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The Melanie Avalon Biohacking Podcast Episode #175 - Seth Stephens-Davidowitz

Seth Stephens-Davidowitz is a data scientist, author, and keynote speaker. His 2017 book Everybody Lies was a New York Times bestseller and an Economist Book of the Year. He has worked as a contributing op-ed writer for the New York Times, a lecturer at the Wharton School, and a Google data scientist. He received a BA in philosophy from Stanford, where he graduated Phi Beta Kappa, and a PhD in economics from Harvard. He lives in Brooklyn and is a passionate fan of the Mets, Knicks, Jets, and Leonard Cohen.



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The Melanie Avalon Biohacking Podcast Episode #110 - Jon Levy

10:05 - Seth's backstory

11:30 - What Can Data Predict? And Why?

14:40 - emotional red flags

15:45 - feelings on the first date

16:15 - data gathering for relationships

17:30 - the root of attraction

23:00 - age gaps in dating

25:50 - attractiveness of careers

26:30 - racial disparity in dating

29:00 - predictors of happiness

30:15 - cliched pieces of wisdom

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35:30 - dietary wars

38:30 - physical appearance and success

42:10 - Implementing changes based on data

48:00 - sports genes

51:00 - having enough data points

52:20 - how having passion predicts success

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57:30 - data on parenting

1:01:30 - parental decision making

1:05:00 - gene editing

1:06:25 - the mappiness project

1:08:00 - what makes us happy?

1:12:25 - alcohol & happiness

1:14:00 - the day after drinking

1:16:45 - blue zone lies

1:20:20 - success in business

1:25:50 - applying the data personally


Melanie Avalon: Hi, friends, welcome back to the show. I am so incredibly excited about the conversation that I am about to have. The backstory on today's conversation, if you listen to the interview that I did with Jon Levy for his book, You're Invited, that was a really fun and fascinating interview, because it went into a lot of topics, not so much health related, but more social related, why we do the things we do, and how we're connected to people. And Jon connected me, appropriately enough, to his friend, Seth Stephens-Davidowitz, who is a New York Times best seller. I was familiar with his first book, which was called Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are. But Seth had a newer book coming out called DONT TRUST YR GUT: Using Data-- I can never decide if it's day-ta or da-ta, but Using Data to Get What You Really Want in life. And just seeing the title, I was immediately very excited about the concept. So obviously, it was immediate, yes and then I read the book-- I read a lot of books for this show, and this was one of those books where I just so thoroughly enjoyed the experience of reading it. Literally, it's just a collection of fascinating information about why we do what we do. And ultimately how we can potentially get what we want in everything in life, so happiness, romance, our careers, sports. It's fascinating. There's so much information, I have so many questions. I think you guys are really going to enjoy this conversation. So, Seth, thank you so much for being here.

Seth Stephens-Davidowitz: Thanks so much for having me, Melanie.

Melanie Avalon: To start things off, while we were talking right before this, about how you're connected to a lot of different social circles. I'm super curious, your backstory. Growing up, when did you become interested in data and information and figuring out why people do what they do and what they're going to do? How did that happen?

Seth Stephens-Davidowitz: My life has been totally, as far as I can tell, just like a lot of random steps that I don't totally understand. I majored in philosophy in college, which I think is only very, very loosely connected to what I now do. As I talk about my book, I want to be a professional athlete when I was a kid. That was all I really wanted but had basically no athletic talent. [laughs] But I think I've always been interested in people and yeah, I've always been interested in numbers and math. And I've always been interested in writing so kind of, when I did my first book, I realize kind of all that came together these interests I had, and then same with DONT TRUST YR GUT. So, I don't know. It felt very random, my career. People always ask me for advice and I kind of don't know what to tell people. Well, first, I wrote a whole book of advice. So, I tell them to just read the book. But also, I feel like my life is an anecdote, not data and for all I know, like all the things I did, or I just got probably lucky a few times. I don't know.

Melanie Avalon:  So, you just touched on a lot of keywords that I actually had questions about. So that's perfect, like anecdotes, data, random, luck. I mean, they're filtered all throughout everything that you just said. So, I have this huge haunting question, just using data and math to predict everything. Can it predict everything? What can it not predict? And then a broader question, which actually might be philosophical, so we can just tie that in too, if it does predict things, why? Is there a universal thing to all of humans that makes these things manifest predictably or is every single thing unique to that topic for why it can be predictable.

Seth Stephens-Davidowitz: Yeah. Well, answer to your first question is, no, data can't predict everything. But I think it's interesting and useful, the ways in which data fails and the places in which data fails. So, I talk in the book about this study by Samantha Joel, and a bunch of other scientists trying to predict romantic happiness. And they had this amazing data set that more than 11,000 couples, and they're trying to predict, that everything you could think to measure on that, their demographics, background, education, religion, race, their values, their beliefs about parenting, their hobbies, their interests, their sexual tastes, just this huge holy grail of relationship datasets, and they used advanced machine learning techniques to try to predict romantic happiness. I'm like, "This is amazing." This is going to answer one of the biggest questions everybody has in life. What should I look for in a partner and if they throw this data and the machine learning models, everybody can just then have-- when they're in a relationship, put their data in this model and the algorithm that tells them stay or go, and this is going to transform everything. It turned out that the predictive power was surprisingly low in predicting romantic happiness, and particularly predicting changes in romantic happiness. It's very, very hard to predict whether a relationship is going to get better or worse over time, knowing everything you can possibly know about two human beings in that relationship.

But I think there's something profound in the difficulty of predicting romantic happiness and changing romantic happiness, because a lot of us think we can make these predictions. So, a lot of us stay in really, really bad relationships. We're unhappy now but on paper we should be happy. So, this kind of has to work or we make the reverse decision, "I'm happy now but there are too many red flags. This is too weird or too different. This isn't the stuff of a long-term, serious relationship." And I think the lack of predictive power in relationships tells us that we're making a mistake. Basically, the only thing that predicts future romantic happiness is current romantic happiness. So, all of us should just kind of go with how we're feeling in a relationship and not think too much about the traits that we share or don't share with our partner.

Melanie Avalon:  Okay, if we're applying that to the red flags concept, would that mean that if it's a red flag that feels like a red flag, like emotionally it feels off, then you should go with that but if it is a red flag, just by like what other people would say, is a red flag, then maybe you don't have to worry about that as much?

Seth Stephens-Davidowitz: Yeah. Exactly. So, an example is, if I'm in a relationship, and I'm really, really happy, but we have different political views, and we come from very different families or maybe we have different religious backgrounds. But I'm happy. My partner makes me feel good, then don't worry about those seeming red flags, because the data says, that none of these things seem to have much predictive power down the road. Yeah, and again I think even more important is the reverse situation that probably many of us either have been there or know someone who's been there, where two people just look so good on paper, but they're not really happy. I think a lot of us stay in such relationships way too long.

Melanie Avalon: Does that mean if you go on a first date, and you're not feeling it right away, you should abandon ship?

Seth Stephens-Davidowitz: I think that it might-- I think give it a little longer than a first date. The study, usually it's people are ready in relationships for a decent amount of time. So, I don't think you can use this right away, necessarily on a first date. But definitely, if you're in a relationship for a couple of months, then you want to just pay attention to whether you're happy with that person or unhappy with that person. Don't pay attention on anything else.

Melanie Avalon: So just for gathering this data before dating apps, how would they gather this?

Seth Stephens-Davidowitz: Yeah. So before dating apps, there were these studies kind of predict what makes someone attractive. And it was basically just asking people, but that gets into the point of my first book, Everybody Lies, which is that people lie when you ask them questions on sensitive topics, such as what they're attracted to. Either they're lying consciously to you, or they're lying to themselves. If you ask people in a survey, "What are you looking for in a mate?", the number one answer will be someone nice, someone kind, right near the bottom will be someone really attractive or someone rich. So, it's very misleading as far as telling us what people are actually looking for. The data from dating apps is more, I think, revealing and a little dark, depressing because people are more superficial than they sometimes say. On just about on a lot of dimensions, everything from physical attractiveness and height, to race there's a lot of prejudice in online dating that's not always talked about.

Melanie Avalon: This is a huge question I have and I don't know how to phrase it, but I've been thinking about it while reading that whole chapter. We're using the word 'shallow' to define these characteristics that we're attracted to. But the root of attraction from an evolutionary perspective, I'm assuming it goes beyond our prefrontal cortex and has to do with who might ultimately be the best mate for us. So, how do we judge certain qualities as shallow or not. I think on the surface, people might say, "Oh, physical attraction is shallow, because that's just looks." But you could also see it as that's something very evolutionarily driven, that this person might actually be a better physical compatibility match for you. And then, there might be something like intelligence and that could be-- I feel we don't say it's shallow too-- or maybe some people do. But to go after somebody intelligent, but that is also in a way just a biomarker of social or intellectual fitness. Well, like I said, there's character traits like kindness and compassion maybe it's not shallow to want that, maybe that has an evolutionary spin, I guess, how do we judge?

Seth Stephens-Davidowitz: I think there are a couple points that are important to keep in mind. One is that there is at least some evidence that physical attraction can change over time. I talked about a study in the book where they asked people at the beginning, they asked college students of getting a class, who do you find the most attractive. Everyone kind of agrees it's people who have qualities that from an evolutionary perspective may suggest greater health, like symmetry of their faces. But then at the end of the class, they asked the same people who's most attractive. And the answers diverge because people started spending time with each other, and some of the people that initially thought, "Wow, they're really hot," well, you actually don't connect with them, you're going to find them less attractive, and people who you didn't think were that attractive, you spend a lot of time with them, you do connect with them, you find them more attractive. So, it is important to keep in mind that physical attractiveness can grow or shrink over time.

And then, an open question in my mind before seeing the data was does physical attractiveness correlate with long-term relationship satisfaction, since that's what a lot of us are after when we're searching for a mate. It's obviously different if we're looking for just a short fling but if we're looking for a long-term mate, we want to know what traits are most predictive of long-term happiness. And it could be, if you looked at the data, that people who end up with conventionally beautiful people end up happier. Maybe they have better sex lives or better social lives, and this really is an important predictor of long-term happiness. But if you look at the data, it seems to have just about no correlation with long-term romantic satisfaction. People end up with-- I guess conventionally, most attractive, people don't report that they're happier in the relationship than people who end up with less conventionally attractive people. So, I think it is important to keep in mind that wherever these desires are coming from, and I agree some of it is probably evolutionarily driven, if we're trying to maximize our long-term romantic happiness, we are being tricked to some extent by some of these qualities. So, I think it's just important to keep that in mind, that you're being tricked.

Another thing I talk about in the book is the romance is a market and it's a competitive market. You're heterosexual, and you're competing with 95% of people of the same gender for mates. And the fact that so many people are drawn to these qualities like conventional attractiveness, height in males, certain sexy occupations, it means that these people are going to be much more difficult to get dates with, let alone to be in a relationship with. So, I think a lot of people who are perpetually single, are trying and failing to date beautiful people. That's one of my diagnoses but I give people this advice.

I told some of my friends, I'm like, "Yeah, the good dating is, care less about beauty and hotness." And all of them are like, "Yeah, I'm not listening to you." So, this is hard advice to follow. If I'm being honest, in my own dating life, to be fair, I met my girlfriend, long-term partner, before I dove into this research, and I was basically attracted, immediately drawn to her because I thought she was really hot. Whether people actually follow this advice or not, I think it is important to keep in mind that we're all being tricked a little bit, in that the qualities that make us most likely to swipe right are not necessarily the qualities that lead to long-term happiness.

Melanie Avalon: It's funny to hear you say that, because I was wondering how the advice would land on people because you did have the sections about maybe you'd have more success with long-term happiness and even just making a match if you go for these undervalued qualities in people. But I feel the happy medium solution that you provided was turning it into a numbers game. Like basically, if you just ask out a lot of people, then the odds go up of making a match with somebody who might fall into your bucket of what you were hoping for with the attractive label. So interesting. Do you know if there's data on age differences in relationships, age gaps? I'm asking for personal-- I've always dated older, so wondering about that. 

Seth Stephens-Davidowitz: Yeah. It's a moderate predictor, remembering from the Samantha Joel study, which I don't, I'd have to look at it again. It wasn't like a zero predictor like attractiveness and height. It was more of a predictor where I think a big age gap are negative predictors of lasting relationships. I think there also is obviously evidence that age plays a big role in desirability in online dating as well. 

Melanie Avalon: Younger for women and older for--.

Seth Stephens-Davidowitz: Yeah. Men kind of hit their peak in their mid-40s according to the data and women hit their peak very, very early. But yeah, I don't know, which is I guess another superficial trait that people care too much about.

Melanie Avalon: I feel like there's reasons behind it, that we're not consciously aware of-- just as far as I guess for age for a man, it would symbolize security and finances. And for women, it would be reproductive ability, maybe?

Seth Stephens-Davidowitz: Yeah. Well, someone I was on a date with once said, that all men think they're going to be most attractive. They just want to be patient, wait until they hit their 40s because then everyone will be into them. Her hypothesis, which I haven't seen data on, but was interesting, was that men, they basically have their 20s and 30s, to prove themselves, and then the 40s, they either prove themselves or they prove that they couldn't do it. So, there's actually more variants. So yeah, if you're 40 something and you sold five businesses and are worth $100 million, you're going to do really well. If you're 40 something and you haven't had a job and are addicted to drugs and play videogames all day, you're going to do even worse than you did when you were 30 when at least you had some potential. But I think on average, men do get a little boost in their 40s.

Although I think it's not necessarily-- if you actually just go based on pure looks, I think men and women both are most attractive in their youth, in their 20s. So, I think, men also, if you look at something like men featured in pornography videos or various other studies, they're most likely to be in their early 20s, as well, or mid 20s as well. So, it's not women who are swiping right on 45-year-old men are like, "Wow, these guys are so hot." It's more like, "These guys could make reliable fathers."

Melanie Avalon: You had a lot on the male jobs that women are attracted to but I don't think there was any data on female career? 

Seth Stephens-Davidowitz: Well, because the study suggested that it doesn't matter. 

Melanie Avalon: That's why I thought the answer was.

Seth Stephens-Davidowitz: It's basically not statistically significant that women in all different jobs are equally attractive to men, so yeah. I guess data from dating sites uncovers some uncomfortable truths, that maybe some of us have suspected but kind of can be proven in the data, I don't know. I kind of don't shy away from these uncomfortable truths but some people might find them disturbing. I find them disturbing. I found this dissection on race very disturbing, the racial preferences that people show in dating. 

Melanie Avalon: What were some of those?

Seth Stephens-Davidowitz: Well, that African American woman and Asian males face a big penalty in online dating. Again, when we think of racism or discrimination, most of the studies and most of the political activism have focused on the criminal justice system and employment market and those are obviously really important. But I think if anything, there's even more evidence for discrimination in the dating market. Definitely African American women, the discrimination that they can face in online dating isn't talked about enough in many ways because most of us, one of our main goals in life is to be in a happy, committed relationship. So, this prejudice is a huge stain on society, I'd say.

Melanie Avalon: That's a social political issue that I don't even know how you would approach it, because presumably it might be unconscious or subconscious racial biases where they're not going with certain races, but how would you tell people to feel attracted to something that they don't perceive that they're not attracted to even if they don't realize it's related to racism? I don't even know how you would have a conversation to change that.

Seth Stephens-Davidowitz: There is not an obvious solution to the issue because I think we correctly value people's right to date people that are most attracted to, but it's just kind of interesting and disturbing. Maybe it should be talked about more, I think, just because when I think of people talking about discrimination racism, it's very rare that people focus on the dating market. I think the evidence for it is overwhelming.

Melanie Avalon: Did you watch Love is Blind?

Seth Stephens-Davidowitz: I've heard about it. I didn't actually see it. 

Melanie Avalon: It's like trying to tackle this question. I've really don't watch reality TV show. But I don't know why I love this series. [laughs]

Seth Stephens-Davidowitz: I was in my 20s, I was super into reality TV. I watched I think all the dating shows. Remember ElimiDate? Yeah, I don't know. There was one on MTV, Next, where you just kind of go-- you feel rejected really quickly. I don't know, it was weird. 

Melanie Avalon: I was on an episode of Millionaire Matchmaker once that was a fun time. The takeaway I did take away from the dating section that I thought was inspiring, was the role of predictions of happiness involving the questions that you asked about the actual person, rather than the other person. Basically, that happiness might involve if you are happy or satisfied or content.

Seth Stephens-Davidowitz: Yeah. So, the study that I talked about the 85 scientists, in general, they found it very difficult to predict romantic happiness. But if there were any variables that had predictive power, they were mostly questions about yourself and your own mental state. So, if someone says, "I'm satisfied with life independent of my romantic partner, not depressed. I'm not feeling anxious," then they're more likely to say that they're happy in their relationship, significantly more likely to say they're happy in their relationship. So, it kind of goes with this kind of classic advice that someone else can make you happy until you're happy with yourself. I think there's a lot of truth to that in the data. Sometimes, data kind of confirms these cliched pieces of wisdom that something that annoyed me, because I'm always like, "Yeah, how do you know that's true?" But actually, once I see the data, I'm like, "Yeah, it actually is true."

Melanie Avalon: Like most of the time, there's a seed of truth to them, or they wouldn't have become a cliché?

Seth Stephens-Davidowitz: No, I would say most of them. So, one of the things that I tried to do with don't trust your gut is just say what the data said, whether it was supported conventional wisdom, or opposed conventional wisdom. Because I think too many books, they do either one or the other. They always say, "Yeah, follow your heart. Do all these things that sound good." They read to me like Hallmark cards. And too many books do the reverse where they're like, "We're going to bust conventional wisdom and show you only things that are counterintuitive." I really tried not to do this, to do that with this book to just always go with the data. I'd say probably 60% or 70% of the time the data tells us what we probably would have guessed, and then 30% to 40% of the time, it tells us something different than what we might have guessed. So, that will be kind of my estimate based on after having written this book.

And the point I take from that is you basically just can't listen to normal advice because we have no idea whether the advice is true or not. We have 60% to 70% chance it's true, but 30%, 40% is not true. So, you always have to go to the data either to confirm it, actually, you can only really can expect to be happy in a relationship once you're happy by yourself, or sometimes it overrules what we might have thought before looking at the data.

Melanie Avalon: Selfishly, I would love you to write a book on the data behind all the different diets. Because there's so many dietary wars and it's so hard to see past biases and cherry picking and stuff like that.

Seth Stephens-Davidowitz: Yeah. I don't know. I kind of-- I tried to have a chapter about all the major questions of life. But obviously, it's going to be biased by my own interests. And for whatever reason, I've just never been a dieting person. I'm an obsessive sports fan. So instead of a pretty obvious chapter on the data of dieting, I think which a lot of people would have liked more, I had a chapter on how to achieve athletic greatness, which I think didn't really register with that many people. But I'm the author of the book, and I have to keep myself engaged.

Melanie Avalon: You get to decide.

Seth Stephens-Davidowitz: Yeah. I got to decide and books are such a pain in the ass, that you can't really spend too much time on topics you're not passionate about. 

Melanie Avalon: I cannot agree more. Even with this show, I really only bring on things I'm really excited and interested in. Did your publisher try to-- did they want you to have a diet chapter.

Seth Stephens-Davidowitz: No. They just wanted me to finish the book because I was taking too long, I think they're just like, "Yeah, whatever you say at this point. [laughs] We need to get this thing done. This is taking way too long." But the one thing I will say I did do a little research on dieting although I didn't turn it into a whole chapter, there does seem to be increasing evidence that there is tremendous variance in what diets work for different people, probably having to do with our microbiome. So, we kind of think that food is either good or bad, so carbs are either good or bad, chocolate is good or bad, broccoli is good or bad. And my understanding is the research is moving towards an idea that what is good for one person may be bad for another person, what's bad for one person may be good for another person. There's some people who might gain weight eating bananas, and more people probably would lose weight eating fruits and vegetables. So, I think there's some projects that claim that you can use machine learning and AI to figure out quickly what diet works for you. I think they're not quite there yet but I think that's where this is ultimately going to land, which is a personalized diet. A lot of people who struggle with weight. There may be foods that they think are really good for them and they think they're really being healthy and that may be good for the average person but for reasons that aren't fully understood having to do with our guts, they're actually bad for you and causing you to gain weight.

Melanie Avalon: That's good to hear because that's pretty much what I've been thinking. Actually, another book I'm reading right now is literally all about that. So, I'm all about individuality. I don't think there's one right diet for everybody and I do think it's a lot of factors like gut microbiome and glycemic control, how you react to foods and that might even relate to the microbiome-- and yeah, there's just a lot of factors. So many other topics to touch on.

Just while we're still in the attraction world, you talked about an interesting experiment you did with yourself, with your physical appearance and how does physical appearance affect our success in life. So, what was your experience and thoughts on that?

Seth Stephens-Davidowitz: There are all these studies, these are also disturbing in my opinion that you can predict how far someone's going to advance in their career based on what they look like. So, Alexander Todorov, University of Chicago, just shows people pictures of the candidates for elections. And you can predict that about 70% accuracy, which candidate won just by asking people, which one looks more competent. Again, we'd like to think that we're electing the person who has the best policy ideas or the best resume, or the most compassion. But it seems like frequently, we're just electing people who looked the part. And there are other studies that the people who look more dominant are more likely to rise high in the military, and people who are more baby faced are more likely to get off on crimes. 

Melanie Avalon: That's concerning. 

Seth Stephens-Davidowitz: Yes. That's very concerning but that's depressing. But there is something that maybe is a little more optimistic is that they've also done studies that how we look can vary a lot. So, whether on all these dimensions, attractiveness, compentence, trustworthiness, dominance, small changes, and how we look can lead to large, small changes we make to our face can lead to large changes in how we're perceived. So, I kind of motivated myself to do a study where I created using this app, FaceApp, its artificial intelligence created about 100 versions of my face. So, this is what I look like-- So, there's version of me they're virtually with, without glasses, with a beard, without a beard, with a goatee, no goatee, smiling, not smiling, gray hair, brown hair, pink hair in one of them. And then, I asked people, how do I look on many dimensions, one of the main one is competence. And it turns out, there are big differences in how I'm perceived. And basically, I look best I found out when I have glasses and a beard. People just take me a lot more seriously, which I hadn't known before looking at the data, and was pretty enlightening. And now, I basically always have glasses and a beard. 

Melanie Avalon: Oh, you did? You kept it.?

Seth Stephens-Davidowitz: Yeah. I keep the beard and keep the glasses based on the market research on myself. And I think people could do-- I took it to the nerdiest as I usually do. I did the nerdiest possible version of this study. But people can do kind of a lazier version of it, where you just download FaceApp or a similar app and create different versions of yourself and at least ask a bunch of people which looks best so you may stumble on a look that you've never even considered that it turns out looks really good on you. Let's say you've never grown your hair long and FaceApp, you can just say, what do I look like with long hair, and you show it to people and they're like, "Wow, that looks amazing." And then, you might consider growing your hair out just based on the data.

Melanie Avalon: When did you do that experiment?

Seth Stephens-Davidowitz: Yeah, it was probably about a year ago and I've definitely had a beard and glasses since. Sometimes, I forget to put on my glasses, and then someone who read my book is like, "Where are your glasses? You lied to us."

Melanie Avalon: So, have you practically-- And this actually relates to a larger question I can ask from it, the smaller question is, have you practically noticed a difference in maintaining this look? And then, the bigger question from that is implementing these changes based on data-- I just feel like we are so in our own head, and we have our own cognitive biases and our own perception of things. How can we actually tell or does it even matter if the things we're doing are affecting what we're doing based on data?

Seth Stephens-Davidowitz: Yeah. It's a complicated question for sure. I don't know, I give a lot of keynote addresses and I always end with the joke that people, "If you think I look really competent, it's because I'm wearing glasses and a beard, and you're all lab rats in my life experiment." But I haven't asked people afterwards or done a controlled experiment to see how competent they view me with and without glasses and my beard. But I think collecting data and actually listening to the data-- and I didn't get to into the quantified self-movement in the book. I was going to go to a conference on it and then COVID hit. I wanted to have a chapter on the quantified self-movement, which is people taking this really, really seriously of measuring their sleep very closely, and their blood, and their cardiovascular health and glucose levels and trying to really understand how their bodies work and make adjustments based on that.

I think there is a danger in that approach is that, as Richard Feynman, the physicist says, "The easiest person to fool is yourself." So, there definitely is danger in doing a study on your own. One of the great things about a doctor is that they're not connected to the participant unnecessarily. And they don't allow doctors to treat their own kids usually because they care too much and they might give a biased analysis based on that. So, that would be a concern I'd have about the quantified self-movement, is it's so easy. Anyone who's done data science knows how easy it is to trick yourself and be biased. And it's that much easier to trick yourself, when you care so much about the results when it's about your own health, your own happiness, your own mood. So, you know that is definitely a big concern.

Melanie Avalon: I wonder if it's more valid to go by how other people perceive you. Rather than polling yourself about how you feel about the changes if you had a poll of, how everybody else sees you from the changes. 

Seth Stephens-Davidowitz: I think that's right. I think that's one of the great things about friendships and relationships is that sometimes they can give you insights into yourself that other people don't give you, although people aren't always so honest and there are some things they don't want to hear. I was talking recently, someone said that there's a difference in a good short-term friend and a good long-term friend. Good short-term friend tells you what you want to hear, and makes you feel good in the moment. But a good long-term friend sometimes tells you uncomfortable truths about yourself that might make you angry. You go home, you say, "Why the hell did Alex just say that?" I'm picking Alex randomly and he's not a real person. Okay, he is a real person, [chuckles] but you're furious. You're like, "Why'd that asshole tell me that? That was so mean. That was--" whatever. But then it's kind of advice gets into you and you make a couple changes and you notice a few years later, like, "Thank God, that person told me that because I was making these huge errors in judgment. Nobody else wanted to tell me these uncomfortable truths."

Melanie Avalon: That's really interesting, especially because I feel for a lot of people, it might require time in a relationship for them to reach a point where they acquire that trait of telling them. Because in the beginning, I think in order to groom a friendship, there's a fear that you will lose a friend if you tell them the truth, especially if it's a new friend. It's something you have to grow into.

Seth Stephens-Davidowitz: Yeah, for sure. Yeah. I'd agree with that. Yeah, I wouldn't recommend your first meeting with a friend or a first date being like, "Oh, you look terrible. That dress looks awful on you."[ chuckles] But a couple years down the road, you could say, "You could dress a little better." When I first wrote my book and I started getting some attention, and I was on podcasts, and I was on YouTube, I religiously read all my YouTube comments. And people are like, "That's the last thing you should do," because people on YouTube are so mean. But I actually found it very useful for the very reason we're discussing, which is at least they're honest, and people were telling me things that I otherwise didn't know. So, they'll say things like, "Your teeth are yellow." Nobody tells you that in real life, because they don't want to be mean. But having gotten that feedback, I got whitening strips. Things like this are so useful, but nobody wants to be the one to tell you.

Melanie Avalon: That's a really good reframe. That's really interesting. Like maybe the way to get these truths about yourself, especially with social media, to let it filter in that way.

Seth Stephens-Davidowitz: Some of it's just useless. It's like people are just mean and they tell you things that aren't really helpful. But occasionally, they'll tell you, "You 'um' too much," or, "You say 'you know' too much, or, "Your teeth are yellow." That's useful information, because it's probably affecting how you're coming across.

Melanie Avalon: Well, going back to something you touched on. You do love sports a lot. I hadn't read the book, but I was familiar. I'd heard an interview. Is it David Epstein, The Sports Gene? 

Seth Stephens-Davidowitz: Yeah. The Sports Gene. 

Melanie Avalon: I heard him on Peter Attia and thought that was really fascinating. Yeah, the big question when it comes to sports, is it mostly genetic?

Seth Stephens-Davidowitz: Yeah. David Epstein has this book on The Sports Gene about how genetic sports are. It's another uncomfortable truth about the world because we like to think that if you're passionate, hardworking, you care enough, you can do anything that's why we like telling kids and David Epstein is like, "No, actually, there are particular genes that make you run fast and make you a good baseball player." There are always things like baseball players have better than 20-20 vision, almost all baseball players, that it's kind of a secret gift. Your kind of like, "Why is that player so much better at hitting than somebody else?" And it turns out, they were just gifted extraordinary eyesight. The data as he talks about the body types that are good for different sports. So, swimmers tend to have really long torsos and short legs like Michael Phelps, very useful for swimming.

It's kind of depressing the book but I realized there's actually differences in different sports and how genetic they are. They actually figured a way to test this, which is basically how many identical twins rise to the top of a sport. Because identical twins of course share 100% of the genetic material. So, if sport is really, really genetic, then there would just be all kinds of tons of pairs of identical twins at the top. Basketball is an example of that, where there've just been so many more identical twins in basketball and other sports. And that's because basketball is based a ton on height, which is one of the most genetic traits there is. So, each inch of height doubles someone's chances of becoming a professional basketball player. So, basketball's just flooded with identical twins.

But then, there are some sports that don't have a lot of identical twins, equestrian riding, diving, alpine skiing, a few sports like that and suggests that genetics play a lesser role. So, those sports may be better bets if you aren't genetically gifted. So, the best equestrian rider in the world may just be someone who is obsessed with horses from a very young age and devotes themselves to the craft. Whereas the best basketball player in the world or the best track and field runner in the world is someone who, yes, devoted a lot of time to the craft, but also had to be given these extraordinary genetic gifts, which are so important in those sports.

Melanie Avalon: How do you determine if the data is actually powered to find the answer? Because presumably-- I don't know how many equestrian riders there are, but I imagine there's a lot less than basketball players. How do you know if you have enough datapoints?

Seth Stephens-Davidowitz: If I wrote as an academic paper, I would have had confidence intervals and more statistical analysis, but writing it as a popular book, I didn't want to bog people down. But you do test to basically say is there a statistically significant difference and there definitely is. It turns out one of the reasons I focused on sports people-- you could do this analysis for other arenas of life as well, but I focused on sports because there have been so many athletes in part because of the Olympics which happens every four years and has tons of athletes from around the world, that the sample sizes get pretty large. Whereas if I tried to study the genetic component to being a billionaire or being president or even being senator, sample sizes would have been too small to really do the analysis. So, another one of the reasons I focused on sports is because I'm obsessed with sports. And another reason is because the sample sizes are big enough to get statistical power.

Melanie Avalon: Sports have never been a thing I wanted to do at all. So, I've always thought-- well, I haven't actually thought about this a lot. But if I were to think about it, I probably would think, "Oh, yeah, it's genetic." Going back to the cognitive biases, I wonder if when you do want to do it, if that's when it seems less genetic because you feel if you just practice enough, you could do it. I wonder what the role of having a passion is for making something seem more genetic or not. Because you wanted to-- did you want to baseball? 

Seth Stephens-Davidowitz: Yeah. I always say I want to baseball, but it would have settled for being a professional basketball player as well. I loved all sports. So, I would have taken pretty much anything but baseball was my biggest love as a kid. And yeah, definitely-- I don't know. I feel like whether you think something is doable, partly maybe it's connected to how passionate you are about it. But I think it's also just connected to personality, and talk about things like fixed mindset and growth mindset. So, some people feel their skill set is set in stone, and if they're not good at something at the age of 10, they're not going to be good at it at all. And other people have more of a growth mindset and think, "I'm not good at this yet. Give me time, and I'll learn to get good at it." And that seems to be a predictor of success in a lot of arenas as well, having a growth mindset.

Melanie Avalon: And is that genetic, having a growth mindset or not?

Seth Stephens-Davidowitz: I think there's a little-- One of the things you learn in genetic research is everything's at least a little genetic. I don't think there's a gene or 10 genes that code in your brain have a growth mindset. But to the extent it's connected to things like happiness and optimism, which are very genetic, it probably does have at least some genetic component.

Melanie Avalon: Well. that goes into another topic, just as far as genetics and the potential for things. The role of parenting, you had some really, really interesting findings. How much of their daily choices about how they raise their kids is affecting how their kids turn out in the end?

Seth Stephens-Davidowitz: Yes. There are all these studies on the effects of parenting and there are different ways to do it. Some studies involve adoption. So, I talk about a famous study of Korean adoptees where the kids were essentially randomly assigned to households. And we could really measure, okay, two kids who are randomly assigned to the same household end up similar or not. Or two biological kids who were raised in different households end up similar. And there are also studies of twins, as I mentioned, which allow using some math to disentangle nature versus nurture. I think the major finding from studies on nature versus nurture-- there are a couple of big findings in nature versus nurture, and parenting. One is that nature matters a lot. So, genetics, just really, really important for just about any outcome you could think of to measure happiness, political views, religiosity, income, education. Nature, really, really important, identical twins who are raised apart, they meet for the first time at the age of 30 and they have all these shocking things in common. Nature really matters.

The other thing is that the overall effect of the environment is pretty small. It's not zero, but it's not that much. So, a lot of parents think, "If I raised my kids right, they're going to for sure be happy." Or, "If I could raise my kids right, they're going to be a brain surgeon, or they're going to be the next Bill Gates." That's clearly not true, and that there's just not that much-- you can't move the dial that much as a parent. That said, there is some evidence that maybe one parenting decision that people make maybe the most important by a pretty wide margin and that's where they raise their kids. There's this data from tax records where they've studied kids from the same families who kind of control for genetics, who are raised in different areas. So, maybe there was a 10-year age gap and one of the kids had their formative years in Los Angeles and another of the kids had their formative years in Seattle. And it turns out when you look at the data, there are big differences. Certain cities, certain metropolitan areas, certain even blocks within a neighborhood, kids who were raised their turned out to do much better. So, why is that? What is it about an area that leads to successful kids? Many of the predictors of a good neighborhood were surprising to me. They're things like the number of two-parent households in that neighborhood, percent of people who returned their census forms, percent of college graduates in that neighborhood, it seemed to have a lot to do with the adults in that neighborhood. Basically, the adults being good people, good role models, kids kind of modeled themselves after the people they're exposed to. And if you expose your kids to people who are pretty good at life, you're more likely to have good outcomes.

I think parents maybe overestimate the effects they're going to have on their kids and underestimate the effects that other people they're exposing their kids to will have on them, in part because kids rebel against their parents. So, kids may think their parents are the coolest people in the world for one period. And then later on, they think their parents are the biggest losers in the world. But the other people, they see, they're more likely to think, "Yeah, that person's cool. I want to be like them." So, I kind of recommend parents outsource the parenting process a little bit. Expose your kids to people you want them to turn out to be like.

Melanie Avalon: What's interesting about it is that factor of environment is literally-- because we're often talking about genetics versus epigenetics, and epigenetics is a whole thing about environmental influences. So literally, this one choice, decision is in a way environment, then it makes it even more broad and all encompassing. Maybe we're saying it's just the neighborhood, but it's not really just a neighborhood, because that would automatically inform so many other things. Which makes me wonder, I thought about this a lot when I was reading the parenting book, and I think about it in similar situations in my life. Because you talk about how parents stress so much about all of these decisions that they have to make for their kids but really, it doesn't have that much of an influence in the end. My question is, does the collective whole though of all decisions have an impact? So, maybe this one decision that you make raising your kid doesn't have a huge impact on its own but if you're applying that mindset of trying to make the best decision for every decision, then does that have an impact?

Melanie Avalon: Yeah. I think the evidence from the adoptees suggests it doesn't have a huge impact, because presumably some of the parents were much more hands on and reading every parenting book and doing research on every topic and trying to get every decision right. And some of the parents were more freewheeling and maybe they read Dr. Spock's book, which suggests, "Just follow your intuition. Don't worry so much. You don't need to get every decision right." And it seems the evidence suggests that adoptees exposed to very different adoptive parents just don't make that much of a difference. So, I think, it's not that parents make no difference. And some parents may say, "Well, I don't care. Yeah, sure, even if I'm a great parent, I can only raise my kid's income by 30%," or, "I can only decrease the risk of depression by 5%, but that's still enough for me to want to do it because it's the number one thing I care, about how my kids turned out. So, even if it has a smaller effect than I might have guessed, I still want to do everything in my power to help my kids."

One kind of complication with the whole doing everything in your power to help your kids is because genetics are so important, if you really weren't doing everything in your power to help your kids, you'd probably get sperm and egg donors. Because think about it, you're unlikely to be the happiest person on the planet or have the happiest genetics on the planet, or the most intelligent genetics on the planet, or the best-looking genetics on the planet. So realistically, the best thing you probably could do would be that but I think the fact that so many parents don't do that shows that parenting is not all about maximizing your kid's outcome at the expense of everything else. Part of what we're doing is sharing who we are with our kids and sharing our particular values and connecting with them and loving them, no matter how they turn out. I think just about any parent, when they think about it, would have to admit that they're not just maximizing their child's happiness, success, or wealth. They're also doing other things and I think that's okay.

Melanie Avalon: I guess we'll see how that goes, especially the future of gene editing, which would be kind of that-- I don't want to say a happy medium, but it would be still the parents but then making genetic changes.

Seth Stephens-Davidowitz: Yeah. Some people say once it starts, there's just going to be no stopping it even at both the country level and the individual level. Let's say United States says, "We're not going to approve gene editing," but then Singapore says, we're going to approve it," is United States going to just sit back while Singapore has all these super babies? And then at the individual level, you might say, "Well, I don't believe in gene editing," but then all your friends are editing their babies and having these designer babies that are great looking and really, really smart and happy, are you going to just say, "Well, I'm not going to give my kids those same gifts"? I don't know. I kind of agree that there's something to the idea that once it starts, there's just no stopping it. 

Melanie Avalon: Happiness, is that genetic? 

Seth Stephens-Davidowitz: Yeah. There definitely is a huge genetic component to happiness and mental health problems, depression, neuroticism, anxiety. It's not as genetic as height or IQ. But it does have a big genetic component.

Melanie Avalon: I loved the chapter you had on-- was it called the Mappiness Project.

Seth Stephens-Davidowitz: Yeah. The Mappiness Project. Yeah. 

Melanie Avalon:  Yeah. So, can you tell listeners a little bit about that project and what they found?

Seth Stephens-Davidowitz: Yeah. I didn't know about the Mappiness project before I started researching this book. It was co-founded by two British economists, George MacKerron and Susana Mourato. They ping people at different times of the day and they ask them some basic questions, who are you with? What are you doing and how happy are you, zero to one hundred.? So, you could imagine, if you were participating this project right now, you probably say, "I'm by myself, and I'm listening to a podcast, and I'm a hundred happiness, because this is so fascinating," or I hope--

Melanie Avalon: --that it is. [laughs]

Seth Stephens-Davidowitz: But then later in the day, you'd say, "With my romantic partner, and we're eating dinner, and 60 out of 100." And you keep on doing this 60,000 people did this multiple times to the point that it had 3 million happiness points. And they can answer all these really interesting questions that obviously everybody cares about, like what activities make people happy, what people make people happy. They can even do things because it was done with iPhones, even if they didn't ask people, where are you? They knew people's GPS. So, they could answer questions like, are there certain environments that make us happy? They didn't ask people what's the weather outside, but they knew what time it was and where people were. So, they could say what kind of weather makes people happy. So, in my opinion, it was a revolutionary project that taught us all kinds of things about happiness.

Now, one of the main things that it taught us, is the things that make people happy, are pretty freakin' obvious. Being with a romantic partner, nice days, being in nature, particularly near water, certain activities, socializing, having sex. Not rocket science. But I think there's profundity in the obviousness of the data because so many of us do these things that don't make us happy, and we don't do these obvious things that do make us happy. So, I thought it's really important to keep in mind how simple some of the things that reliably give people happiness are.

Melanie Avalon: Yeah. I've been asking-- probably the reason I have this show is just because I love learning things and sharing them with people. I've asked so many people the question of what do they think are the top two things that make people happy? One was sex, and then two was going to a show, which made me happy because that's my favorite thing. So, that was fantastic. [laughs] 

Seth Stephens-Davidowitz: People are all over the place. You think these things are obvious. Oh, yes, sex would give the most pleasure, I guess. But I do the same thing when I give a talk, I say what's the number one activity and people say relaxing, eating. Some people say watching TV, lying on the couch. And those activities tend to be actually below average scoring activities. Very rarely does somebody say gardening, which is one of the top activities, or go even going to a show doesn't usually score that high. I think people might not say sex because they're feeling sheepish.

But there're some systematic biases that we have. I did a study motivated by Mappiness Project with my friend, Spencer Greenberg. We asked people kind of what you said you did with your friends, but more systematic. We just asked people to rank these 40 activities on how happy they make people and people. There was a correlation. People kind of got that sex would score higher than doing chores or that socializing with friends would score higher than waiting on a line. And they're right about that but there were definitely some activities that people really thought made people happy that don't make people happy are conversely some activities that people thought don't make people happy that do make feel really happy. One of the biases seems to be that people think that lazy activities make people happy and they really don't. Lying on your couch, watching Netflix, playing computer games, relaxing, all these things, people seem to think that they give people a lot of happiness. When you actually ask people right in the moment, "How happy are you?", people are doing these things tend to say they're pretty unhappy. 

Melanie Avalon: Well, first for the sleep one, I was thinking that if people are answering that, then it's when they're not asleep. 

Seth Stephens-Davidowitz: There are some imperfections in the project, I would say. They do give people time to respond. So, if you get beeped, you can say up to 60 minutes later how were you feeling when you were beeped and what were you doing. So, that could explain some of the sleep on. I think even so, do people know how happy they are when they're not fully conscious? I think there were some issues, it wasn't a perfectly designed study, in part because there's no such thing as a perfectly designed study, and a lot of activities were grouped together that I thought maybe shouldn't be grouped together. 

Melanie Avalon: Like shopping and errands. Two completely different things. [chuckles]

Seth Stephens-Davidowitz: Traveling and commuting.

Melanie Avalon: Oh, those are way different. Yeah.

Seth Stephens-Davidowitz: Yeah. There's a difference being on the subway at 8 AM and being in the Caribbean, with your friends by the beach or something. So, it wasn't a perfect study but don't let perfect be the enemy of the good. It's still taught us I think more than we've ever known about happiness. And I'm sure there have been-- I've talked about other projects that have been motivated by my Mappiness. And so, I think more and more people are creating these apps. And I think within 10 years, we're going to know way more about what really makes people happy.

Melanie Avalon: I really thought the findings on alcohol and happiness were interesting. What were some of them?

Seth Stephens-Davidowitz: Yeah. That was a study from MacKerron and Geiger, and they studied the effects of drinking. They found that maybe not surprisingly, drinking does give a boost in mood. But the interesting thing was it only gives a boost in mood for certain activities and they tend to be the activities that people don't tend to use alcohol for. So, drinking gives a boost in mood when you're doing chores. So, you're doing the dishes, you're going to be much happier if you're doing the dishes and have a glass of wine, or you're in the shower. But booze doesn't give a big mood boost when you're doing something exciting. Having sex, socializing, being out with friends more generally, then you don't really get a mood boost. And of course, that's exactly how most people use alcohol. It's like, "I'm having so much fun with my friends out at the club. I'm going to drink to make this an even more epic night." And the data suggests that it basically doesn't work, that you're going to have fun with your friends with or without alcohol. But obviously, a huge danger giving this advice, because a lot of people do have problems with alcoholism and I don't want to encourage people who shouldn't be utilizing this strategy. But I tend not to have-- neither myself nor my family have problems with alcoholism, I have occasionally found myself having a glass of wine when I'm doing the dishes based on the this mappiness study. 

Melanie Avalon: It's so funny. Yeah, I've been sharing that with a lot of people. And I found it interesting-- I don't know if it was that study, one of them was talking about next day happiness effect from alcohol. It was counterintuitive.

Seth Stephens-Davidowitz: Yeah. It actually didn't have a big effect. So, I would have thought, yeah, you're really happy when you drink, but the next day, you pay for it and you feel horrible. And they found that that's not actually the truth, that actually, you go back to pretty much where you would have been on average. Certainly sometimes, we've all had a horrible hangover. It maybe also be a limitation of the study that if you have eight drinks, you're too drunk to answer the Mappiness survey. [laughs] There are all kinds of limitations with this methodology. But on balance-- I took from this study that with a huge caveat, huge, huge, huge caveat, that alcohol can be dangerous to people with an addictive personality. There definitely is a role for alcohol and perhaps other substances as well in boosting your mood. But we probably use it wrong. Trying to getting drunk on Saturday night with our friends, maybe isn't actually a great mood booster. 

Melanie Avalon: Like I love wine and I have every night with glass of wine. And out of curiosity, I went a year without any wine, because I just felt like-- I'm a very happy person. That's another question about stats on happiness. They say-- They say, I don't even know who 'they' is. [laughs] But they say you're happier without the substances. So, I was like, "Okay, I won't drink for a year and see if I'm happier." And at the end, I was like, "I feel happier with my wine." 

Seth Stephens-Davidowitz: With wine, yeah. The usual parental advice is always stay away from substances. And my parents have told, I think, all three of their kids, me, my sister, and my brother, that we could use substances a little more, because a lot of times we go out to dinner, and we're the teetotallers. My parents are like, "No, you can have a glass of wine."

Melanie Avalon: All the siblings are?

Seth Stephens-Davidowitz: Yeah. We were like, "Yeah, definitely." my sister, in particular, she almost never has a glass of wine. My parents are always like, "Come on, have a drink. Lighten up, relax." I think the data says that's not crazy. But of course, there's this huge caveat that whatever percent of the population, I don't know, off the top of my head does have a tendency towards alcoholism and they have a glass of wine and they soon have a whole bottle of vodka.

Melanie Avalon: Just looking at the supercentenarian studies and the long-lived cultures, they all, except for the Seventh Day Adventists, include alcohol, which I find interesting.

Seth Stephens-Davidowitz: Although there's a recent study that the supercentenarians are largely due to clerical errors. They've done studies that when birth certificates became more official, then the rates of centenarians and supercentenarians just dropped precipitously. 

Melanie Avalon: I saw some stuff about that. 

Seth Stephens-Davidowitz: Yeah. Even some of the areas that supposedly produced a lot of people who lived a very long time were areas that just had really bad recordkeeping. So, I think we're going to have to reevaluate some of the analysis of what leads to long life. But I have read some of the same things you've read, the importance of social connection. I think it remains to be seen which of these findings survive better recordkeeping.

Melanie Avalon: One last topic we could touch on. I'm curious. Your job, success in business, what you're doing, is that something that normally leads to business success?

Seth Stephens-Davidowitz: Yeah. In some ways, it is. Well, one of the-- I talk about the data from tax records. Basically, studies last three or four years. They've analyzed, deidentified tax records of the entire top 1%, top 0.1%. And they're really telling us what it takes to get rich. There's a sentence in one of the major studies that the typical rich American is the owner of a regional business such as an auto dealership or beverage distribution company, that really surprised me. I hadn't really thought of-- I guess if I thought about auto dealers, sometimes we associate with great wealth. Beverage distribution companies, I knew basically nothing about. It's all these basically local monopolies. Basically, you want to own a business that allows for a local monopoly. I recently celebrated my 40th birthday, and my dad gave a speech.

Melanie Avalon: Oh, happy late birthday.

Seth Stephens-Davidowitz: Thanks. My dad gave a speech where he just roasted me for exactly what you're saying. He's like, "You don't do any of the things you suggest in your book." [chuckles] He started with saying, "Seth says that the path to wealth is owning an auto dealership. Seth doesn't own an auto dealership. The path to happiness is not watching sports, and Seth watches more sports than anybody I know." He just went through all the things and explained how I'm not living my advice. But I do think that being an independent creator, which I currently am, actually is not a crazy path to making a lot of money because you can have a local monopoly through your brand. So, if you build a lot of fans, you can make a good living. You do have to get lucky, which is why I have a whole chapter on how to get luckier according to the data. A lot of people want to be a successful author, successful podcaster. But I think in many ways, it's a better path than being an employee, which the data says you're very unlikely to make a lot of money as an employee, because the owner of the business kind of is going to take just such a big share of any profit that you produce.

I guess I'm following my advice in that I'm not currently an employee. And I have made-- this catches me by surprise but I was a data scientist at Google. And I've actually probably made two to three times more as an independent creator on average than I was as a data scientist at Google. Because as an independent creator, I do get to keep more of my product than you do as an employee for even a great company like Google.

Melanie Avalon: Why did you leave Google? You shared that story.

Seth Stephens-Davidowitz: I signed this book contract, and I just wanted to focus more on my writing so. The book contract was paying me more than my Google salary at that time. So, I just wanted to give it a shot. I was pretty young. When I did that, I was about 30 and I'm like, "This is my one shot to do something I'm really passionate about and really love."

Melanie Avalon: Oh, that's amazing. Wow. You said something about Google picking a shade of blue.

Seth Stephens-Davidowitz: Oh, that has nothing to do with me. A designer quit the company at Google because, to decide what blue to show their users on their links, they did all these random experiments on 40 different shades of blue. And the designer was so furious, he's like, "This is not art. This is commerce. I'm quitting my job."

Melanie Avalon: Okay. That's so funny. Well, it was motivating speaking to that concept, because I think for a lot of people, especially if they are in a typical 9 to 5 job or a salary job, and I'm not saying-- and you talk about this, there are people who obviously do make a lot of money in those avenues, but there seems to be a lot of potential for even more being self-employed.

Seth Stephens-Davidowitz: Yeah. But you've got to hustle your ass off.

Melanie Avalon: No kidding. It was interesting to me to read because going back to the fan thing, I was like, "Oh, this is kind of exactly what I am doing. So, maybe that's why it's working." [laughs] Like cultivating your own brand so you're not imposed on by other conflicts and competition, things like that. But it was very motivating because you're saying how in the media, with self-starters and entrepreneurs, the media makes it seem like it's people really young that are doing this. But really, it's older and you have a long time to potentially still make it.

Seth Stephens-Davidowitz: Yeah. There are these studies on successful entrepreneurs and the average age of a successful entrepreneur is about 45. Even in tech, which everyone thinks that you have to be really, really young to be a successful tech entrepreneur and it's just not true. Yeah, I think a lot of people find that encouraging that a 60-year-old entrepreneur has three times higher success rate than a 30-year-old entrepreneur. Most people don't think of a 60-year-old entrepreneur. So, I think that is in part--

Melanie Avalon: Somebody starting at 60 or somebody who--

Seth Stephens-Davidowitz: Yes. Someone starting a business at 60. Yeah. 

Melanie Avalon: Wow. That is really motivating. 

Seth Stephens-Davidowitz: Yeah. That's motivating for just about everybody. I guess except for people in their 80s.

Melanie Avalon: Do you know if there's a sex there? Is that just men?

Seth Stephens-Davidowitz: They didn't break it down by gender. Yeah, that'd be interesting.

Melanie Avalon: Well. Unifying question that kind of brings everything together is applying this data personally-- for me when I read the happiness chapter, and it was saying that people are happy in warm weather and not cold, I love cold, and I don't like warm. There's some things-- that's just a very specific example but there are some things where it's just not me, for example. So, in those situations, if the data just literally doesn't apply, it's just like not what I like, does it still apply a little? Or do you have to throw out stuff that just, for whatever reason, doesn't apply to you?

Seth Stephens-Davidowitz: Definitely, there's individual variation in everything including what makes us happy. I think as more of these projects like Mappiness are created, maybe the next level is to explore more of the individual variation. That said, I think there is a danger in thinking that you're so unique. One of my favorite studies is they've compared self-described introverts and extroverts, the mood boost they get from being around other people. And the mood boost is exactly the same. Introverts get just as big a mood boost as extroverts do. Even though if you asked introverts, they say that they predict they would get a lower mood boost, because they think they like solitude, they crave solitude. So, that shows that there can be some danger in thinking, "Yeah, well, everybody else likes gardening, but I like watching Netflix," or, "Everybody else likes hanging out with their friends, but I like being by myself," or even, "Everybody else likes 80 degrees and sunny, but I like seasons."

I'm not saying you're wrong. I'm sure there are some people who do like more of the cold, do like seasons, but we do have to be careful, I think, thinking we're unique in these arenas. I think anybody will at least try the things that make the average person happy, give them more of a shot, even if we think they wouldn't work for us.

Melanie Avalon: That was a really fascinating thing that you talked about, about the memory of happiness and how it might actually be having an effect on drug trials with medications because people don't accurately remember.

Seth Stephens-Davidowitz: Exactly. Anytime we're trying to make sense of our happiness, we have to keep in mind that we have terrible memories when it comes to what made us happy. I talk about these studies of colonoscopies where they asked people-- during the colonoscopy, they say how much pain they're in, and then after the fact, they say, how much pain were you in, and there's almost no correlation between how much pain they were actually in and how much pain they remember being in. I think, all of us, yes, that's another reason to kind of distrust our own intuition around what makes us happy that we have these faulty memories. I'm not picking on you for the weather thing. I suspect you do have a different reaction to the weather than maybe the average person, but maybe you remember some glorious winter days and you forget glorious summer days. I'm not saying that's true but we do have to be careful in trying to recognize patterns between our activities, our environment, and our happiness, we do have to keep in mind we can very easily miss remember our prior moods.

Melanie Avalon: I cannot agree more. The one thing I always say is that the only thing I know is that I know nothing. I always mention this on the show, but ever since I read the split-brain patient studies where they would show people who had some sort of disconnection between the hemispheres of their brain, show them things that only one part of their brain saw, and then ask them why they did things that they did, and the language part of the brain would just make up stories about it. I was like, "Okay, I know nothing, literally."

Well, thank you so much. This has been absolutely incredible. The last question that I asked every single guest on this show, and it's just because I realized more and more each day how important mindset is, and it actually relates to something that was found in the happiness data about the present moment, what is something that you're grateful for?

Seth Stephens-Davidowitz: It's hard to pick one because I'm grateful for so many things. But certainly, my family. Even though I claim that in the book that parents don't matter that much, I definitely feel gratitude towards the parents I have and the siblings I have, and the cousins I have. I have a very warm, loving, nurturing, supportive, nonjudgmental family and I feel very, very lucky because a lot of people do not have that.

Melanie Avalon: I love that so much. Literally, when I read your acknowledgments-- because I remember when I wrote my acknowledgments for my book, it was a very similar vibe. I feel like you and I are grateful for very similar things in that regard. Well, thank you so much. I, like I said, so thoroughly enjoyed your work. I've been just telling everybody about it. Do you have another book coming out?

Seth Stephens-Davidowitz: Not in the near future, but I probably will write another book at some point.

Melanie Avalon: Well, I will eagerly look forward to it. How can people best follow your work?

Seth Stephens-Davidowitz: I'm on Twitter, @SethS_D. That might be the best way. 

Melanie Avalon: Okay. Awesome. Well, I'll put links to everything in the show notes. Thank you again so much and enjoy the rest of your day. 

Seth Stephens-Davidowitz: Thanks, Melanie. 

Melanie Avalon: Thanks, Seth. Bye.

[Transcript provided by SpeechDocs Podcast Transcription]

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