In this episode, I was joined by Seth Stephens-Davidowitz, American data scientist, economist, and author to talk about his book, Everybody Lies, and the secret of the world!
Do you know one of the most google searches in India is a man trying to get his wife to breastfeed him!? I was surprised too!
Have you ever wondered what are the most searches on Google? What are the most ridiculous searches on Google? And Google probably has more data on you than any agencies out there!
In this episode, I have Seth Stephens-Davidowitz, American data scientist, economist, and author, to talk about his book, Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are.
We also breakdown what were the most google searches, how do people use the "secret" data to improve their business and/or their life!
My new book Skip The Line is out! Make sure you get a copy wherever you get your new book!
Join You Should Run For President 2.0 Facebook Group, and we discuss why should run for president.
I write about all my podcasts! Check out the full post and learn what I learned at jamesaltucher.com/podcast.
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James Altucher 0:01
This isn't your average business podcast. And he's not your average host. This is the James Altucher Show. Today on the James Altucher Show, everybody in the world keeps secrets. And now, there's a way to basically find out the world's secrets. And that's what we do in today's podcast. So I have on Seth Davidowitz, who wrote the book, everybody lies, but it's not that everybody lies. It's that, again, everybody covers up what they don't want others to know. But the one entity they don't hide from is Google. So we know the world's data, we know the world's secrets from what they enter into Google and other sources of data. For instance, Seth tells me about this incredible fetish that exists only in this one country. Seth also reveals by the end of the podcast, really the secret of all happiness. There's so much amazing, mind blowing, data and secrets that we talked about today. I was just blown away. So here it is.
Seth Stephens Davidowitz wrote everybody lies, big data, new data and what the internet could tell us about who we really are. And there's so much fascinating data in here. Like, I was really fascinated by some of the searches about relationships. Can you describe some some of that? And then I want to get into your background, everything. But there's like, just, there's just a lot of interesting facts in here. Yeah, about what people search for. And what that tells us about humans. Oh, there
Seth Stephens-Davidowitz 1:43
are lots of things. One of the things I talked about is how you can't really trust what people say on social media, but people are more honest on search. So on social media, when people are talking about their husbands, and they're posting out their husbands, it's my husband is the best, my husband is the greatest, my husband is so cute, my husband's adorable, my husband's amazing. And then when you look at Google searches, it's my husband's a jerk, my husband's annoying. My husband's cheating on me, I think my husband's gay. It's like a totally different view of relationships on the social media, which is public and Google, which is private. So that was definitely one of the things.
James Altucher 2:16
Well, could both be true. Like it could be, we don't know if it's the same people posting their husband is adorable, that's also searching for,
Seth Stephens-Davidowitz 2:24
I think it just shows that the data you get depends on the incentives you give people. So you know, I think just like Google is kind of biased towards negative things. Because you don't necessarily want us to tell like if your your relationships going great, you don't necessarily feel the need to search Google for anything, because you have nothing to fix. But if your husband or wife is annoying you then you search on Google, and on social media, you don't have an incentive to tell all your friends you know, I can't stand my husband or my husband so annoying. My husband's a jerk. My husband's I think my husband's gay. So if you just looked at social media data and said that's marriage, you would be getting not the full picture.
James Altucher 3:00
Yeah, like what other what other like marriage related things? Do? You kind of mean, you talk about a lot of them in here or relationship related things? What do people search on
Seth Stephens-Davidowitz 3:09
that the number one complaint that people have about both a marriage and a relationship or that it's sexless. And that like, kill, and the number one complaint that husbands wives, boyfriends and girlfriends have about their partner, is that the partner won't have sex with me. Like it easily beats the number two complaints that the partner won't text me back. And like they're surprised surprising things there are twice as many searches for my boyfriend won't have sex with me, then my girlfriend won't have sex with me. Which goes against like, we usually think that men young men particularly or aren't unmarried usually are always want sex and there's kind of a stereotype that women are you know, wanted less but in the data of anything, it's it seems to be reverse that they're twice twice my complaints. A boyfriend is one of them Sex and the girlfriend won't have sex.
James Altucher 3:57
What about the mouth email breakdown on you know, I think my significant other is cheating on me. It's a
Seth Stephens-Davidowitz 4:03
little hard to fully break down. Like Google's data is all anonymous and aggregate so you don't know always what the breakdown is. Unless you can guess like boyfriend girlfriend, you know, 95% of people are straights you can kind of do it. I do a whole bunch of things on sexual stuff. Yeah, where it's pretty easy to know the gender because people say like, my penis, and it's like, if someone says my penis, they're male. And, like, I found that that men have more questions about their penis than any other body part more than their lungs, liver, ears, nose and throat combined. And for every 100 Questions man asked about their penis, they asked five about their brain. And the other thing I found is that one of the top questions men have about their penis is how big is my penis on Google? Which is like a totally ridiculous question to ask Google right? Like that's not the way to find out. And I just found out this is actually a brand new five discovery that the James all Teacher Podcast, the first to hear that men sometimes type into Google, like just report in a full sentence. The size of their penis. So they go like my penis is four inches. My penis is five inches, my penis is six inches, I paid seven inches, whatever. And when you actually analyze all this data, it's a normal distribution of reported to Google penis sizes centered around five inches. Wow. Which I don't know what to make of that. But I was just like that. It just shows. I think one of the things that the Google Search research kind of uncovers is the weirdness of humanity. You know, I don't even like to say, it's weird, because everybody's weird, then maybe nobody's weird. But you definitely see things in the data that people don't otherwise talk about. Another one that I mentioned in everybody lies is that the top search that starts my husband wants in India, is my husband wants me to breastfeed him. And that's India and nowhere else. And there in India, in like, in the United States, if there are questions about how to breastfeed, about 99% of them are how to breastfeed a child. But in, in India, they're about evenly split between how to breastfeed a partner, and how to breastfeed a child, which actually is kind of is very, very interesting. Some people just find it amusing or think it's silly or whatever. But it actually shows that, I guess a fetish can develop in one part of the world in pretty large numbers without ever being openly talked about, actually, after I published that finding a lot of people interviewed doctors in India, and they said that they had no idea. They never heard of this. But I'm, I'm 100% confident based on the data. This is a thing. And it's just not talked about. It's so
James Altucher 6:29
fascinating, because like, is it really borders Pacific like this Pakistan not have that fetish? Or yeah,
Seth Stephens-Davidowitz 6:35
Pakistan has a South Asian thing with just a little bit Pakistan as well, but not not nothing much beyond that.
James Altucher 6:42
You mentioned, the earlier thing was like a brand new discovery, like, where do you get this data right now?
Seth Stephens-Davidowitz 6:48
Yeah. So I just use Google Trends. And sometimes I see things and I haven't seen anybody report that my penis is blank inches. Like, I'll look if anybody else has said that. But I've kind of moved beyond that. Because initially, when I was doing this, like I do, I think I'd go to like, give a talk. And I'd say how many people know about Google Trends which Google reports synonymous area data, and like to people would raise their hands. Nobody knew about Google Trends. So it was kind of this great secret for understanding humanity. But now it's well known. And there dozens of academic papers written every month using Google Trends, data, and people are tweeting Google Trends findings. So it's a little harder to find anything new.
James Altucher 7:29
But but that seems like just academic data. Like I think the on average people I know, don't explore the human condition by looking at Google Trends, because you have to look at a lot like you have to sort of ask lots of questions to Google Trends to really find a pattern or a trend.
Seth Stephens-Davidowitz 7:44
That's right. I know. Did you do like a stand up comedy set based on Google Trends? Or is that someone else
James Altucher 7:49
I did something about it. But I also, I did a lot of stuff on on reviews on Google Maps, because I didn't realize that every location on Google Maps has reviews like Yelp. And so people would spend the time to like review the Eiffel Tower or the Mount Rushmore. And it's just like this. But what's interesting, and where this kind of intersects with what you're saying, is that cool is not only a place to find information, you don't know. Google is almost like a confessional. And you mentioned this in the book, like, for instance, before people have children, you said it was something like I forgot what the ratio was seven to one or something people wanted to know if they would, would regret not having kids. And then after they had kids, they would sort of report back to Google and and basically search on people who regret having kids, it's almost like they are outsourcing some of their thoughts to the Google verse.
Seth Stephens-Davidowitz 8:47
Yeah, exactly. So yeah, before people have kids, it's, it's highly tilted in favor. The question is, Will I regret not having kids, and after the fact, it's tilted in the favor of people are far more likely to report to Google regretting having kids than regretting not having kids now, I think part of that is, people might just be having a bad moment. So I don't think everybody who searches on Google I regret having, you know, my son or my daughter, that they view this as a major life mistake. And if they and if you ask them, day after day after day, they'd say, you know, this is the worst thing I ever did. They may just have not had a good night of sleep. And you know, their kids, maybe it's during, during the COVID pandemic, all this research is before the call of the pandemic, but their kids have a billion problems, and they're exhausted, and they just can't deal with it. And they turn to Google. I regret not having kids. But those are the types of thoughts that we don't usually see. Certainly in everyday conversation. And even as I talk about everybody lies in anonymous surveys. So the way we got around people kind of lying is we try to ask people questions anonymously, and figuring Okay, well, if nobody knows who's giving this answer you'll be more likely to be honest. But it turns out, it's been shown over and over again, that people are deceptive even in anonymous surveys. And they're, they don't like saying things that they're not proud of to a stranger on the phone, or a stranger. They're in the same room. But Google, they are more comfortable saying these things, in part because Google gives you an incentive to tell the truth. So Gallup or pew or Quinnipiac you have no incentive to say, you know, I regret having kids or I'm not having sex in my marriage or these other things. But on Google, you do have an incentive, because you get the information you need.
James Altucher 10:34
So So I mean, I, I've underlined a ton of stuff that like interesting data, interesting facts that you've uncovered. But let's rewind a bit and talk about how did you, you you worked at Google as a data scientist? How'd you get the job? What do you do there? What did you uncover there?
Seth Stephens-Davidowitz 10:53
So actually, I was writing New York Times columns of my analyses of Google Trends. And then the company reached out to me saying that, you know, you might want to work for us, since you have such an interest in our data.
James Altucher 11:05
Everybody reaches out to you. Nobody ever reaches out to me, I write also, though, and reaches out.
Seth Stephens-Davidowitz 11:12
I know, you're lying about that, because I personally reached out to you six years ago to get coffee. So I at least some fans do reach out to you. But that's true. That's true. And I would bet that you're being deceptive there. And people do reach out to you. You certainly done some very, very things in your career.
James Altucher 11:30
Your book is called everybody lies. So you're probably skeptical of people's honesty in general. That's true.
Seth Stephens-Davidowitz 11:35
And I think interestingly, you may be dishonest in the negative direction. Most people are dishonest in the positive direction. And they say everybody's reaching out to me, and I'm in huge demand. And ISIS, I suspect not to be your therapist that you may be dishonest the opposite direction, which I also am. So if that's true, we have that in common.
James Altucher 11:52
So Google contact you you started working there. And what did you do for them? Did you move out to San Francisco? Did you work here in New York?
Seth Stephens-Davidowitz 11:58
Yeah, I was living in the Bay Area. And I was basically doing data analysis, it totally independent from the work I did in my book, I was doing a lot of like, ad I was in the on the quantitative marketing team. So a lot of analysis of advertising, and just kind of basic data science, which I actually enjoyed. I tend to like everything once I get into it. What
James Altucher 12:21
does it mean, though? On the advertising side, like, like, it seems like there could be proactive stuff, like if you see everybody is googling stuff about, I don't know, some particular kind of bed, you can inform that bed company, hey, a lot of people are googling you and get it and then going to other results, we can help you find something that is it proactive like that, or is it something else,
Seth Stephens-Davidowitz 12:46
I wasn't doing that I was doing more just like analyzing the effects of a b tests or different projects that weren't really using the search trends as much I did. One project that was using search trends, it was kind of the idea was surveys are small. So you ask 1000 people a question. And you don't necessarily have data for different geographies. But you can kind of combine that data with Google Trends data and say, if people let's say you ask, like, who supports Biden, and if people who support Biden tend to be an area's that make a lot of certain Google searches, like search for yoga, or a search for, you know, vegan recipes, then you can kind of predict Biden support throughout the country, even though you only have a 1000 person survey. So I did a little bit work on that, which I should be able to talk about because it's public.
James Altucher 13:35
And was it successful? Yeah, it worked pretty well, like people at Google could probably do really well in prediction markets, where you get to bet on political outcomes. For instance,
Seth Stephens-Davidowitz 13:45
there was actually a story that I'm pretty sure like, some Google executives at some point came up with an idea we should just be a hedge funds. But then like, I think Eric Schmidt was like, there's no like, There's no way that's at all legal. So but yeah, I'm sure if you had access to moment to moment search data, you could predict the stock market and other things.
James Altucher 14:07
You could, for instance, search, if in the area of where a company is if suddenly there's a uptick in searches, like what happens when a company fires, its CEO, and it's all coming from IBM or whatever. And it's also coming from a law office in New York City that represents IBM, then you could probably make some predictions.
Seth Stephens-Davidowitz 14:26
Yeah. And they're just just companies use this data. Like a lot of times just seeing how their products doing. I think politicians have used this data to see whether they have to address a scandal. So if like everyone's Googling something, but then, like, basically, does the story have legs? So if it gets a lot of attention, then people just stop googling it. They'll sometimes say, Okay, let's just let this be. But if everyone, you know, all news covers and people, the Google searches go way up, and they stay up, then they say, Well, now I need to address this.
James Altucher 14:59
Yeah, it's interesting. So so what were the A B tests that you were analyzing? I'm just trying to build a picture of like, your experience at your time at Google. Oh,
Seth Stephens-Davidowitz 15:09
ah, I don't even remember it was so long ago. I don't know. They're just particularly it was it's kind of boring. It's not as exciting as the penis searches, trust me.
James Altucher 15:18
But like is if they change the search algorithm, are people more likely to click the top results and stuff like that? And you test different search algorithms?
Seth Stephens-Davidowitz 15:26
I think the highest level does stuff like that mine were more like basic questions or analyzing the effects of experiments and just kind of more general analysis, but nothing too crazy.
James Altucher 15:35
You know, and you mentioned this fascinating story. And maybe this got you interested in data. Originally. You mentioned the story of the guy who bought a horse for like, a million dollars. Jeff Seder, yes, ater. He used a data driven approach. And I might have heard of this guy actually, Stephen Dubner from from Freakonomics told me about a guy who had essentially, almost like a hedge fund, betting on horses and use using a Moneyball or a data driven approach is I wonder if this is the same guy. It probably
Seth Stephens-Davidowitz 16:05
is. And it may have been because I was on the Freakonomics podcast talking about it. So that may have been what got Stephen to talk about. I'm not sure but he, he, this guy, Jeff Seder. He is like a totally brilliant guy. He has three degrees from Harvard University. And he was working in banking at Citibank in his 20s. And one day, he came home from work, he saw himself in a suit and tie in the mirror. And he's just like, This is not a I'm not meant to be a banker. I'm not meant to wear a suit and tie every day. I'm not meant to live in New York City. So he fled from with his three Harvard degrees to rural Pennsylvania. And he wants to be in nature around horses in the woods. And he spent the rest of his life analyzing what makes a great racehorse. Great. And amazingly, this was before Moneyball before kind of the before the term data science existed. But he was way ahead of the curve that he wanted to figure out what makes great horse race horse great using data. And he tried all these things over the years. He He's like an eccentric dude. And he told me I flew down to Florida because I found his story so fascinating. And I met with him over a weekend. And he was telling me all these things he tried. He's like, he measured the size of horse nostrils to he had this theory that horses with big wide nostrils would breathe better, and that would make them run faster. And he created what I think to this day is the largest horse nostril dataset ever assembled. And he tried that out like do these horses with big wide nostrils run faster and found out No, no they don't. And then he measured the size their leg muscles do horse with a big wide leg bet muscles run better makes makes a lot of sense didn't turn out to predict success. And he tried one time he tried to measure the size of horse poop, the size their dedications, he literally set stood outside the barn and was measuring the size of like the diameter of horse poop and said do horses big wide poop run faster. And he found out that no, it doesn't work. And he tried all these things about horrible failure. I'm pretty sure his wife was on the verge of leaving him he was probably close to bankruptcy. And then he came up with the idea to he worked with a professor at the University of Pennsylvania, he built the world's first EKG to measure the size of internal organs of horses, including the size of different ventricles, their heart, including the size their left ventricle, and he put this in the data set he had built. And he found that horses with big left ventricles just run faster than everybody else. And that's why he made the prediction that American Pharoah would be a once in a generation horse, because American Pharoah had a 99.6 first percentile left ventricle, and nobody else except for Jeff Seder knew that he had this left ventricle or do that left ventricle was so predictive of success. So it's an amazing story.
James Altucher 18:59
How do they get the data about that specific horse meaning like, let's say he's going to an auction, and there's 20 horses for sale? Would he make them all go through like an M an EKG or
Seth Stephens-Davidowitz 19:09
I think he just has to like robic near their heart outside the barn. I'm not exactly sure. But I think it I think it was a small device that allowed for it. I'm not totally sure. But it was it was amazing. Because he showed me the card. I was just like, wow, American Pharoah based on his model just had to be an incredible horse and then and nobody else thought that when American Pharoah was one year old like basically the way every other horse analyst predicts horse racing success is using pedigree and American Pharoah his pedigree was just basically average. So everyone's like, yeah, this horse fine, nothing special. And Jeff Sater just had this model is like no, this is like going to be a once in a generation horse and then it was a one inch generation horse. And the first one's a triple crown. And then another horse I think it was justify won the Triple Crown again and I emailed Jeff I'm like Tell me, did he have a big left ventricle? And he's like, Yeah, I was enormous as well. So, yeah, it's it's really cool.
James Altucher 20:06
And so how much money do you think he made? How much money did he make on that one horse?
Seth Stephens-Davidowitz 20:10
I don't know exactly because he always eats, he's also died. He's, I think he's lesson to it, that for money then other people, he said that on some podcasts he's been on. And I think it's basically true. Like, I hung out with him. And he was just obsessed with trying to figure out horse racing success more than business as far as I could tell. But I he didn't tell me how much he made. It was basically he sells his service as consultants to horse owners. And what he did is he had a client who is trying to sell American Pharoah. And he told the client, don't sell this horse, sell your house, like there is no way you can sell this horse. He is too good. So he saved the client, you know, from a huge mistake. And I don't know how much the client paid him if he got a bonus out of it. I'm not exactly sure. Yeah, because
James Altucher 20:59
that that horse probably went on to a big career in being a stud as well. So he's probably made 10s of millions of dollars.
Seth Stephens-Davidowitz 21:07
Yeah, that's where most of the money in horse racing is. Yeah.
James Altucher 21:09
So when I hear stuff like this, I always think to myself that, okay, is is a data driven approach to this kind of analysis where you can have real world, you know, positive outcomes, including making money. I feel like, is it too late? Because every domain has been conquered? Like, you know, Moneyball, did it for baseball, actually know a guy who's doing it for football and doing very well. I'm just wondering what domains, you know, you feel are, like unexplored for this.
Seth Stephens-Davidowitz 21:38
I think it's definitely not too late, in part, because, after all, everybody lies I started, some companies reached out to me. And they asked me to help them consult. And like 90% of the companies, I'm not exaggerating, initially apologize. They're like, our data. Science is so pathetic, like, we know you're expecting a lot more. And we just have a lot less than you suspect. And when every company is saying that, I think like, I'm like, You're doing nothing wrong, you're just like, there's it that just says that there's still a way to be way ahead of the curve. I think there are some fields, if you're competing with if you're going to try to create a new search engine, or a new social network, I think you're gonna have trouble competing on the Data Science Front with Google or Facebook. But if you're in any industry, most in Wall Street, I think is another area where the best data scientists to work there and you might have a, you might have a tough time, having a huge edge. Baseball's may be one area where you might struggle to find an edge, except every few years, a new book comes out about how a different team use data analytics to become great. So first, it was bought, evolved, covered the story of the Oakland A's. And then there was a book about the Tampa about the Houston Astros, I think was Astro ball. And then there was a book about the Tampa Bay Rays, how they use data analysis to kind of beat the system. So even baseball, which is maybe the quintessential example of a field where the secrets of the advantage of data science have spread widely, there seem to be ways to still have an edge using better data science are advancing. And I think the other thing that Jeff Seder story tells me is that frequently, the way to have an edge in data science is not by having better models than everybody else, or just thinking to use data science. Everybody can do that. In many ways. Every horse consultant was a data scientist, they just looked through the same books that everybody looked through, and rank them and saw how good the pedigree of the horses were, and then consulted their clients based on that information. But what Jeff Seder did is he was entrepreneurial, he actually went out and got new data that nobody else had. So he, you know, measured the size of their horse nostrils and measure the size of their poop and the size their legs, and he built the EKG, and he did all these things. And that entrepreneur being entrepreneurial, doing annoying things that nobody else wants to do. I think you can always have an edge basically indefinitely in life, because everybody ever most people are drawn to the lazy approach to just using the same data sources that are very else's using. So if you're willing to put energy into collecting new data, I think you could have an edge in just about any fields.
James Altucher 24:26
It's really interesting, because there's two things happening. One is how unique and different is your model from all the miles prior. Now, that doesn't mean your model is going to work. But it's a combination of that using a unique model to uncover something that is very common, because it's what you're trying to uncover it, let's say is the best horse, but you want to go about it in a way that no one's ever gone about it before because that will be the arbitrage in price ultimately or the arbitrage or whatever it is you're transacting. So, so its uniqueness combined with commonness, you're using the unique token In the common
Seth Stephens-Davidowitz 25:02
Yeah, that makes makes a lot of sense.
James Altucher 25:04
And and it's interesting because you know, the book's title, everybody lies, but it's really you mentioned this in the book, it's, it's not so much about lying. It's sort of about everybody's, what you're doing is using this data that is always out there to find the industry secrets. Yeah. So like, for instance, what you were just saying about relationships, or what you're saying about India, even doctors, and, you know, therapists probably didn't know, this was a big thing in India, you know, Indian doctors and Indian therapists. And yet, it's something a billion people, you know, give or take search on, on Google. So it's like a big, this big, massive secret that no one talks about. They feel comfortable talking to Google about it, because they because like you say, they have an incentive to learn more.
Seth Stephens-Davidowitz 25:48
Yeah. And I think the other thing with data science, is you have to be willing to be surprised by the data. So like, I think a mistake that a lot of data scientists have is, I think one of the reasons Jeff Seder was so successful is he was I think, by his own admission, a little eccentric, and maybe, I think a partner of his who I met patrie Patty Murray just said, he's crazy. And I think that can be an advantage in data science. Because most people, like both people just test what everybody else has already been using. So you just look at the pedigree. You look at the times they they ran, most people are like, you know, could poop size correlate with success? Nobody thinks that. And then if you do think that a lot of times you're wrong, but occasionally you're going to be right. And you know, I did this, I talked on the book. I started this site Stormfront, which is the largest hate site in the United States. And actually the way I, the way I came up with the idea to study Stormfront is I was Googling myself, because I read an article and I got excited because this message board was talking about me there like Seth Stephens Davidowitz wrote this article, I had read an article about racism or something like that, you know, like, I get excited. I'm like, Oh, wow, I mean, the news, whatever. And then I look at the site, and it's like, June, yeah, it was like June sets the image below it, and like, you know, analyzing my face and how Jewish I look. And I'm like, Oh, God, what the hell is this site? This isn't so cool. And then I just found out that it was the biggest hate site in the United States. And I was shocked at the biggest hate site in the United States was when you look at the actual message boards, was predominately focused on Jewish people. I'm just like, What the hell like that's not like I grew up with kind of an idea that anti semitism was deeply in the past in America. And I grew up in a, you know, town that was 40%, Korean 40% Jewish, like, I don't think there was much anti semitism that I detected. And I went to universities that were all very Jewish and with, as far as I could tell, zero anti semitism. So I wrote this article about Stormfront, and I just found out like, recently, that I wrote this article, and my dad told my mom that Seth has gone crazy. She's like, he's like Seth has lost his mind. He's down into conspiracy theories like, like, What the hell is he talking about, that there's some, you know, anti semitism, anti Semites congregating on the internet in the United States, like he's lost his bind. And my neither my dad or my mom told me that they had that hypothesis. And then the Charlottesville protests happened, where there were all these people chanting anti semitic things. And my dad goes to my mom, I guess Seth was right. And I think what I take from that story is you have to be willing to let the data take you to places that seem crazy to other people, and just stick with the data and say, I don't care what anybody says, I am seeing, you know, not if the data is not telling me that 10% or 20% are visiting this site. But the data is telling me a lot of people are visiting a site that is predominantly focused on how on theories of how Jewish people are running society, and my dad could think I'm crazy, my mom could think I'm crazy, but I'm going to put that data out there into the world. And more times than not, you know, the the world catches up to the data, and it gets revealed in some other way. Maybe we're going to find the breast feeding thing some other way. And I can tell people I told you, that India that you know, Indian men have this fetish, that not all Indian men but more than other places.
James Altucher 29:26
What were some other things that that kind of surprised you they again, again, it's not that everybody lies, it's not like that Indian men lie. It's this. It's a secret. It's it I'm really more fascinated by the term secret like that. society as a whole keeps all of these deep secrets like like whether it's anti semitism or some fetish or whatever. And we're not really aware of it because we don't really know whatever anybody else is thinking because they might be so secretive that you don't want to talk about these things. It's like what are they about but Google knows it all go and
Seth Stephens-Davidowitz 29:57
does it all and other sites No, it also i Also in the, in the book, analyze data from Pornhub. And speak about a site that knows a lot about people that people aren't gonna normally talk about, you know, that's an area, you know, where there's a lot of stuff that's surprising or not talked about, I was struck in the data. There, there was, were more searches than I was expecting and more views in pornography sites for overweight people than I would have guessed. And I think that was really interesting, because there's also data from dating sites, which suggests very clearly that people try very hard to date people who are skinny, that being overweight is a huge negative in dating. And that made me think that there's a sense in which being in the closet is more widespread than we sometimes think. So the traditional definition of being in the closet is a home a gay person who pretends that he or she is straight. So the person is attracted to members of the same sex, but due to social pressures, they pretend that they're interested, a desire to conform or desire to make other people think highly of them, they date members of the opposite sex. And I suspect that that phenomenon is more common than just gender, that a lot of people try hard to date people, because they'll impress their friends, or they think other people will think though cool, or other people think they're normal, rather than what they're really interested in. Because the data from pornography shows that the what people are most deeply attracted to varies much more than is usually talked about. But what people look for in dating, it doesn't always vary so much. So I do suspect that there are, for example, men who are would be are more attracted to overweight woman and will be happier and more fulfilled if they date an overweight woman. But because they are embarrassed about that attraction or think other people will judge them negatively. I try to date skinnier woman instead.
James Altucher 32:03
What do you think it is about, in this case, overweight women that and I can understand the reasoning why I'm curious, your interpretation. Why? Why do you think that is? So on the dating side, I understand they're trying to impress their friends. But in the in the fulfillment side? Why would want a weight determine a higher degree of fulfillment?
Seth Stephens-Davidowitz 32:23
Why are people attracted to people of certain types? What causes those attractions?
James Altucher 32:27
Or in this particular case? Why do you think being in relationship with an overweight woman might be more fulfilling whether it's sexual or just the relationship in general?
Seth Stephens-Davidowitz 32:38
Oh, no, because I think some people the range of what people are attracted to varies quite a bit. And that for some, some people, for whatever reason, are more attracted to overweight people. Some people are attracted to brunettes, redheads blondes, bald people, people with full heads of hair, tall people, short people, there's a pretty range wide range of what you're attracted to. I think a big question that this data will ultimately help us answer is what causes such attractions. So why are some people attracted to types of people, there's some evidence that people get imprinted from a very young age from the people they see around them, or the people they have a first romantic experience with, and tend to be attracted to that same type the rest of their lives. They've actually done studies with, I think, Doc's where they paint like the brothers beak red. And then for the rest of their lives, the the kids have that mother with the beak with that was painted red, seek out partners who have read beaks, which suggested that some attraction, at least for ad for many animals comes from certain key moments in childhood. So but that's an area well beyond my expertise, although that usually doesn't stop me from opining about topics.
James Altucher 34:13
I kind of feel and and data sort of shows this. There is no such thing as expertise. That's a lot of what you're telling me like, take the Jeff saders example, with horses. Most people buy on pedigree, and the experts will analyze pedigree and they're experts on pedigree and they'll tell you what worse to buy based on pedigree. And it turns out, they forgot to check the left ventricle. So they weren't really experts at all compared to Jeff Seder.
Seth Stephens-Davidowitz 34:37
I think that's right. Although that can be taken too far. There have been studies on like, what on successful entrepreneurs where they've looked at the entire record of entrepreneurs in the United States, and there is there has there is an argument that outsiders have an edge in entrepreneurship David Epstein's book, which is excellent range has a whole chapter The Outsiders that you have an edge if you come from kind of a field, a different field, because if you're in a, so stuck in a field, you're going to be so constrained by whatever else is doing, you're not able to see kind of new solutions. But if you actually look at the data of every business created, there's a huge Insider's edge, that the closer you are to even the sub specialty, you're starting a business and the more likely you are to be successful. So I think some of what happens is the non experts who succeed, we get so excited by their stories, and they're so almost because they're counterintuitive, and they stick out. We love telling the stories, and then we kind of lose track of the fact that it still is the exception. So it's not like you can't be an outsider revelation revolutionize, you feel your field. Jeff Sater has shown that there have been many entrepreneurs who have created successful products in something in an area they knew nothing about. But it's still the exception rather than the rule. The other example that business is age of entrepreneurs. So there's this idea that young that youth is an advantage in business. And we hear all these stories, there was a movie, The Social Network of Hollywood blockbuster about Mark Zuckerberg started Facebook when he's 19 years old. And people started thinking, Oh, it's, you know, you can start a great business in your dorm room, or you can start, you know, a great business shortly after college or in your late 20s. And if you look at the data, not the stories or the movies, the most successful founders of businesses tend to be in their mid 40s. And your odds of creating a successful business increase up until the age of 60. And the average business owner, the average successful entrepreneur who is not turned into a Hollywood, who, for whom there is not a Hollywood movie made is someone who learned a lot about their field over many, many years, excelled in that field, and then went off to start something on their own in middle age, or even sometimes later,
James Altucher 37:09
I completely believe that like, just anecdotally, my own experience whenever I've started a business, because I thought, Oh, this is the next hot thing. It's always failed. But if I started something where it was an area that I've been doing first for fun, then for years for little money, and then became an entrepreneur, those would tend to be more successful.
Seth Stephens-Davidowitz 37:28
Yeah, they're like, in the data, there is like something close to a formula for entrepreneurial success when you look at the data, because the odds of success are so much higher. If you did something in that field showed success in that field, we're already making a good income in that field, and then went out on your own, when you had a lot of experience that feels like the chance of success are just monumentally higher, that doesn't mean that you can't start a successful business in your dorm room, or, you know, I there, there are people Suzy Betty's is one of the richest woman in the United States, she created a product PooPourri which lower which gets rid of the smell indemnifications You pour it into your toilet bowl, and he gets rid of the smell of defecation and she had no training in the field. She wasn't a chemist, she wasn't, you know, a scientist, she wasn't anything. She just kind of had this eureka moment and did it and it happens. It's not like a It's not like it's impossible. But I think people hear those stories and they get and they and they and they think that that's likely to happen. Whereas it's it's not. There's clearly mathematical, mathematic goal evidence and data that shows that your odds of success are just way higher. If you've previously if you have experience and success in a field over a long period of time.
James Altucher 38:49
Well, you know, as someone who is aging, this is I mean, everybody's aging, but as someone who's getting older. I'm older than I was when I started a lot of companies. And this is encouraging news. What other age related things surprised you like, you know, people always say mathematicians do their best work in their 20s. But I'm not sure this is true, either. I read one study where if you judge success in mathematics by how many other papers reference a paper you wrote, it turns out older mathematicians have more successful academic research published.
Seth Stephens-Davidowitz 39:27
Yeah, and part of a youthful advantage in some of these fields, is because young people just write more papers, partly because older people are busy on committees and things like that. So quantity adjusted. As a percent of papers written there, even 10 tends to be more of an advantage towards older people, but some older people just aren't as driven and don't put as much work out there. There are some advantages to youth definitely in art Professor galenson at University of Chicago has basically found that there are two types of artists. And one, one type of artists just blows up on the scene at a very young age. And that an example of that is someone like Bob Dylan, who I think most people agree. And even Dylan himself said that his best work was done in his 20s. But there are other artists, who are more experimentalists, and tinkerers, and those artists tend to get better with age. So an example of that would be Leonard Cohen, who wrote his best work probably in his 50s. So there can be advantages to youth that some people there, your brain, you know, does have more horsepower at younger ages. So for poets, mathematicians, there definitely can be advantages that some people take advantage of, to do great work at a young age. But some of the some of the advantage of youth is a myth in many in many domains, certainly in entrepreneurship. And the other thing about the study of entrepreneur doors and age is it's true even in the field of tech. So you'd say okay, I understand how that would be true in some really boring business. But tech is such a fast moving field, with all this new technology, you think in that fields, you need to be really young to understand the newest trends. But even in tech, the most successful entrepreneurs tend to be in their 40s.
James Altucher 41:27
So interesting. And because that does go against a lot of basically you're you're busting mythologies with with data, which is kind of the story of history, like the the story of history is basically new religions and new belief systems completely developing because New data shows the old belief system didn't work. So like Christianity, for instance, had to evolve. As we learn more about the shape of the universe.
Seth Stephens-Davidowitz 41:51
I was reading recently, there was some study, people had all these ideas that like certain superstitions around the age, that there are certain years that just people die a lot. And then someone collected all this data and found that that wasn't true that your chance of dying, you know, where there were no jobs at a particular age. And that really did change things about how people viewed it did the data actually worked in kind of getting rid of those myths? And a similar recently, there have been papers, analyzing a birth, time of birth, and basically horoscopes. So do you see personality differences? For people born, you know, for Virgos or Tauruses or whatever they are, I don't even know all anything about Horoscopes. But do you see these patterns? And not surprising to me, there were no relationships, there's no difference. You know, these these things are all myths. The idea that people born on particular bonds, or particular dates are going to take on certain personalities is not true at all. And we'll see if that I wouldn't be shocked if that does lead to fewer people. Following horoscopes believing this astrology.
James Altucher 43:04
This always assumes that people read academic papers, which they don't well, like no one cares actually about facts.
Seth Stephens-Davidowitz 43:10
Well, it's not. But then you have popular science writers. So now I'm kind of moving into the arena of Popular Science. And now I'm spending a lot of my day, reading a lot of academic journals and being like, and trying to get these ideas out there and making them entertaining for people and going on podcasts and talking about them. And, you know, I'm actually surprised by how much credence people give to data. And if people are willing to change their mind more than I expect, when you show them a compelling data point. In that direction, I don't kind of agree there's a notion that everyone's so stuck in their ways that they just ignore facts. And it hasn't been true. In my experience.
James Altucher 43:55
You know, it's interesting that, you know, you mentioned earlier that you Oh, you were talking about penis size, that it fit a normal distribution. So, you know, normal distribution is, how would you describe it to somebody, it's like how our tests were graded one of our kids, it's, you know, the idea that there's an average. And if you're, if you could beat the average person at something two out of three times, then you're one standard deviation away, if it's like, I don't know, four and a half out of five times, you're two standard deviations away and so on. But then you have people like Nassim Taleb, who believe that most domains could be better modeled by some sort of power law distribution, like the way earthquakes are modeled. And, you know, so financial markets, for instance, are normal until they aren't is kind of the the expression like you could use a normal distribution model of the stock market to make money year in and year, you know, year after year after year, and then suddenly, you'll lose all your money because of this black swan event. And so there is a risk to data.
Seth Stephens-Davidowitz 44:58
Yes, that's so you seemed Talib kind of popularizing some ideas by Benoit Mandelbrot says that a lot of financial markets are run by power laws where a normal distribution, there's an average and most of the people will be very close to the average. You know, as you get further and further from the average, you get fewer and fewer people there. And to a point that if you're talking about three standard deviations out from the mean, they're very, very few. And then 5678 standard deviations of just like nobody. And power laws are a little different. We're even way out numbers way out there, they still happen. So wealth is an example of this, where if wealth was a normal distribution, you'd have everybody you know, we'd have you'd have the average, let's say, you know, the average wealth in the United States, which I'd have to look up what it is, but $121,000 is the median wealth in the United States. 121,000 median wealth, and then you'd have most people right here, 121,000. And you'd have, you know, only very few people, you know, above 300,000. And then you'd have, you know, nobody above 10 million 20 million, let alone 100 billion. And what we know is that wealth doesn't work that way at all, that it's it's a power distribution. And some, you can have people very, very far from the mean, you know, I think that's I don't think that that argument goes against data science, it just shows you have to correctly analyze the data and know whether you're dealing with a normal distribution, or a power law. And there actually, there are usually ways you can figure out whether you're going to do power law of power law, laws tend to come from anything with kind of multiplicative effects, where some additional edge is going to lead to even more edge. So that certainly happens in wealth, where if you get you know, some people start using your product, you get some capital, you can build on that into an and build even more wealth, it happens in city size. So city size is also a power law zips law, it's a power law distribution. And if you are, if your city is popular, more people are going to move there. And it's going to feed on itself and lead and the the biggest city is going to be far bigger than we expect if city size was a normal distribution. But some things like IQ height, don't have that phenomenon, where they're just the, to the best of our knowledge, they're kind of additive effects of various of a whole bunch of genes. And having one of those genes doesn't make you more likely to have another of those genes. So there's nothing that's leading to these power law effects.
James Altucher 47:46
Yeah, that's interesting. And then you could say, okay, in, you know, a normal distribution, like if you want to predict stocks, for instance, most of the time, probably a normal, a normal distribution of price movement works. But there are situations where everybody is either buying or everybody is selling, there's like, there's too much panic or too much greed, and then it kind of flips over into a power, power law distribution. Yeah, like on a normal day, like, like, right, like last month, people were a little too panicked. And so anything could kind of happen. But on a normal day, where maybe the markets going to go up, maybe it's going to go down, nobody really knows nobody, that then a normal distribution tends to work better.
Seth Stephens-Davidowitz 48:30
Yeah. And that's actually another example of I would say that's another example of using data to do better in a field and even become rich or I would say that Nasim Talib success came from reading the work of metal bright, who he says he was a big fan of that first said that stock prices didn't follow a normal distribution, basically looking at data collecting a huge data set of stock prices and commodity prices and saying that they fell by power laws and realizing that Talib real Talib, from that data, realize that extreme events were underpriced in the market. And there was a disk, there was an inefficiency. And you could make money by betting on extreme events. Because the probabilities, those events were priced as if the data fit a normal distribution, whereas actually they fit a power law.
James Altucher 49:27
Well, it's interesting because and you refer to this in the book, something that Peter Thiel said that a good business is all about what I forget the exact quote, but a book good business is about what secrets you're unveiling. And that's the key to making a great business. And it's because there's a big it's because somewhere, there's this arbitrage between how people value something based on what they expect that something to be, and there's a difference between expectations and reality. And so Like if you were starting a business, how would you use that concept that Peter Till's concept that a business is all about? What What secrets you're sharing? How would you use that to start a business?
Seth Stephens-Davidowitz 50:11
Yeah, I think the examples we talked about have been, have have fit that that model. So Jeff Seder had a secret about horses, that the left ventricle turns out to be really predictive, not seem to leave had a secret about the market, that it's more power distribution than people realize. Zuckerberg had a secret about people that they're more nosy than they let on. As I talked about everybody lies. And I think the key to using secrets to start a business is you don't always have to be the first one to have noticed this or the only one who knows it. It still can be as long as it's not common knowledge or hasn't been, you know, Talipes insight that the market had more black swans than people realized or that were priced in again was not original Talib idea. It was, as far as I can tell, first found discovered by Mandelbrot, but it wasn't properly priced in the market. Similarly, with the A's and how they revolutionized baseball, they initially weren't doing anything proprietary. They were basically implementing ideas from Bill James, which had been around for decades. So Bill James, for decades was writing books about how baseball was how the how data shows that baseball teams are run all wrong and that bunting doesn't make sense. Stealing doesn't make sense, walks are undervalued. And baseball teams just ignored this. And then Billy Beane said, I'm going to use this, you could call it a secret. It's not that nobody knew it. But it was a secret in the sense that it wasn't being paid attention to by other baseball organizations. And being said, I'm going to use this secret to build a better team. And it basically largely worked.
James Altucher 52:06
Yeah. Or take this woman who made the the pooper Eva thing that makes deprecations not not smell. What would you say? I mean, it's not really a secret that people don't want to smell that or that they are maybe, maybe, or maybe the secret was, is that you could make it not smell like I didn't know, you could just pour something in the toilet that could make it not smell,
Seth Stephens-Davidowitz 52:30
I think from what I understood she, she did a bunch of experiments and largely got lucky. And that happens too, which is why I say that that is not a story you want to build your life around. Because it's not a scalable model to just, you know, like, a lot of things in life have been serendipity. And you know, you maybe want to put yourself in situations where serendipity becomes more likely. But you don't want to assume that serendipity is going to happen or assume that's a assume that that's a great path to life success.
James Altucher 53:06
But but you use the same word when describing her and Jeff Seder, which is that they both did lots of experiments. So the good thing about data modeling is that you could have a theory and then you collect the data. And you test the theory is right based on the data. And you're going to be wrong. A lot of the time, the data will tell you whether you're right or wrong. And the theory is just a theory, but the data will tell you the truth. And so maybe a key is always be willing to be persistent about these experiments with data.
Seth Stephens-Davidowitz 53:36
I think that's right, and you got to be willing to fail a lot on your way to victory. Yeah, and then, I guess the other thing is when you have that victory go all in. So a lot of people if I had played around with various chemicals, and thought that I found the one that did that got rid of the smell of feces, I probably would have convinced myself that was insane and gone back to writing books. But I guess having the hutzpah to say that I figured something out that is can lead to hundreds of millions of dollars can be can be good.
James Altucher 54:15
I mean, I have so much stuff. Outline, I don't even know where to go. But oh, you know, what was interesting was the data about stories that, you know, people had modeled, like, I guess hundreds of stories, and, you know, sort of showed that each one had, you know, every successful, let's say novel, or play or movie or whatever, had a very specific kind of arc, and it was roughly like the arc of a hero. But there were like more components to it. Like what, what interesting thing did you derive from that?
Seth Stephens-Davidowitz 54:48
Yeah, as well as using something called sentiment analysis. So that's a tool that data scientists use where certain words are positive words. So happy good. Certain words are negative. Words such as sad or bad, and you, you analyze the positive or negative words, you can see that the sentiment of successful plays movies stories tend to follow certain paths, there isn't one path, there are a whole bunch of them. But they're there, the data scientist has discovered about six of them. Which is pretty cool. And if you're trying to write a story, I definitely read that work and try to see if you fit them if you fit one of those models. Because if you don't, it seems like
James Altucher 55:30
they differentiate it from stories that weren't successful.
Seth Stephens-Davidowitz 55:33
Yeah, exactly. So. And yeah, if you don't have that pattern, you're less likely to be among them, the more successful stories. So it's interesting also, because I think sometimes data sharpens the picture in that, like, there have been definitely Hollywood that I've read many books over the years of people from Hollywood talking about what makes a great story. And some of the patterns uncovered in data science, were hypothesized, but I don't think anybody had found these are the six, exactly the six, you know, types of successful stories. And that type of clear, sharp picture, you frequently can only get in a convincing way, if you analyze lots and lots of data.
James Altucher 56:21
Again, one other one other area that you researched in the book or afterwards, did you suddenly realize, oh, my gosh, this is, this is this big secret, I never could have imagined this.
Seth Stephens-Davidowitz 56:34
Ah, let's see there. Oh, this is one for my upcoming book, don't trust your gut. They, these scholars, they analyze tax data, digitize tax data, and basically studied every rich person in the United States, they have this sentence in their paper, I couldn't believe it didn't get more attention. They go the typical rich American is the owner of a regional business, such as an auto dealership or beverage distribution company. And I just read that I'm like, What the heck, like that was not who I thought of as the typical richer American in the United States. And so I read the paper closer. And then I also did some of my own data analysis based on some of their comparing their charts and some other sources. And you kind of see that, like the like, who gets rich in the United States? Well, it's mostly people who own who don't rent, who don't rent their time, who don't have wages. So it's there's rage about three to one in the month, in the month, the richest Americans and owners versus wage earners, which I kind of figured out over the years, but I definitely did not know that when I was 20, or 25. And that, it seems like there are certain industries that are just really, really good at creating rich owners. So auto dealerships is one of them. Beverage distribution, some other middlemen, investing in real estate, that's kind of well known market research. And it seems like what these company what these industries allow is a lot of local monopolies. So auto dealerships are regulated local monopolies, where you only can start there. If you have a auto, if you're the auto dealer for a car company in a region, basically, you're you're protected by law from competitors, which is a very good place to be as a business. And, but other companies kind of have the have these flavor as well. So market research is a very scalable business, you can kind of write up your reports on your very dish interest, and then sell it to a whole bunch of people. And it's hard for someone else to have that same the same contacts that you built in your industry, to compete with you to just totally take away your prices. Beverage distribution is a regulated industry also helps investing in real estate, kind of hard for one firm to totally dominate because each invest in each investor, kind of many different investors have their own strategies and are able to differentiate or claim their differentiating in ways that allow them to make money.
James Altucher 59:06
Also, there's 100 million homes out there. So yeah, you know, but it's hard for one person to have 100 million homes.
Seth Stephens-Davidowitz 59:12
It's true, but there are 100 million homes who need painting. And paint companies that are painters aren't do it creating a lot of billionaires, because they just people just ruthlessly compete on price on those in many of these industries. So there are only certain companies that allow you to kind of avoid for whatever reason, this ruthless price competition that destroys a lot of businesses. And so they caught the combination of the you need to be in a business, you have to somehow kind of build some sort of moat, either with the help of law, or the help of scaling or the help of industry contacts. Somehow you got to prevent just being like, you know, a lot of these industries that aren't creating millionaires where people start businesses, people just search on Google and pick the cheapest one, and you're just destroyed. You know, all your all your money goes to advertise competing to be higher on Google's advertising you know, to the high higher ranked in Google ads. So so that, you know, is basically the thing I took from this the data is business is where the money is, but it's particular businesses. And the other thing in the data, which I kind of also learned over the years, but was really striking is like sexy businesses just freakin suck. So like the quickest, the quickest field, the field with the shortest average lifespan is record stores, the average record stores out of business and 2.5 years. And other businesses that are right near the top of the list of worst businesses, the shortest lifespans are toy stores, clothing stores, makeup stores, game stores. And, you know, that kind of goes to the Suzy Betty's lesson, which is if something's kind of seems kind of cool and exciting, and makes for a great story. People jump on it. And too many people jump on it. And it's actually a horrible career decision. So you don't you Yeah, you don't want to learn from Richard Branson's success in record companies like that was a one off thing. Don't read his biography and try to pick up lessons like just look at the data and know that the average record store I mean, nobody goes to record stores anymore. So that's part of it. But in the same way, you know, all these sexy store store sexy companies. They're just awful businesses.
James Altucher 1:01:32
No, I agree. Like, somebody once told me that the uglier of a business, the more likely you have a chance of succeeding. And so this guy, specifically he was in the business of collecting trash, and then finding them, he would filter out the metal that was in the trash and he would melt it down and sell it's called slag, he would sell this slag to, you know, as a commodity, metal commodity. And it was just an ugly business. He was basically this enormous trash collector, but he'd make money on you know, he had a process for weeding out the metal and selling like the aluminum and selling it.
Seth Stephens-Davidowitz 1:02:11
Yeah, but I think oddly is a necessary but not sufficient condition. Because you can just be stuck in ruthless competition. Even a lot of ugly businesses like bog exterminator, nobody wants to do that. But I think the data is pretty clear that people aren't getting rich doing that. Because they're just in ruthless price competition. So it's not, it's not just as simple as pick something boring. And you're, you're good to go. You really got to always be thinking of how can you have your little moat around competitors. So you're not just stuck in horrible price competition,
James Altucher 1:02:40
right. And scalability is important to like exterminators might not be able to scale.
Seth Stephens-Davidowitz 1:02:45
Yeah, exactly. Although like scalp is another thing where it's can be a little overdone, where if it's too scalable, it also becomes a dangerous business for an individual. It's a good business if you're an investor. But like if you start a social media company is incredibly scalable. But it's so scalable, that we end up with like a few social media companies. And that's it, which is also not necessarily a great place to be from an individual entrepreneurs perspective, because your life becomes almost too much of a lottery. And it's better to be more to, and it's great if you're an investor and you can make 1000 investments and just pick all the social media companies just say I'll get, I'll end up with whichever one wins this scales correctly. But an individual I think you want like, I always say local monopolies are good, you want scale, but not too much scale is a good place to be because then you can avoid price competition. But you can also avoid this winner takes all phenomenon, where you're just like, where, you know, there's a few sneaker companies that win a few social media companies that win. And I think as an individual, that's a dangerous, that's a dangerous life path. It it may work. But that's kind of one of those things where you get if you if the universe plays itself 1000 times you get rich in three of them, I think it's better to try to make life decisions where if the universe plays itself 1000 times you get rich and 500 of them, 600 of them 700 of them.
James Altucher 1:04:23
Tell me about the next book. He said you're working on another book, and we talked earlier about it. It's kind of like using data to sort of, you know, improve your life.
Seth Stephens-Davidowitz 1:04:32
Yeah, it's called Don't trust your gut. Don't trust your gut. And
James Altucher 1:04:35
it's gonna end it's coming out in May. We're and we'll have another podcast about it. But let's talk just a tiny bit about it now, like, what are some of the things you'll be sharing in that book?
Seth Stephens-Davidowitz 1:04:44
Yeah, so I basically just read, I kind of retired myself from my Google Search Analytics and read every academic study I could find on big life decisions and what is the data tell us and present that as trying to help people make better life decisions. The motive one of the motivations for this is I'm a huge baseball fan. And we talked about Moneyball. And I kind of realized that baseball has changed so much, since due to the Moneyball revolution, so when I was a kid, the game of baseball look different, like the infielders all stood in the same spot and every play, and now every play, the infielders are all over the place, there's something called the infield shift, which data scientists discovered was actually a better way. It looks insane, but you put mostly infielders on one side of the field, it actually leads to better outcomes. And I was thinking about, like, our personal lives, and I feel like most of us don't really use data driven, make data driven decisions, we generally do what feels about right, and go with our gut. So kind of what would a data what would a data driven life be like, and I think the area where there's the clearest and the body ball analogy extends best is dating. So there have been studies, there's a work by Samantha Joel, where she studied 11,000 Romantic couples, and she had every she worked with 85 other scientists, she had every possible trait, you could measure on them, their sexual tastes, their demographics, their values, that their physical appearance as ranked by other people, and she could and how happy they reported being in that relationship. And she and the other scientists use machine learning to try to find what is it about a person that predicts you're going to be happy in a relationship with them? And the over arching lessons is that it's incredibly hard to predict who makes someone happy. Like it's shockingly unpredictable, you would think that like many qualities about a person would dramatically improve the odds, they make you happy. And it seems the data it's it's, there are some things that moderately improve the the odds, but they're not that big. And this, The striking thing about that study, is you contrast that with scholars have studied online dating, and they've bind through, you know, everybody's clicks and messages. And they say, Okay, what makes someone desirable in online dating, and that is incredibly easy to predict. So it's, it may be hard to predict who's a good romantic partner, but it is so easy to predict who's desirable partner. In fact, they can even predict with high accuracy, not just whether you're going to swipe left or right, but how long it's going to take you to swipe left or right. Because if someone's close to your barometer, it's going to take you a little bit longer to make that decision. So like we're just lemmings on these online sites, and what predicts someone's more likely to be clicked. It's their beautiful, not surprisingly, that's by far the biggest predictor it explains conventionally attractive people way more desirable, tall men. Each inch of height they scholars have found is worth about 40, you have to make about $40,000 of income as a man to overcome like one inch by one inch shorter. certain occupations not in women in men, lawyers, people in the military do way better in online dating students do horribly. I spent most of my life as a student and did horribly in dating. And now I know the reason for that. People work in transportation, in hospitality disaster for men on dating sites, similarity to oneself, people are drawn, there's this idea that people are drawn to opposites, it's totally not true. Just about every dimension, scholars can measure people are drawn to people who are similar himselves even on still seemingly silly things like how many photos you include in your profile, and my favorite, that people are 17% more likely to match with someone who shares their initial on an online dating site. Like totally ridiculous. If someone shares your initials, you're more likely to batch with them even take into account everything else like their religious background.
James Altucher 1:09:07
I'm just curious. So on an online day, this is not relationships like long term relationships or marriage success. This is just being selected for a date. People will subconsciously note oh, this person has 12 photos that they're sharing. Yeah, I have 12 photos and so they're more likely to click on that. Yeah, that must be just a subcon.
Seth Stephens-Davidowitz 1:09:23
Yeah, must be subconscious and initial. The same thing.
James Altucher 1:09:27
I just have a question like for all the ladies out there. Jay, the producer of this podcast is is recently single and then what's your J do on his dating site profile?
Seth Stephens-Davidowitz 1:09:38
Oh, well, so I think there have been some measures there have been some ways you measure success. I always think more how you pick someone, not how you improve your profile. There's some obvious things have better pictures. This one caught me by surprise. Like I had horrible pictures because I didn't really care what I look like and then I improved my pictures and I dramatically improved by dating process. There is some evidence, it's the most interesting evidence that you can improve your dating success by being an extreme outlier. So I said that it's predictable what people click on and online dating. And you know that conventionally attractive people, taller men, men who are lawyers or military people with things that you can't necessarily change are more clicked on. But there's some evidence that if you don't, you aren't, weren't gifted some of these traits, if you're not a six, three gorgeous male, or a gorgeous woman, you can do better by like, take a being an extreme version of something having a high variance. So Christian writer has discovered that if you have a higher variance, if some people really like you, and some people really hate you, you'll do better. So people do well are like women with shaved heads, or people with colored hair, or people with really wacky glasses. And what happens then is that you turn off a lot of people, but some people are really, really into you. And that's all it really counts and dating is to have some people really, really into you. So that's kind of an interesting strategy. If you're not like lighting up the dating world on your natural traits. If you're not Brad Pitt, or Natalie Portman who everybody wants to date, you can sometimes have more success by being an extreme version of yourself. And then and then having some people extremely into. But the thing that I find the best strategy I find in dating, based on the data is it's very similar to Moneyball where Moneyball point out there's an inefficiency between what was valued in the baseball market and what actually made a good player. So data driven teams had success going with players that are example of Kevin Youkilis, who didn't look like a first baseman, he was kind of a little chubby, shorter than most first baseman. But he had these great stats that made him a good bet. And the data driven teams were obsessed with Kevin Youkilis, because other teams kind of weren't properly pricing him. And dating is exactly the same, where the fact that the dating sites show that people are, like, consistently drawn to these qualities that don't lead to long term happiness, conventional attractiveness, really tall, bad men in certain occupations, people are similar themselves, etc, that you can really hack the market a little bit by focusing more of your attention on some of the groups that are not getting the attention. So shorter males, for example, and I'm not just saying this as a shorter male, myself, I have a happily in a relationship. So I'm not this in self serving advice to try to get more woman intrigued by men like me, who are on the shorter side. But it is true in the data that there's zero correlation between height and long term happiness. But there's this incredible correlation between being clicked on in height. So for women who are spending the heterosexual women who are struggling to perpetually single and trying to date these six to six, three guys, well, you're calm, the competition for these men is ferocious. And if you end up with one of them, the data says you're no more likely to happy. And if anything, the fact that you ended up with them, it may be because they're so highly desired, they might have some other negative traits, like they may be completely have some very bad psychological traits that make them still available. It's a horrible place to focus your energy, focus your energy on these groups that aren't getting the attention, that that that they deserve. So, you know, even racial dynamics. It's a little, you know, politically incorrect, but there is horrific racism and dating that's been shown in many studies, particularly, for example, African American woman, huge penalty, it's hard. It's horrible. It's not talked about, we talked about racism and in careers and interpersonal dynamics and police stops in many in getting a taxi cab. We don't talk about racism and dating, but that's maybe the area where the evidence is strongest African American woman, Asian males do a lot worse, in many ways on online dating sites, and one of but if you look at correlations, long term happiness, there is zero correlation between the race of your partner and how happy you are. So it's another huge inefficiency, where the market is saying that certain races is being prejudiced against racist for no reason. And the actual suitability as a bait is not correlate with race at all, will focus more of your attention on these groups that aren't getting the love? And you're going to find you may get a mate with way better quality other qualities, because the rest of the market is punishing them. And I told this,
James Altucher 1:14:40
this idea, this is like great advice.
Seth Stephens-Davidowitz 1:14:42
Thank you. i It's almost too good advice because I told this advice to my girlfriend, and I think she's thinking of leaving me and finding an Asian American male who has better qualities than me. And using my advice against me or something. J stay tuned. Yeah, j you just need to wait for a book comes out and then you're in in good shape,
James Altucher 1:15:01
other than dating, like one of the domains is your book on the cover.
Seth Stephens-Davidowitz 1:15:05
Happiness is a big area where they've done all these studies. So I became obsessed with this project, map Enos, it's by this guy George McCarran and Susanna barato, where they've been pinging people throughout the day. And they're saying, What are you doing? And how happy are you? And like, correlate this with other things. Because from iPhones and there's other there's a Happiness Project, there are other projects, happy air does this, track your happiness. And it's like kind of a revolutionary understanding of what makes people happy. Because we haven't had that they've collected like billions of data points on, ask people how happy you are, and correlate with all kinds of things around what's going on with their life. And, like they found cool things like sports makes people miserable on average, because the average boost when your team wins is about three points in happiness out of 100. And the average loss when your team loses is seven points of misery. So basically, the average sports fan is making a horrible happiness deal, almost like a drug. That's another one. Another one they found is that alcohol gives people a mood boost. This is another study by McCarran where alcohol gives people a mood boost. But the biggest mood boost, and this is dangerous advice. So I don't I know if people have history of alcoholism in their family, I don't want to suggest this. But if you don't have this history, that the biggest boost, if you're drinking is if you're doing something boring, like the chores are commuting. And if you're socializing with friends or doing something fun, you actually get only a very moderate or no Boost, which is exactly the opposite way of how most people use alcohol. So most people, you're having a great time with your friends, you're like, well, now I'm going to make it even better by having having four beers. And the actual data is that it doesn't make people that doesn't actually prove your mood. But if you're doing if you're doing chores, getting ready to go out, like all these things, you're actually if you do it tipsy, you're actually like get this huge boost in happiness. So I've actually I don't have a history of alcoholism in my family. So I read this study, and actually started adjusting myself a little bit, where I'm like, okay, if I'm going out,
you know, if I'm going out with friends, maybe instead of having the beer with the friends, I'll have the beer like, in the shower while I'm preparing to go out and which and take that boring activity into a fun activity. And then I'm with my friends and already having fun, even sober, so I don't need to drink anymore. So I take these things a little too far. Like I actually, like I just read these paper and it totally changes my life. And I'm like, oh, now I'm gonna change everything. I think some people don't do that as much as as, as I do. But either way, it's it's good to know. And it's great to know, it's, it's, it's, it's always the other thing about these studies, is they're just interesting. The other thing that the data shows which was comforting, is we're kinda told that there's some secret to happiness. And there are some things that are counterintuitive drinking when you're doing the chores or drink when you're commuting. Or not watching sports, even though you think you love it. Like that's a little counterintuitive for a lot of these studies, like I described them to people and they'd be like, That's so freakin obvious. Like, people are happier in nature, people are happier when they're around beautiful scenery, or people are happier, the happiest single activity is having sex. And people are like, do we really need scientists to tell us this? Like isn't that, you know, pretty freakin obvious. Or people are happier on 80 degree in sunny days than they are when it's cold or rainy. It's like, you know, come on, like, that's just confirming the obvious, but I think they're saying a little profound in the obvious nature of these findings. Because a lot of the people are criticizing me saying all these you know, criticize me are really the scientists who who publish these work these discovered these things or are saying, Oh, come on. I didn't need a scientist tell me that. But then you look at their actual life decisions. And they're doing none of the things that the site these obvious things that make people happy. Most of the people who criticize me are workaholics? Well work is the second most miserable activity, the only thing that makes people more miserable on average than working is being sick in bed. So like, they're they're working all the time. They're not. They don't have great sex lives because they're too busy and tired from work. They're not spending time in nature, because they're living in cities where you know, where they get these lucrative jobs. So I kind of I conclude the book with what I call the data driven answer to life. And the data driven answer in life only uncovered by scientists versus McCarran Verado. Thanks to iPhones, thanks to 3 million pigs in cell phones, the data driven answer life is being with your love on an 80 degree and sunny day overlooking a beautiful body of water, having sex. And it's like it's the most obvious thing in the world. But like, just keep that in mind when you're complaining that you're miserable. Like how far is your life from that life of what actually makes people happy? And can you have spent more of your time doing these things? Very obvious data driven answers to life's, you know, to life's problems, which, you know, it's not necessarily, it's not so easy to be by the beach people are really happier when they're by water. It's not so easy to be an 80 degree in sunny climate, it's not so easy to have sex, you'd need to have a find a partner or you know, presumably, but as these aren't impossible, and I would, my advice to anybody who's miserable, is to ask whether they're putting enough time into organizing their lives. So they're actually spending time doing things that the sometimes obvious things that makes human beings happy.
James Altucher 1:20:39
That is so fascinating. This has been such an eye opening podcast, and I can't wait to come. So you're always welcome to come back. Give us more data each time and particularly for your for your this upcoming book. What's it going to be called again?
Seth Stephens-Davidowitz 1:20:54
Don't trust your gut?
James Altucher 1:20:55
Don't trust your gut? Is it on sale right now?
Seth Stephens-Davidowitz 1:20:58
Yeah, you can preorder it Yeah, I'm
James Altucher 1:20:59
gonna buy it right now. I'm gonna pre order right now. And definitely come back for that. And this has been great. Seth. So author of everybody lies, and soon to be author of a new book, don't trust your gut. Come back for that one that cut this coming out. And maybe we'll have you on before then. And thanks so much for coming on the podcast. Oh, one last question. Yeah, data has been a big topic in terms of COVID. Like, I don't know if there's any any insights there. But what do you see in the data about any data at all about COVID? That is unexpected. Well, the
Seth Stephens-Davidowitz 1:21:35
only thing is, when COVID started, I, I was using my Google Search expertise. Someone suggests I do this. And I think I actually found a new symptom of COVID. I'm pretty sure I did. I wrote a New York Times column, where I basically said that, like every time COVID was, every time every area that had a COVID outbreak, you'd see people search for eye pain. And like it was it was very clear and data was much higher than other symptoms, and nobody was talking about eye pain is a symptom. And then I published this in New York Times, I'm like, you know, I'm not an epidemiologist. But I just think people should look into this. Because, you know, I analyze the data as best I could, I've talked to her I could talk to, and as far as I could tell, I paid searches are rising every time COVID spikes in an area. And it's not due to people using their screens, more appalling rates, or other things you might think it's caused by. And then, like about a year later, the biggest study on eye pain, found that sore eyes was the biggest eye symptom of COVID, and a significant symptom and about 15% of patients. So I was pretty proud of that, even though it got like no attention. But it again shows to the power of data analysis and being willing to kind of put yourself on the line. You know, I talked about Stormfront when I wrote this article about the hate side of my dad told my mom that Seth has gone completely insane. And I think a lot of people that I said I paid the symptom. They're like Seth, not an epidemiologist, what's he doing publishing in New York Times article claiming he's found a new symptom. But as best I could tell, I was right about that symptom. And I think you have to be willing, when you have when the data shows something, and you've tested everything you can think, to test otherwise, to go with it, rather than your gut, basically, kind of similar to this book coming up. And this advice really talks about dating and like, you know, it might feel weird to shave your head or dye your hair or dress like a weirdo or be a total nerd. And, you know, you might think that's not the right approach to dating. But the data as has said, that that can improve your odds of getting a date by about 70%. So even though it feels weird or feels wrong, or seems a little crazy, I think you have to in this in 2022, you have to be willing to do things that feel a little wrong, but the data says are actually right,
James Altucher 1:23:52
man, I am I am loving this stuff I got this is gonna change my life. I'm going to start being obsessing on data. So, Seth, thanks again for coming on the podcast. I'm glad finally after six years ago, we talked about you coming on the podcast. Finally, you're on the podcast. It's it. This is so great. And I'm looking forward to the next one already. So thanks again.
Seth Stephens-Davidowitz 1:24:11
Thanks so much, James. This has been fun