask are only limited by our creativity. Translating that into practical terms, how for example, today when scientists can affronted sars Covi two and said, okay, let's figure this out and then let's find something to do about it. How did their approach differ from the way it would have looked, say twenty five or thirty years ago, or four years ago actually in this case, so let me give you an example. There is something called the Human cell Atlas. It's probably this generation's successor to the Human Genome Project. The Human Genome Project was reading out all the genetic information in a human The Human Cell Atlass was reading out what are all the cells in the human body? By asking which of the twenty thousand genes are turned on in this cell or that cell. It became possible and eight years ago to start reading at a single cell basis the genes that are turned on and by how much in first dozens of cells, then thousands of cells, then millions of cells, and eventually it'll be billions of cells. And an international catalog. International program to create that catalog describing all possible cells and their expression patterns of genes and the states they find themselves in just caught fire around the world. So then stars comes along and people ask what cells might sars Covie two in fact, well, it was known that the previous coronavirus SARS, infected cells that had a particular gene that was active goes by the name ACE two. But that doesn't matter. People quickly figured out that the same gene was used as the receptor for the new coronavirus. And then you wanted to ask the question, what's every cell in the body that expresses the receptor for the new coronavirus. Well, in ancient times, meaning four years ago, one would have had to have done thousands of experiments to figure that out. Instead, the scientific community came together and then a matter of two weeks, sifted through all the data about which genes are on and off in which cell types to say, oh, yes, here are the different cell types that might be infectable. And you know, one of the things they found was the smell receptors in your nose. They made that discovery and then three days later people reported that people were losing their sense to smell when infected by the virus. Bingo. The idea that we have lookup tables, Yeah, pretty good now, but much much better in the coming years. For every cell in our body is going to mean that any process, whether it's a virus that's infecting us or some other physiological process, we're going to be able to look up signatures for it. It doesn't solve all problems, that doesn't make a disease go away, but maybe it cuts a year or more off the work. I guess an older example would be chemistry before there was a periodic table of the elements. In chemistry, after there was a periodic table of the elements, didn't solve all chemistry, but no chemists thought about chemistry the same way after the periodic table was in evidence. Do the mRNA vaccines that are in development and that have been so far attested in what looks like a very promising way to address SOARS covy two infection themselves owe something to these revolutions in biology My impressions that they do. Oh yeah, of course, How did anybody find this sarscovy two virus so quickly? You know, establishing what was the virus behind AIDS HIV took quite a long time. Even establishing some of these other more recent novel virus that have appeared have taken a long time. Now, with kind of a hypothesis free brute force sequencing approach, you could take cells from infected patients, sequence the genes that are getting expressed, and say, WHOA, are there any genes here that aren't supposed to be in humans? And when you sift the genes you see in the cells versus the genes you expect in the cells, the difference kind of turns out to be this virus that's infecting you. You didn't need to go in with the hypothesis that it wasn't necessarily a coronavirus, or that you were looking for a particular kind of gene. You could go in saying I think there's a virus to look for what novel stuff is getting expressed. So it's a great example of the ability to make discovery science by looking at the big picture in a comprehensive way. Kind of global views of biology have become possible, and they depend on people generating data, making those data freely available, a whole new generation of scientists growing up who live to analyze those kind of data, and incredible creativity because you'd think, oh, there's a big pile of data, you just crunched it through the computer. But given a big pile of information, you can ask a thousand different questions and it depends on the perspective you're bringing. So I'm just in awe of the creativity that people bring to these questions. I think at the beginning people thought, oh, all this data are boring, But of course they're an invitation for incredible diversity of intellectual questions. This is a philosophical question. But do you think that the changes that we've seen in these recent decades count as not just an evolution in the way the biology has done, but in fact as a revolution, especially with respect to being able to do something different than saying, here's our hypothesis. Now, let's search instead being able to look at a huge body of data and say, well, what are the associations? What are the associations across the genome. Let's drill down and see which ones turn out to be real and which ones turn out not to be real. At that point you can form my hypothesis. But as it were, the hypothesis comes from the associations. Yeah. I think people can fight over whether you should choose the word revolution, but it seems to me anything that radically changes your perspective deserves to be called a revolution. And this idea that we used to have that we'd be good at guessing what are the processes responsible for cystic fibrosis, or heart disease or schizophrenia, you know, just a mystery locked in people's brains. The idea that we're supposed to guess that based on some prior knowledge of biology was I think, doing biology with your hands tied behind your back. The idea that we could range across the genome and ask why there genetic variations anywhere more frequently found in people who have schizophrenia, Well it turned out that instead of finding one gene, it's pointed now to two hundred and sixty five genes across the genome that play roles. But no forward make a hypothesis based on prior knowledge could possibly have produced that picture. And biologists at some point argued over this new way of thinking, and now, as usual, they've just absorbed it into the way biologists think. But looking back, it was a shift that took place in the eighties and nineties and really took hold in the first decade of this century. You know, intellectual shifts like that are quite amazing. You know. I were still run a laboratory, and one of my students at some lab meeting a couple of years ago, was listening to a description and he just turned and he said, before you knew the sequence to the genome, how did you do anything? Of course lots got done, but it was the sign of what what intellectual progress is, which it so completely infects the way you think about things that you assume it's been in the woodwork forever. We'll be right back, Eric. I want to ask you about how the institutions that enable science to be done have been changing as a consequence of the apocal change in the cognitive part of science that you're describing. Your institute that you're the founding director of, the Broad Institute is a great example. It's tremendously influential throughout the areas of science which it touches upon, and it touches upon many areas of science. It's extremely well funded, it's not subordinated to the universities that it's affiliated with Harvard and m T the way a traditional institutent have been. And to be blunt, it's enormously powerful in the world of science. How coincidental is the evolution of the Broad to the developments you're talking about. I mean, had you started the Broad and it's not been the way science was done would it have been as significant? And similarly, had you not started the Broad But had these scientific developments occurred, could they have occurred with the same speed and efficiency Starting the Broad Institute it was a response to these scientific changes. The Broad was an answer to these new intellectual possibilities. But the word that you didn't mention, which I think, is that the heart of all of it is collaboration. We use the word collaboration lightly. It's doing anything as we collaborate with somebody. No, no, there's a sense of deep collaboration that underlies this new era of science. So you know, what the Broad really is is an intellectual meeting ground. What the Broad is about is a collaborative spirit that is I think necessary to take full advantage of where science is going right now. Everything else follows from that. I totally buy that collaboration is kind of the special sauce. It's also true, though, that once there is a site of collaboration, that site of collaboration can become tremendously empowered. I mean, think of a trading zone in ancient civilizations or even in modern civilizations. So if you find a spot where cultures converge in collaboration becomes possible, that place becomes enriched and becomes powerful. You know, Venice might be the classic example. It's a kind of crossroads of East and West a certain moment in history, and then tremendous wealth and power accrue in Venice. And I guess what I'm wondering about is as the resources needed to do biology at the highest level have become greater and greater, doesn't that empower the institutions that are at the center, that are the collaboration crossroads that can raise the funds and then everyone really wants to get a part of the action, which seems justifiable and good for science. I'm not objecting to this, I'm just trying to describe it. And no, I think biology is just much more diverse than that. There are so many different ways to do biology. As much as I champion the rise of the ability to generate large data and learn from it, it's one lens on biology. It's probably fair to say that ninety five percent of biological discovery today still is going on in traditional laboratory structures, and they are dramatically empowered by the fact that the five percent of places that are really into the let's generate large data and analyze it all that put the data freely out there because they use it. So the traditional biological laboratory, which remains an incredibly powerful model, it becomes a solid foundation that saves them tons of work. I think what this has done is this has allowed different approaches to grow up and interact, and it will continue to change. I don't see anything close to a monopoly of approach or a monopoly of power in modern biology, because a biology is way too rich for that. One of the consistent themes in your fascinating career, Eric is that you've been constantly in touch with as an advisor to or interacting with government. You've also been part of the broader field of academic science, always centrally, and you've also touched on the private sector corporate part, which is one of the three legs, as it were, of contemporary science. How do you see the relationship between those different moving parts changing. We all still very much have the COVID vaccine race in our minds, in which you've had government playing sum roble, you've had private sector, you've had academic centers. So that might be a concrete example to use, although you feel free to use others too. You're describing a model that was laid out in the closing months of World War two. Very famously. Franklin Roosevelt, a couple of weeks after his reelection in nineteen forty four, wrote to his science advisor Veniva Bush, saying, boy, this science and technology stuff's been pretty helpful in bringing the war at least a successful direction. Then and eventually conclusion, how can it make a big difference in peacetime? And Bush wrote this report that is sort of known as a foundational text, Science, Science, the Endless Frontier, and it laid out and eventually shaped a world in which we have three pieces. We have government, we have academia, we have industry. And there's this virtuous cycle where Bush said in this report scientific discovery, which during the war had been going on in government labs, it should go on in universities, and it should go on in the context of training the next generation. And governments should fund academia to make basic knowledge fundamental knowledge and make it broadly available. Industry is then able to pick up that knowledge and turn it into private goods, private products. And this virtuous cycle I've written about it, and I called it like this miracle machine is something that the United States perfected before and better than any other country of how these pieces work off each other. As an academic, I understand that our goal is create knowledge and make it broadly available. But I also know that it's never going to complete its mission if it doesn't get to patients, and so academia has to work with industry and government tests to think about what should its policies be on funding. But understanding that balance of those three partners in trying to create social products to make society healthier, wealthier, and more secure, I think it's really important to think about that. You depict a somewhat rosy picture there, and I think for those of us just coming out of we're not quite out of it yet, but a Trump administration viewing an administration that was deeply skeptical of science in a whole range of ways, from climate ultimately to the epidemiologists advice on how to handle COVID, and then which finally circled back to but we're doing such a great job because we're facilitating the emergence of vaccines. Left a lot of us skeptical about the productive role that government can play, and then apart from that, a lot of us have independent skepticism of the tremendous power of private companies. Is there anything you would say that's more critical about the relationship rather than that it's it is still the miracle machine that it was depicted as being in the rosy, good old Dask Miracle machines need a lot of tending and repair and care. They don't always get them right. I think, you know, we'll stand back with enough distance and see what things got done wrong and what lessons we can learn and what things got done right. I'm thinking at a broader level, do we have the model right? And I think the model surely needs repair at many levels, but I don't think it's fundamentally wrong. I think more fundamental science is getting done in industry that's really important. I think, yes, we've seen instances where the government has engaged in denying obvious scientific facts. Not a good thing. But I don't think there's any reason to think that that's a permanent condition. I would point to a constant revision of this model. Science does not sit on its laurels. It's always edgy, and as soon as Veneva Bush laid out his early model, there were efforts to rethink it and change it. If you ask me, do I think we're in for a period when there's both enormous need an enormous opportunity to rethink those things. Yes, absolutely. But the fundamental idea that this is one of the great engines of producing progress for society I very much agree with, and that makes it worth the trouble of figuring out how it needs to be fixed and changed and improved. Eric, You've done something pretty unusual for someone in your August position, which is that you started a podcast, Brave New Planet, I should say for disclosure purposes, produced by Pushkin, which also produces this show. Tell me why I have to say, I mean, it's someone who's relatively new to podcasting figures. I'm learning a little bit every day, make two mistakes for every step forward. I was kind of heartened to hear that you were doing it because I know that whatever you do your due to the highest standard. And sure enough, it's a great podcast. But why why did you decide to devote significant time to that pursuit. Well, it's actually related to what we're just talking about. I really do believe in this compact between science and society, and I do think it's frayed in certain ways. And so for me, Brave New Planet, which is seven episodes that try to take on really hard problems where I don't know what the answer is, deep fakes, for example, solar geoengineering. Should we engineer the Earth's atmosphere to mitigate climate change? Lethal autonomous weapons? Should we have killer robots? Biases? And predictive algorithms? And new technology is called gene drives to reshape species in nature. And what Brave New Planet is about is smart, thoughtful, passionate people trying to grapple with what should we do? People who agree on the facts, agree on the societal goals, and then don't agree on the solutions because they're hard. Brave New Planet as the tagline utopia or dystopia. It's up to us, and I think that's right. I mean, there are gonna be a lot of consequential decisions about science and technology that if we make wise choices, could leave us a lot better off, and if we don't make wise choices could leave us a lot worsolve. Brave New Planet was an invitation for that kind of a conversation and I hope we're gonna have a lot more of it. Eric let last question, and it derives from that tagline utopia or dystopia. It's up to us. There's a theme that I sense in you are thinking about your work over the last decades and in the direction where things are going now. I see you as on the whole an extremely optimistic, positive person. But I actually wonder if that might be one of the many secrets to your extraordinary success, that you're looking optimistically and what can come next, and how change can be productive, and how institutions can be evolved to make them better. And yet that word dystopia is still lingering there as a much more potentially You're not saying it will be dystopic, but a much more potentially worrisome picture of how our world is evolving, and particularly coming out of extraordinary technological innovations, of which big data biology is only one. So how do you think about the big picture risks that we face really as a society or as a civilization, which you know, at least when you go to Silicon Valley you hear a lot of smart people with a big steak in the future, very very worried about what their technologies are capable of producing. Look, I am an optimist, but I am a very realistic optimist. I'm not Poyanna that everything works out well automatically. You have to work really hard to make sure that you get the upsides. So, as a realistic optimist, every one of the episodes of Brave New Planet starts with all of the upsides that could come from something, and then pivots part way through the show to exactly the same question what could possibly go wrong? And it then unfolds layer after layer of how things can go off the rails, and in some cases are going off the rails. I try to be just completely clear eyed. There aren't quick fixes, but we do need fixes, and so that balance is something You're right. I could not do what I do without being deeply optimistic, and I couldn't do it responsibly without being deeply realistic. Eric. Thank you for the extraordinary work that you have been doing, that you're still doing, that you're going to continue to do. And thanks for coming in talking about it with me on deep background. Thank you a real pleasure. Noah, take care. Eric Lander is not only a tremendously influential figure in science, He's also a very, very talented science explainer, and I was thrilled that we had that on display here in the podcast as he talked about the transformation in biology, the emergence of what some have sometimes called hypothesis free science, which is really about forming hypotheses in new ways. For scientists and for me, listening to him describe these developments, it is really extraordinary to hear just how basic they've become, to how biologists can respond to real time crises like the crisis caused by Czars Cove two. At the same time, all transformations in scientific institutions drive changes in how power is deployed and how power functions, And although Eric preferred to emphasize the ways that power is spread out across the biological community, it's also true that big data science inevitably has some concentrating effects on those people, places, and institutions where the best and most cutting edge techniques can be found and consolidated, and Eric has been at the center of that development as well. Finally, I was very struck by the carefulness with which Eric addresses the problem of whether science is on the whole today bringing us in a better direction, or has the capacity to throw us into dystopia. I think it's highly significant that for his podcast Brave New Planet, Eric is exploring specifically technologies and scientific developments that have the capacity to go very, very wrong. He's a realist about how to try to fix those developments because they can't be put back in the bottle. I tend to agree with that instinct towards realism. Yet he knows that we cannot do the right thing unless we think hard about what the right thing to do, in fact is. In this moment, we're feeling or about to feel, tremendous gratitude to science for what it's accomplished with respect to a vaccine for Stars Covey two. Maybe we're not quite there yet, but it's entirely possible that we will be very grateful to science relatively soon. That gratitude will also call for common sense analysis of what the risks are and the downsides are of trusting the scientific community too much in terms of its response to a range of the most difficult social, political, and health problems facing us today. Until the next time I speak, you, be careful, be safe, and be well. Deep background is brought to you by Pushkin Industries, our producer is Lydia Gencott, our engineer is Martin Gonzalez, and our showrunner is Sophie Crane mckibbon. Theme music by Luis Gera at Pushkin. Thanks to Mia Lobell, Julia Barton, Heather Faine, Carlie mcgliori, Mackie Taylor, Eric Sandler, and Jacob Weisberg. You can find me on Twitter at Noah Arfeld. I also write a column for Bloomberg Opinion, which you can find at bloomberg dot com Slashfelder. To discover Bloomberg's original slate of podcasts, go to Bloomberg dot com slash podcasts, and if you liked what you heard today, please write a review or tell Afrah this is deep background