YouSaid · the spoken record

Emily Oster

lines on the record: 48
first: 2019-05-11
most recent: 2019-05-11
sittings or episodes: 1
sources: podcast

Every line below is reproduced as it was said and linked to the record it came from. Nothing here is summarised or generated. Directory · Search · Corrections

“It reminds me a lot of what one of my good friends, Branny, said to me when I was in the trenches of babyhood and having a lot of anxieties around all these hot button issues, breastfeeding, sleep dime, like all of it. She had been through it. Her kids were in college and she was like, let me give you a piece of advice. Be wrong, but be wrong with confidence”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“Because, like, I thought about it and I thought there wasn't any data. And, like, that's the choice that I made that sort of that confidence is important for being happy. And if we could sort of like move in that direction, I think that would be, that would be good.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, I mean, I think the big message of the book is in some sense that like you should use the data to make yourself confident and happy in your choices. I think so much of what is hard about parenting is that in the moment you are not often confident in your choices. And then when somebody asks you, like, why did you do that? Then you feel bad. Yeah. Right. And I think that there's a sense in which sort of looking at the data but then confronting like, well, we don't know, but you'd be like, okay, I made this choice. You know, I decided to let my kids watch an hour of TV every day. Yeah.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“Maybe that's just free will. Yeah. But I do think there is a segment of people who want to make the change, but the gravity, you know, because of the information, but the gravity of the habit is so much that it's hard to know where to go about it. I guess I would say, where do you see this data going? Like if you had your fantasy for where you want the kind of data and the way that we see this data evolving and the way that you see that kind of percolating out to the public, I mean, in terms of being sort of a translator and providing people the tools, like what do you want to see in terms of the way this system responds to or integrates this data in the future?”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah. Maybe that's just free will. And it comes up in the parenting stuff too. Like, you know, how much do we want to be externally controlling the choices people make with their kids, even if we don't think that they're the right choices?”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“I mean, I think there, I'm not even sure that would help. I think part of the problem is people really like the diets that they're comfortable with. Like diet is like such a habit formation thing. And, you know, people are willing to make important health sacrifices to maintain the diet that they like. We get into some of these questions of preferences. And, you know, if people, if that is the choice that people want to make, should we be trying to intervene with policy? Like let's say everybody had all the information, they knew that they shouldn't drink so much soda and that they should lose weight, but they still chose not to. Like, do we want to develop policies that affect that? I'm not sure”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“Inferring information on diagnosis from people's purchases of testing products and then following their grocery purchases. So this is like an example of using a different kind of data. So not health data in this case, it's actually like Nielsen data. So Nielsen data on what people buy. But then using some machine learning techniques to try to figure out from the kinds of things people buy, when were they diagnosed with diabetes, and then looking at their diets over time.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“Moment, exactly. Right. Like, you know, and monitoring, follow up, right? I mean, you're diagnosed with diabetes, like, you know, you have to take medicine every day. You got to go to the doctoral law. You got to test your, you know, test your insulin, at least for some period of time. So this isn't something where you can just forget that it happened. And even then, the changes in diet, you know, they're there, but they're really small. They're like, you know, like one less soda a week.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“Much for that So, I mean, I think one of the big challenges in the health space at the moment is that so much of the health problems that we have in the US are problems associated with behavior, just the fundamental fact that people do not eat great and we have a lot of morbidity and expense associated with that. And I think there is often a lot of emphasis on the idea, like if we just get the information out, if people just understood vegetables were good for them. Doesn't happen. That's not true. I think, and so this paper is about sort of looking at something where kind of a pretty extreme thing happens to people, like they are diagnosed with diabetes and we can see what happens to their diet. And the answer is, you know, it improves a tiny amount.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“I feel like we can plan so much for that. No. You also study when we are resistant to change. You looked specifically at diabetes, people I think, who had been diagnosed with diabetes and then whether or not their behavior changed even given a certain amount of information. So what do you see there about our resistance to change even from even with the right kinds of information?”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“This is about vacuum extraction, which is a way of bringing the baby out and has gone down a lot over time. And there was like this sort of sensationalist like John Stossel 2020 episode about how it could hurt your baby, which caused big reductions interesting.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“So, I mean, I think one answer is media attention. The kind of few times when we see very large spikes and changes, they actually seem to correspond with some media coverage. On the flip side, like media can often be very bad. Some of these big changes in these expert things were kind of resulted from media coverage, which was really like sensationalist and like totally inappropriate. And, you know, it wasn't like a very nice New York New York Times story about some study. It was like a sensationalist 2020.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“And then it happens pretty fast. It doesn't happen immediately. Like, you might have thought that those kind of changes could be immediately affected. And I think that they're not, but they do happen over time. Those examples really rely on there being like a Cohort of sort of like experts who are all reading the guidelines and sort of seeing that they changed and then themselves are sort of doing this all the time. I think part of what's hard in the broader health behavior space where it's people who need to make the choices, not physicians. Yes.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, so I think there are times in which the change in evidence is so big and so compelling that we can get changes, best practices in obstetrics. Like how do you deliver reach baby as an example, like those changed over time because there was like one very big, well-recognized study that everybody agreed, like this is now the state of the art. And it happens fast.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“What about when you really do need to affect change? What are the ways in which these guidelines can shift over time with kind of new sources of information or data and statistics? Like what's the positive? How does that actually play out in the right manner?”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“It's amazing. Yeah. Yeah. And so maybe there are some secrets. Like, maybe Kale really is mad. Maybe it is. But it's probably not. You know, I don't, you know, I spent a lot of time with these diet data and, you know, there's this sort of like dietary patterns, like the Mediterranean diet, which do seem to have some sort of vague, you know, support in the evidence. But I would be extremely surprised if we ever turn up like the magic one magical food.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“My dad is like really into cheese seeds. Yeah, that was the thing. There was a moment. Well, he's still in that moment. He's still. Are there sometimes secret sleeper? Like, whoa, there actually might, you know, the only way to find out is to do amazing”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“To draw conclusions in these spaces like diet or these health behaviors where the honest truth is probably a lot of these effects are very small So, if you ask the question, what is the effect of chia seeds on your health? My dad is like really into chia seeds. Yeah. That was the thing. There was a moment. Well, he's still in that moment. He's still in there. And, you know, like, what is the effect of those on your health? The actual effect is probably about zero. Maybe it's not exactly zero, but it's almost certainly about zero.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“I think it's not unrelated. Yeah. So I often think about this idea of peacking, which refers to the idea that you can keep running your studies until you get a significant result. There are a bunch of, like there's a bunch of people interested in this process of like how science, how like science evolves and the ways in which the evolution of science influences the science itself or the incentives for research influence how science works. And I think it's particularly hard.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“With you, so this paper is just very destructive. Other than saying it probably doesn't matter if you take vitamin E. So it's like, that's like news you can use. You can take that home with you. But I mean, I think it does, yeah, more or less just highlight some of the inherent and very deep limitations with our ability to learn about some of these effects, particularly when they're small.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“Not just how sure, but like what are some of the other ends of the curve? I mean, that's just information you just don't get. You just don't get. Yeah. So let's zoom out a little bit as somebody who lives in the world deeply of data in the health system. We're in a time of enormous shift, right, for data.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“As a piece of Yeah. And I think that is kind of part of generating the uncertainty and sort of showing people like what are the limits of the data that how sure are you that this should happen at this time?”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“Kind of a little more broadly. Exactly. I think that would be super helpful. And that's a place where I can imagine data collection helping, right? That, you know, we have a much more of an ability at this point to like get information about what is happening with our kids, what's happening with, you know, with our health. There is a sense in which that could be helpful in just setting some norms for the normal, the standard variation. People”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“So you're sort of told as a parent, like, oh, this is kind of roughly like around six weeks. Your kid will start sleeping longer at night, but there's no, the information that's sort of typically conveyed to people is not a range. It's just like around six, six weeks-ish. That'll start to happen. But the truth is, yeah, that's kind of right, but if you look at data on when that actually happens, it's a pretty wide range. And I think part of what is so stressful about this early parts of parenting are that it's very hard to understand whether what you are experiencing is normal.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“I think that it would be helpful if more information was shared. So, I think a lot of these things, there is a lot of information that is contained in people's experiences that we are not using. In our evidence production. So in the book, I talk about the sleep schedule.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“Sample size of one. And, you know, maybe if you have like a mother-in-law in law, it's like a sample size of two, but that's kind of it. And I think that that's really scary, especially when the choices seem so important.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“There are pieces where it's easier, where the data is better and makes it clearer about what you need to do or what the choices are, you will be making many choices without the benefit of evidence or data or very good data. I think part of what makes some of this parenting so hard is that for those of us who like evidence and facts, and it's hard to accept, I'm just going to have to make this decision basically based on what I think is a good idea based on my gut. Based on my gut and maybe based on my mom. And, you know,”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“That Right, you say you have a great quote where you say in confronting the questions here, we also have to confront the limits of the data and the limits of all data. There's no perfect studies, so there will always be some uncertainty about conclusions. The only data we have will be problematic. There will be a single not very good study, and all we can say is that this study doesn't support a relationship. So it feels kind of hopeless. I loved when you talked about the first three days of when you brought Penelope home and it really brought that back.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“But in real life, yeah, I think people face constraints associated with just not having all the information. And also the fact that these kind of information like whipsaws over time, that, you know, you get one piece and then you kind of the next day there's a there's a different piece of information and we have a tendency to kind of Glom on to whatever is the most recent thing that we have seen about this as opposed to what is the whole literature over this whole period of time, say.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, and I think we wouldn't necessarily think of that as in constraints because, of course, in our models, people are fully informed about everything all the time. That's one of the great things about the models.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“But is information flow kind of the data itself a constraint in that regard? Because it's so piecemeal, the information you get. That feels almost totally random. Like some media story picks up on something, you tend, you know, some tidbit you hear somewhere, unless you're systemically studying a graduate seminar on parenting, which none of us do. It is random.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“But we also recognize that people have constraints In the absence of constraints, like having money to buy things or time to do them, people would just have an infinite amount of stuff. That's the thing that would make them the most happy. And so, but when you're actually making choices, you're constrained by either money or time. And in the book, I talk a lot about this in the context of time, that you're as a parent, you're making choices, and you have some preferences and things you would like to do, but you are also facing some constraints.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“In economics, we think about people optimizing their utility function. The idea is that you have a bunch of things that make you happy. That's your utility. They produce your utility, and you want to make the choices that are going to optimize your utility, that you're going to give you the most amount of happiness points, utils, come utils. It's a very warm and fuzzy display.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“Very murky data, very, very variable from all sorts of different contexts, and like put it through the sifter of like this kind of data, this kind of data, and then match it all up and say, okay, what do we have left? And then therefore, and then hand that over and say, and now you make the decision based on this, right? Here's coming.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“But the thing you worry about is like one kid is not doing well, is unhealthy, so the mom chooses not to breastfeed or chooses to breastfeed to try to make them healthier. Those are the kind of things where there's some other reason that they're choosing differences in breastfeeding, which has its own effect on the kids' outcomes. So you kind of like some of what I try to do in the book is sort of like put all of these pieces together and kind of like look like look at them and think about them all as a sort of totality of evidence and just think like how compelling is this altogether.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“Another time. If that were the reason, that would be great, right? If the reason we're just like kind of worked one time, it didn't work the other time. You know, if there was something that was effectively a little bit random, then that would be exactly the kind of variation you'd want to use. Okay.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“But it's exactly it's so specific. And you said, like, well, you know, how do I take that result in the Bay Area in 2019? Right. It's a challenge. Okay, was there any other within this space of not randomized data? Is there anything that's better? And in that case, there is, you know, there are some studies that compare siblings. Oh, okay. Where you look at two kids, you know, born to the same siblings, born to the same mom, one of whom was breastfed and one of whom was not. And then look at their obesity rates. And when you do that, you find there's basically no impact. So then you're kind of holding constant like who's the mom? So if you're worried, was that there are differences across parents in their choices to breastfeed, well, now you're looking at the same parent.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“So it's hard to pull apart the web. So, I would say this is an example where the data is suggestive. Like, it would certainly be consistent with an effect of breastfeeding on obesity, but I think it doesn't prove an effect. And then you can sort of take the next step and say, okay, well, do we have any data that's better? And in that example, we do have one kind of randomized data. But again, we run up against the limits of all kinds of evidence. So the randomized data on this question is from a randomized trial that was run in Belarus in the 1990s.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“The best example of this in the data in the parenting space is probably in breastfeeding. Let's say you want to know the impact of breastfeeding on obesity in kids. That's the thing which you hear a lot, that breastfeeding is a way to make your kid skinny and so on. And so the basic way you might analyze that is to compare kids who are breastfed to kids who are not and look at their obesity when they're, say, seven or eight. And indeed, if you do that, you will find that the kids who are breastfed are less likely to be obese than the kids who are not. But you will also find that there's all kinds of relationships between obesity and income and obesity, mother's income and mother's education and other things about the family. And those things correlate with breastfeeding and they also correlate. So you can't.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“Right, yeah, but I think it's exactly these preferences that, of course, make it hard to learn about these relationships and the data because once you recognize that a lot of the reason that some people choose to eat eggs and some people choose to eat cocoa crispies is that some people really like cocoa crispies. Some people really like eggs. How can you ever learn about the impact of eggs? Because we know there must be differences across people. And I think that that becomes even more extreme when we think about really important decisions that people are making, like the kinds of choices they make in parenting or also in their diets.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“Think this is why in these spaces decision making should be so personal. We often run up in health and also in parenting and all of these spaces into a place where we're telling people like there's a right thing, there's a right thing to do. And I think that that can be problematic because it doesn't recognize this difference in preferences across people.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“Right So, you talk about kind of breaking it down into the relationship between data and preference. How do you factor in that in the healthcare system where it's so diverse, where preference has such an incredible effect and puts you into so many different possibilities?”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, exactly. I try to first seek are there good pieces of data that we can use? And then if we're stuck with the data that isn't good, trying to figure out which of the murky studies are better than others and what would you mean by better? Well, it's roughly like how good is this study at controlling or adjusting for the differences across people?”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“So, there's one really nice example of the book where this happens exactly like you would hope, which is in studying the impact of peanut exposure on peanut allergies. So the first paper on that is written by a guy and what he did was he just compared Jewish kids in the US, or sorry, Jewish kids in the UK to Jewish kids in Israel. And he saw that the kids in Israel were less likely to be allergic to peanuts. And he said that's because they eat this peanut snack when the babies bomb. And so then that's like the hypothesis generation. And then he went and did the thing you would really like, would just say, okay, let's run a randomized trial and let's randomly give some kids early peanuts and some kids not. And indeed, like he found that he was right. So that's like a great example of like how you would hope that literature would evolve. But in many of the kinds of health settings we're interested in that you can't do that or it is much harder to do that because the outcomes would take a long time to realize or it's expensive or it's hard to manipulate what people are doing.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“In the best case scenario, be like a scratch pad. Let's just look in the data and see what kinds of things are associated with good health or associated with good outcomes for kids. And then we could imagine a next step where you would analyze more rigorous gold standard. And sometimes that happens.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“A million different ways. And data like that is really subject to these kind of biases that the kind of people who make one choice are different from the kind of people who make another choice. One of the things that's very frustrating in a lot of the health literature is that there isn't always that much effort to improve the conclusions that we draw from those kind of data”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“That's the gold standard, but it is not the default. So many of the kinds of recommendations that I look at in parenting, but that you look at in general in health are based on observational data, which is the other kind, where we compare people who do one thing to people who do another thing and we look at their outcomes. And one of the ways in which the people differ is on the thing that you're studying, but of course there are other ways that they may differ also”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source
“So there are a lot of settings in health. And in all of those settings, we have to figure out what the evidence say. And I think about some of them in this context of parenting, but you can think about even questions like, you know, is it a good idea to eat eggs or is it a good idea to take vitamins, other kinds of health decisions? And you can sort of think about there being kind of two types of data you could bring to that. One would be randomized data. So you could run a randomized trial in which half of the people got eggs and half of the people didn't and you followed them for 50 years and you saw which of them died. And that would be very compelling and convincing. And when we have data like that, it's really great.”
2019-05-11 · a16z Podcast · a16z Podcast: A Guide to Making Data-Based Decisions in Health, Parenting... and Life · IDENTIFIED FROM THE TRANSCRIPT · source