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How Much Does Google Know About Me? | Seth Stephens-Davidowitz | Modern Wisdom 134

Seth Stephens-Davidowitz is a former Data Scientist at Google and a writer. There are things which you write into Google which you have never told another person. Our search history is a window into the deepest recesses of our mind which has never before been available. Time for the big data analysts like Seth to step in and look at what we can discover from these information. Why do people commit suicide? How many Americans are racist? What is the most popular type of pornography in India? And what is the biggest determining factor in a child's development? Extra Stuff: Buy Everybody Lies - https://amzn.to/2QZqHH0 Follow Stephen on Twitter - https://twitter.com/SethS_D Take a break from alcohol and upgrade your life - https://6monthssober.com/podcast Check out everything I recommend from books to products - https://www.amazon.co.uk/shop/modernwisdom #bigdata #google #datascience - Listen to all episodes online. Search "Modern Wisdom" on any Podcast App or click here: iTunes: https://apple.co/2MNqIgw Spotify: https://spoti.fi/2LSimPn Stitcher: https://www.stitcher.com/podcast/modern-wisdom - Get in touch in the comments below or head to... Instagram: https://www.instagram.com/chriswillx Twitter: https://www.twitter.com/chriswillx Email: modernwisdompodcast@gmail.com

Seth Stephens-DavidowitzguestChris Williamsonhost
Jan 16, 20201h 2mWatch on YouTube ↗

EVERY SPOKEN WORD

  1. 0:0015:00

    There are lots of…

    1. SS

      There are lots of people in this area and, you know, data science is just exploding in all kinds of ways and I think a lot of people are go- definitely millennials or people younger than millennials are also looking ... You know, it seems like the values are shifting a little bit where it's less about just making money. So I think initially everyone's kind of like, "Oh, data science, that's a lucrative field. I can get a job at-"

    2. NA

      Mm-hmm.

    3. SS

      ... you know, getting people to click on ads or, uh, work, get a job in finance." Which, which is tot- are totally fine jobs. They're kind of bored of studying. You know, they- they- they like data science but they're kind of bored of s- of getting people to click on ads and they're, you know, they, they feel kind of unfulfilled and lacking purpose and I think there are ways to use this data, uh, towards social good as well.

    4. CW

      (wind blows) Seth. Hi, man. How are you doing?

    5. SS

      Really good. How are you?

    6. CW

      Yeah. Very good, thank you. I'm excited for today. Big data and all this sort of stuff. It's going to be cool.

    7. SS

      Yeah. I hope so.

    8. CW

      Looking forward to it. So first things first, how do you describe what you do for work or on a day-to-day basis?

    9. SS

      Uh, well, so I guess I'm, I guess I'm a data scientist and an- and an author, writer. So, uh, you know, I, I spend most of my time on books. I wrote Everybody Lies. I'm trying to write ... I'm in the process of writing another book. And, uh, other than that, I don't know. A lot of random projects. I do random consulting for companies and, uh, there's not necessarily a standard day, but-

    10. CW

      I got you. Is it a lot of time on spreadsheets or similar sort of applications?

    11. SS

      Yeah. Uh, R, the coding language. There's a lot of time on that, kind of moving back and forth between R and, uh, Google Docs, uh, 'cause I guess the combination of data science, which is R, and writing, which is Google Docs.

    12. CW

      Got you.

    13. SS

      Uh, and then sometimes just researching. A- a lot of, like, reading, so a lot of reading other people's studies. Kind of reading what, uh, other people are talking about since I can't just, uh, write about my own studies.

    14. CW

      Which is a shame.

    15. SS

      Yeah. (laughs)

    16. CW

      Yeah. It'd be lovely. Um, so you wrote a book called Everybody Lies, New York Times bestseller. But I heard that you wanted to call it How Big Is My Penis? Is that right?

    17. SS

      (laughs) Tha- tha- that- that is, that is correct, yeah. I-

    18. CW

      You wanted to call your book How Big Is Your Penis?

    19. SS

      No, How Big Is My Penis? Um-

    20. CW

      How Big Is My Penis? N- yes.

    21. SS

      Well, no. Basically the reason for it is that that's one of the top ... Well, I, I talk about how men ask more, Google more questions about their penis than any other body part. (laughs) And that one of the top questions they ask Google about their penis is, "How big is my penis?" Which is just, like, an absurd question to ask Google.

    22. CW

      (laughs)

    23. SS

      Right? They're not going to be able to answer that. So I ki- I kind of thought that that title would kind of get the flavor of what some of the, some of the things I was talking about, uh, that kind of ... But I think one of the things that my research has shown is the absurdity of the human condition, the absurdity of people. We kind of, people kind of put on a very presentable front, but in the privacy of their own home on their s- Google search engine or the websites they visit and they go to Pornhub they kind of just show, uh, a different side of themselves which is a little bit stupider, a little bit less polished, a little bit weirder, a little bit sometimes nastier. Uh, but I think, uh, it's kind, it's kind of, um, an interesting view of people that we haven't really previously had.

    24. CW

      Mm. Yeah, that totally unfettered view where you, you don't think that anyone else is watching, but the data analysts are watching. You are.

    25. SS

      Well, th- the data I analyze is all a- anonymous and aggregate, so I don't know that any particular man searched how big is my penis. I just know that lots of men apparently-

    26. CW

      (laughs)

    27. SS

      ... uh ...

    28. NA

      (laughs)

    29. CW

      You know what I think? I think there is an opening in the market for an app which can use AR, like augmented reality. You hold it up to your face, you angle the penis, and then it, it works out how big it is.

    30. SS

      Well, how would ... You'd have to know how big the face is. Right? You'd need, like, something behind. You'd need to be, like, standing in front of the Eiffel Tower or something. Something-

  2. 15:0030:00

    Got you. So what…

    1. SS

      uh, ride, so I don't know.

    2. CW

      Got you. So what else, what else have we learned from porn? Let's stay with porn for a second before we get away from porn. Were there any other s- surprising things that came up other than

    3. NA

      You know?

    4. SS

      There's some of them... Some of them, I think, when I ca-... When the book came out, people said they were really shocking. To me, I didn't find it shocking. So for example, the popularity of rape porn among women is very, very striking in data. A huge percent of heterosexual porn searches or vide- videos watched by women are for kind of violent humiliation, uh, against a woman.

    5. CW

      Mm-hmm.

    6. SS

      And much more popular among women than men. About twice as popular among women than men. Uh, that, that didn't shock me. There have been surveys that kind of have talked about that a lot of women have these types of fantasies. And kind of just in my conversations with friends, I have very honest friends, this is kind of... You know, it's kinda come up in my life that-

    7. CW

      Mm-hmm.

    8. SS

      ... that it, that it didn't... When I, when I saw the data, I'm not like, "Oh, my God. That shocked-"

    9. CW

      Mm-hmm.

    10. SS

      But I kind of looked at it and...

    11. CW

      I mean, loo- look at, look at the most popular book of the last decade.

    12. SS

      Yeah. 50 Sh- Right, yeah. Yeah, so-

    13. CW

      50 Shades of Grey.

    14. SS

      So... Right. But, you know, it still is, it still did have... I think what was more interesting is you actually can compare the percentages around the world, and it's not correlated at all with how women are treated. That's kind of interesting. That's not... It's not like also-

    15. CW

      How, how so? What do you mean?

    16. SS

      In other words, so you have, like, some areas like Berkeley, California or, like, parts of, you know, or parts of, uh, you know, or you have Sweden or Finland or Netherlands, which Finland now has a female prime, prime minister and, like, there, where there is really much progressive attitudes towards women. Then you have areas like, you know, Saudi Arabia or Iran where women are really held back. And it's not like... So you could really rank kind of, you know, how, how women are treated. Are they re-... Are they treated like second-class citizens?

    17. CW

      How egalitarian it is.

    18. SS

      Yeah. And you, you might... You, you could imagine that that could affect how women think about themselves and kind of, you know, affect their fantasies, but it doesn't seem to... You know, it's kind of a pretty universal-

    19. CW

      It's this universal-

    20. SS

      Yeah. Or-

    21. CW

      ... desire to watch some, like, hardcore porn.

    22. SS

      Even if, even if women are growing up telling, you know, saying they could be everything, they're, they're equal to men, they're, you know, there, there still is, uh, that fantasy seems to exist in about the same number as the places where women are saying, like, "Men should dominate you. Men are the, you know, the, the lead- should be the leaders of society." So that was pretty interesting.

    23. CW

      That is, that is really, really fascinating. Do you ever ask the why question? Do you ever bother to delve into that, or do you just sort of stick to the, to the data?

    24. SS

      So I try to in the next, in the next level. You know, I think there are... Uh, you know, it's, it's... I think the initial thing... Initially, I was kind of just presenting the facts. And I have, I have made much progress. I, I, I thought other people would come up with theories. So I thought when I wrote the breastfeeding one, people are gonna like... Maybe there's some explanation that's very obvious that, you know, I didn't know that... But nothing's come up, uh, you know, to kind of explain this. So I, I don't know. It's, it's, it's tough. Uh, I think... You know, I think there are definitely some areas. So definitely I think people are more attracted to people they grew up around, uh, or like, people like them, I think p- probably maybe more... Maybe because of their environment. So there's kind of there's been this long idea that opposites attract. Uh, and I think if you see in dating data, it's not true at all. So in dating data, it's very, very clear that people are drawn to people who are similar to themselves on just about any dimension you could measure.... and pornography data, it also seems to be the case. So if you look at areas that have high African American populations, uh, they tend to watch porn featuring African American ... Well, there's some men in that area, those areas tend to, uh, watch porn featuring African American women in large numbers. Uh, so it's not like, you know, uh, yeah, I think you could imagine that it would go the opposite way and that the fantasy of the Black man would be, you know, the, the white cheerleader or something. I don't know, that you could imag- uh, but it, it's definitely not the case. Uh, so that, that, that kind of, I think, also moves towards the why direction that maybe sexual ... I, I do think that one of the things you see is that, uh, sexual fantasies seems to be related to childhood in various ways. Uh, so people, uh, tend to have fantasies from their childhood. They fantasize about, uh, babysitters or, like, teachers or I think there's kind of a, there's kind of a maybe kind of key moment in childhood where people kind of get imprinted sexually that also, uh, dovetails with some other research in, uh, in fields of sexuality, uh, that childhood imprinting is really important in developing, uh, adult sexuality.

    25. CW

      Mm-hmm.

    26. SS

      So that would explain why if, if, you know, a, a Black man had grown up around a lot of Black women, uh, he'd probably be more likely to be attracted to Black women, uh, than a, than one who hadn't been grown up. Yeah.

    27. CW

      Yeah. I get that.

    28. SS

      Yeah.

    29. CW

      What about, um, when we're talking about the split between heterosexual and homosexual, there must be some interesting insights there about how many men and women are being truthful about their sexuality?

    30. SS

      Yeah. So one of the things that, that's also striking today, which also didn't surprise me just 'cause it had come up in conversations I've had with very honest friends is the popularity of lesbian porn among women who otherwise consider themselves totally straight. And I think, you know, I, like, uh, I don't think that they're necessarily in the closet. Uh, so, like, I think about 20 ... I think it was ... I, I don't remember these exact numbers. I think it's something like 20% to 25% of pornography, uh, views from women are for lesbian, explicitly lesbian porn. And I think, you know, uh, this will come up in surveys or focus groups, a lot of women, you know, that they live in Berkeley or San Francisco or areas where it's totally, uh, you know, or l- or lo- where, where, you know, in this day and age, I think it's pretty okay, uh, to be lesbian. I don't think there are many social pressures to be heterosexual. And they consider themselves straight. They only want to pursue relationships with men, but they're just like, "You know, the female body's hotter." Like, it's just they, they can, I think, disconnect kind of the real emotional... Women are maybe sometimes ... I don't want to over-generalize, but women are maybe better at disconnecting, uh, the kind of emotional, romantic connection to just like-

  3. 30:0045:00

    Yeah. I, I, I'll…

    1. CW

      statistics, and then you can measure them before and look at what happens afterwards? Have you got some plans for this year with that?

    2. SS

      Yeah. I, I, I'll play around. I play a- I play around every election. There are definitely insights in the internet. You know, I, I think Nate Silver of FiveThirtyEight does a really good job of making predictions based on kind of, uh, all the data, so it can be hard to, you know, tough to, to beat his predictions.

    3. CW

      Mm-hmm.

    4. SS

      Uh, you know, he put, he put so much thought and care into building-

    5. CW

      Didn't he ... Di- did you retweet something of his about ... Was it the Democratic nominees? Was that, like, this week?

    6. SS

      Oh, yeah, yeah, yeah, right. Yeah, yeah, yeah.... yeah, the iD- id. Well, he kind of, th- he just built a model of the Democratic nominee and I just thought that this wasn't based on data. This was actually just based on m- my intuition that he's maybe underestimating Michael Bloomberg's chances just because, uh, you know, he's... His whole, uh, kind of in the past models, the past elections where he's building, uh, the models from, there's never been a candidate who's willing to just spend (laughs) billions of dollars to try to get elected. So I think we don't really know how that's going to play out and that kind of, you know, m- makes me say he shouldn't... You know, I think in his model Bloomberg's at 1% or, or so- something like that. Uh, and I, I kind of think, you know, maybe 5% to 10% just because, uh, the amount of resources he's going to throw at this problem-

    7. CW

      Got you.

    8. SS

      ... uh, couldn't be-

    9. CW

      What's the... So have you looked at much data? I don't know whether you can predict this far out, um, but have you looked at much data for moving forward into 2020?

    10. SS

      I think it's ti- I think th- this time out, this, this far, this time out, th- th- this far out, it's tough. Uh, you need, you need to look closer. Uh, you know, I think so many people just aren't really thinking about their election or, you know, a lot of it, a lot of the general election will come down to who's going to actually turn out to vote.

    11. CW

      Mm-hmm.

    12. SS

      And that, I think we're going to need to wait, you know, a few weeks before the election where we'll really get clues, uh, on who's actually going to turn out to vote.

    13. CW

      You hear the, the story that, um, people decide as they cross the threshold into the voting booth, right? Like, it's like the decision that they actually feel like they make is that, but it must be so interesting to, to compare because you have exit polls that don't... You know, in the last election that you guys had, the exit polls didn't marry up tremendously well with what actually happened. But were you... Did you have be- more of an insight about what was going to go on or retrospectively would you have had-

    14. SS

      Well, I, I, I said Tr- I said Trump was going to win, but I don't know if that's because I'm a genius or a pessimist, because I'm just always predicting-

    15. CW

      All right. Uh, let's go, let's go with genius. Let's go with genius.

    16. SS

      Okay. (laughs) Yeah.

    17. CW

      Let's go with genius.

    18. SS

      I'm always predicting horrible things are going to happen, but-

    19. CW

      Yeah.

    20. SS

      ... uh, there, there are some clues. So one of the interesting things that correlates with voting outcome is the order you put candidates in searches. So a lot of people, they search Trump Clinton polls or Clinton Trump polls-

    21. CW

      Mm-hmm.

    22. SS

      ... or Trump Clinton debate, Clinton Trump election. You can see if you actually look historically the order, if people put Trump Clinton first, they're much more likely to go Trump. If they put Clinton Trump fir- Clinton Trump, Clinton first, they're more likely to go Clinton. And that's kind of interesting because it might almost be subconscious. And you could imagine someone, like they've been searching Trump Clinton election, Trump Clinton polls, Trump Clinton debate, and then they say... if you ask them, they're undecided and they go to the, they go to the, uh, polling place and they think they're undecided and then a few seconds before they cast their vote, as you said, they say, "Okay, you know, I'm feeling Trump." Well, maybe they weren't undecided all along and if you, like, looked at the data-

    23. CW

      Mm-hmm.

    24. SS

      ... they were giving away subconsciously, uh, which way they were going to go, um, from-

    25. CW

      Have you, um, have you, have you looked at much of Sam Harris's work on free will?

    26. SS

      Uh, I, I do know, I do know, I do know some of that work. Yeah.

    27. CW

      Yeah. There's some interesting stuff on that about when they say, uh, raise your left or right hand or like pick a random city or whatever it might be, and if they put people into, uh, is it FMRIs where they can kind of do brain scans and stuff like that, and they're able to tell when someone made the decision to do the thing they're going to do before-

    28. SS

      Right.

    29. CW

      ... they do it and also before they think that they realized when they were going to decide to do it. Um, and that's kind of... This is like a more drawn out version of that, right?

    30. SS

      Yeah. Definitely. I'm sure it happens. Uh, yeah, I'm sure it's a pretty widespread phenomenon.

  4. 45:001:00:00

    Interesting. …

    1. SS

      Uh, basically the particular area you raise your kids and one of the reasons for this is that role models are really important for kids, and the role models aren't just you. So, uh, so if you see like, uh, girls who grow up in neighborhoods with lots of fema- adult female scientists are much more likely to become scientists themselves. Uh, they kind of see, they kind of see role models. African American boys who grow up around a lot of African American males who are successful, who stay married, who have jobs, are much more likely to do it themselves, and it's not necessarily through their own parents. So kind of one of the things, kids kind of discount advice from their parents frequently or rebel against their parents. So if your parent ... You know, if you're an African American boy, uh, your dad leaves you, you may just bec- y- you may decide, "I'm going to be the best parent ever because I don't want to be like my asshole dad." Uh, or your dad's a great dad, you're going to, you kind of rebel the other direction, "I can never live up to him." So it's kind of the parent relationship is very complicated but the neighbor relationship is not so complicated. It's kind of like if you have cool ... You're a Black boy and you have ac- cool a- good role m- African American role models on the street, that's unambiguously good. Uh, so in general, kind of like, uh, the, almost the best way to parent is kind of just get a lot of other people to do the job for, (laughs) for you to, uh ... You know, the, they're just going to discount anything you say, but if you kind of surround your kids with, uh, people who live life the way you want your kids to end up, uh, that, uh, will have a big impact. And you can-

    2. CW

      Interesting.

    3. SS

      Yeah, you can u- use this, you can use this finding in kind of lots of ways, kind of, uh, any t- ... I think, uh, parents try to lecture their kids too much, uh, try to lec- lecture their kids and, you know, "You got to do this, you got to do that." And I think a better way is take one of your friends who they admire to kind of tell them that, uh, where it's more likely to, to kind of th- they'll want to live up to it, uh, kind of u- utilize the fact that the, I think from the evidence, that, uh, other people are much more influential on your kid than you are, uh, because again, you, you are k- ... Your, their relationship with you is very complicated.

    4. CW

      Mm. Yeah. It's so funny that you can outsource parenting to the Joneses next door and be-

    5. SS

      Yeah.

    6. CW

      ... like, "Right, you take, you take our kids and I'll take-"

    7. SS

      Yeah. "... I'll take your kids and you be as good as you can and I'll be as good as I can and we'll just have like loads of Elon Musks." And it means you got, and it means you got to be cautious in who you, in th- the Joneses you choose, the particular Joneses or Johnsons-

    8. CW

      Mm-hmm.

    9. SS

      ... you choose. It's, uh, you can also, uh, have bad role models in the area, you know, that, uh, that, you know, they, they see a guy who just, like, is lazy all day and just drinks all the time and seems to be having a good time and they're just like, "Oh, I want to be like..."

    10. CW

      Yeah.

    11. SS

      "I want to be like that."

    12. CW

      Yeah. For sure.

    13. SS

      It's not going to be-

    14. CW

      It's, it's a cliché, right? It's the cliché of the, the parents that spend several thousand, tens of thousands of pounds, dollars per year sending their kid to some, uh, super high-end private school or they get them home tutored and they've had ... You know, they've tried to give them all of the opportunities and the, the head start in life or whatever it might be, and this kid is in with, like, a bad crowd and grows up to be e- some drug dealer or, so you know, get in trouble all the time, always getting kicked out of schools or whatever it might be, uh, despite the parents' best efforts to try and have this.

    15. SS

      Exactly. Well, I think the key is that you can't ... I think you can't m- ... I think what, what ... The way I read the evidence is you can't mold your kids too much because they re- k- they can rebel. You have to do it more subtly (laughs) , basically. Uh, you have to, you ha- you have to be more subtle in putting them in situations without them realizing it, uh, where they're ... You know, the kids have to want, uh, those outcomes. The outcomes that you want for your kid, you can't tell them to want them. They have to want ... learn to want them themselves that they're really going to go to it. 'Cause they can be in the nicest school in the world, if their goal in life is just to party and-... uh, you know, have fun and, uh, you know, not achieve academically or not work hard, then they're, they'll just do that, you know, no matter what you tell them, no matter what school you send them.

    16. CW

      Mm-hmm.

    17. SS

      But if you can somehow give, you know, gi- give them early on, uh, some people who they think are really cool, who work really hard and, and, you know, are, are, uh, you know, are a- achieve academically, then they'll want that in themself. They'll ask you to go to the private school.

    18. CW

      Mm-hmm.

    19. SS

      They'll ask you, uh, to, uh, you know, get a tutor and that's going to be really powerful, you know. The, the best thing you could probably do is trick them so that they're like, "I want a tutor," and you're like, "Well, I don't know if I can afford it," and then you finally, you eventually g- give in. Make it like they're like, make it they're fighting you to, uh, yeah, m- make, make it so like, uh, make it so th- so that they're kind of like, like you're, you're holding back what they really want. They, they-

    20. CW

      It was actually your plan all along.

    21. SS

      Yeah, actually or, it was your, yeah, but don't let, uh, don't let them realize that. I think that's more effective than saying, "You have a tutor. You gotta be there. You gotta play the piano, or you gotta do this." Uh, but, but again, yeah, yeah, the plan can work. It's just you gotta, you know, you know, like s- uh, you know, like somebody they think really cool. "I was tutored as, as a kid," like, "That's how I got really successful. That's how I got really..."

    22. CW

      Mm.

    23. SS

      Uh, "That's how I, that's how I, that's how I eventually like did these things that now you think are really cool."

    24. CW

      Yeah. I've, uh-

    25. SS

      I might, okay.

    26. CW

      Yeah. I've heard, um, uh, I don't know whether this is true, but I, I remember hearing some stories about where parents would treat vegetables, uh, as kind of precious and as a, a reward, kind of like they do with sweets to children, and they'd managed to kind of flip this sacrifice/reward matrix on its head so that kids were like really clamoring these, th- the children were really clamoring to get vegetables because of this basic like, "I don't have it, I want it."

    27. SS

      Yeah.

    28. CW

      Um ...

    29. SS

      I think that, uh, I think that, that probably, yeah, yeah. I think, uh ...

    30. CW

      Which is kind of like, it's like, that's going to be like finding out that Santa Claus isn't real or whatever. Sorry if anyone's kids are watching. I'm supposed to put a warning on before I do stuff like that. If you are listening with your children in the room, (laughs) I'm so sorry. Um, but it's the same as that, right? Like, it's like, uh, one day they'll grow up and they'll be like 14 and realize, "Hang on a second. Vegetables weren't a treat all along. Like, I've been lied to for the last (laughs) 14 years of my life by these tyrants that I've got as, as parents." But, uh-

  5. 1:00:001:02:01

    Yep. …

    1. CW

      the stuff like that. But as you say, this anonymous aggregated data is precisely that. Like, it's happening, but I don't know that it's you or as if it's the guy next door.

    2. SS

      Yep.

    3. CW

      Yeah.

    4. SS

      Yeah. Definitely. (laughs)

    5. CW

      Yeah, which is interesting. Anyway, man, this has been absolutely awesome. Have we got ... Seth, have we got a, um, a, a date or a, uh, an idea in mind about when the, the next book's gonna come out?

    6. SS

      Probably 2021, but uh, I'm not sure exactly when.

    7. CW

      You got to get through this presidential election, then you're gonna have to do all of your cool-

    8. SS

      Yeah, I think, uh, yeah. I'll publish it during the election because everyone's gonna be focused on the, on the election.

    9. CW

      Yeah. I was talking to, uh, Paul Bloom, uh, from Yale and, uh-

    10. SS

      Okay.

    11. CW

      He was, he was saying precisely the same thing. He's doing this new book about, um, suffering. About how people really enjoy suffering. He'd managed to find a link between BDSM and meditation, which actually sounds exactly like one of the things that you would, you would've come up with out of big data. And, um, he wa- he was saying ex- He was like, "Ah, I think it'll maybe be finished, like, first draft sort of start of the year," and blah, blah, blah. And I said, "Oh cool. So are we gonna get it next year?" And he's like, "No, man. (laughs) It's an election this year, like (laughs) I'm not, I'm not releasing anything."

    12. SS

      Right.

    13. CW

      (inhales through nose) So 2021, hopefully we'll get a load of new, uh, literacy stuff through. So, um, where can people find you online, Seth? They want to f- follow your stuff. Where can they go?

    14. SS

      Uh, probably just Google Seth Everybody Lies. Nobody's going to remember my last name, so just Seth Everybody Lies and then they'll, they'll find, you know, my Twitter and everything else. So ...

    15. CW

      Awesome, man.

    16. SS

      Yeah.

    17. CW

      Thank you so much. Well, I really appreciate your time, um, um, I'm gonna try and work out who it was that I lived near at home and, uh, and see where the, the in- influence was on me.

    18. SS

      Great.

    19. CW

      Cheers, man. Thank you so much, dude.

    20. SS

      Thank you.

    21. NA

      (instrumental music plays)

Episode duration: 1:02:01

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