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Speaker 1: Get in touch with technology with text Stuff from dot

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Speaker 1: com either and welcome to text Stuff. I'm Jonathan Strickland,

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Speaker 1: and today I have a special guest host, Alison louder Milk,

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Speaker 1: wu's editor extraordinary here in Hell Stuff Works dot Com.

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Speaker 1: Thank you very much, Donathan. I love that introp So

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Speaker 1: I'm glad now those of you who have been listening

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Speaker 1: to How Stuff Works podcast for a while will recognize

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Speaker 1: Allison's voice. She's an old hand at podcasting. Though you've

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Speaker 1: taken a nice long hiatus, I have that. It's a

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Speaker 1: pleasure to be here today. Yeah, fantastic, And so I

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Speaker 1: asked Allison what she would like to talk about. When

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Speaker 1: she agreed that, you know, she jump on and be

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Speaker 1: a guest. I give my guests the opportunity to pick

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Speaker 1: if they want to. And you jokingly suggested an app

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Speaker 1: called Cuddler, And while that was a joke, it led

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Speaker 1: to the actual choice of this episode, which goes beyond Cuddler.

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Speaker 1: But we will talk about that right, right, right, We

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Speaker 1: were talking about it in the break room and the

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Speaker 1: fascination that was Cuddler. Yeah, yeah, there's kind of a

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Speaker 1: horrid fascination for a lot of us here and how

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Speaker 1: stuff works. Who have very specific parameters, uh, within which

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Speaker 1: we welcome that kind of personal interaction, and when it's

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Speaker 1: outside those parameters, we get a little wigged out by it,

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Speaker 1: but we'll get there. So we decided we wanted to

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Speaker 1: talk about how the Internet has become an incredible tool

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Speaker 1: for people to first meet each other in the online

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Speaker 1: space or the digital space, and then event eventually transition

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Speaker 1: that into meeting in real life. And a lot of

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Speaker 1: what we're going to talk about today is focused on dating,

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Speaker 1: but that's not exclusively what we're going to talk about.

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Speaker 1: But it turns out that's a that's a big part

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Speaker 1: and has been a big part of the Internet since

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Speaker 1: the Internet became a thing that most of us got

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Speaker 1: access to. Yes, do you have any kind of early

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Speaker 1: memories of some emails you sent, maybe to a lady

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Speaker 1: you were interested in, or well, there's a there's a

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Speaker 1: lady that I was very much interested in, a lady

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Speaker 1: who I'm still very much interested in because she's my wife.

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Speaker 1: I met her in a chat room online, Yeah, a

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Speaker 1: tell net chat room, so not even a web based one.

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Speaker 1: In fact, when I met my wife, the web was

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Speaker 1: new to me, Like I had not even used a browser. Uh.

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Speaker 1: I had seen other people on a browser, and I thought, well,

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Speaker 1: that looks really interesting. But I was jumping into chat

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Speaker 1: rooms just chatting about anything really and she and I

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Speaker 1: hit it off, and we ended up, uh, corresponding quite

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Speaker 1: a bit, and then we met in person, and then

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Speaker 1: we started dating, and then she moved to Georgia, and

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Speaker 1: then we got engaged, and then we got married. And

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Speaker 1: seventeen years later, here we are so early story of

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Speaker 1: using the Internet to do exactly what we're talking about.

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Speaker 1: So I have personal experience here, but you know, we've

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Speaker 1: seen the people use the Internet for all sorts of

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Speaker 1: things along those lines. And here's an interesting statistic I found.

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Speaker 1: According to the American National Academy of Sciences, which did

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Speaker 1: a survey back in two thousand thirteen, more than thirty

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Speaker 1: three of all people who got married in the United

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Speaker 1: States between two thousand five and two thousand twelve met

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Speaker 1: their spouse online. Yeah. That's a large swath of people. Yeah,

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Speaker 1: more than a third of all of all married couples

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Speaker 1: first met online, well married couples from two thousand five

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Speaker 1: to two thousand and twelve. And that's incredible to me.

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Speaker 1: I mean, I remember when I started dating my wife,

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Speaker 1: that was considered unusual. Yeah, we all have friends who've

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Speaker 1: met online, and I was kind of a novelty back

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Speaker 1: in the day. I remember thinking, you know, one of

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Speaker 1: my very dear friends met her husband on match dot com,

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Speaker 1: and I was a little wary, like, but it's it's

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Speaker 1: pretty it's pretty normal now normal if I when when

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Speaker 1: more than a third, you know, it's quickly becoming as

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Speaker 1: normal as other method of meeting people and getting to

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Speaker 1: know someone and dating them. And uh, yeah, for me,

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Speaker 1: it was it was outside the norm both because one

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Speaker 1: the Internet was so new, and too that I was

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Speaker 1: getting a date, so it was multiple outside the norms.

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Speaker 1: But uh, I read a CNN article which was not

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Speaker 1: entirely helpful because they reported that a survey which was

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Speaker 1: unnamed in the article, so that by two thousand nine

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Speaker 1: of all same sex couples reported meeting online first, and

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Speaker 1: about half of all married couples who met online did

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Speaker 1: so through dating sites. So in order for us to

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Speaker 1: really talk about it, we're gonna be looking a lot

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Speaker 1: at dating sites early on in this episode and what

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Speaker 1: they do and how they do it. So across platforms,

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Speaker 1: about eleven percent of Internet users have said they've used

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Speaker 1: an online dating site, and across cell phone users, about

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Speaker 1: seven percent have used a dating app on their phones,

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Speaker 1: and it seems like it's going more in that direction,

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Speaker 1: although if you look at it from a stock market

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Speaker 1: type perspective, it's still the online dating sites that are kicking,

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Speaker 1: but in terms of market share and actually making revenue,

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Speaker 1: and that that comes from a two thousand thirteen report

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Speaker 1: from the Pew Research Internet Project. And what's also interesting

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Speaker 1: is that it just continues to get more segmented, right,

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Speaker 1: so you have you know, Jonathan, maybe you and I

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Speaker 1: were first interested in this, but now it's our parents,

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Speaker 1: and now it's more niche markets to oh sure, yeah,

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Speaker 1: So we're seeing lots of of services and sites pop

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Speaker 1: up that are catering to very specific demographics. Right, So

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Speaker 1: you might see one that's catering specifically to uh, to

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Speaker 1: the baby boomer boomer generation, or some that are obviously

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Speaker 1: based just on the experience, geared towards folks who are

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Speaker 1: more in the college age range or uh. You know,

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Speaker 1: there are a ton of different variations on this. So there,

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Speaker 1: of course some sites that try to be all things

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Speaker 1: to all people, and then we're seeing a lot more

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Speaker 1: of these that are kind of tailor made for specific demographics.

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Speaker 1: It was funny. I was talking to a coworker who

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Speaker 1: just signed up her mom last night for I think

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Speaker 1: it was called Our World or My World. Her sixty

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Speaker 1: three year old mom was like, Hey, can you help

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Speaker 1: me get on some of these dating sites? And she said, okay, Mom, Yeah.

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Speaker 1: I mean again, that might sound unusual to us, in

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Speaker 1: particular not to put a number to our ages, but

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Speaker 1: Alison and I both can remember a time when the

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Speaker 1: Internet wasn't really a thing that we access um, So

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Speaker 1: it's certainly something that's still there's still elements of it

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Speaker 1: that are kind of unusual to us, but it's becoming

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Speaker 1: increasingly normal to the younger generations because they grew up

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Speaker 1: with this, And you know, why not have this be

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Speaker 1: a tool to to meet people and to try and

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Speaker 1: match yourself up with people who are sharing the same

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Speaker 1: sort of interest that you do and thus potentially find

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Speaker 1: someone with whom you're going to be really compatible with.

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Speaker 1: You mentioned before that this is a big industry. You know,

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Speaker 1: you talked about a lot of how how many people

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Speaker 1: on the Internet had used a site, and you mentioned

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Speaker 1: that you know, there's there's real money to be made here.

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Speaker 1: But let's get to some real figures, right, So there

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Speaker 1: is some serious money to be made here. I was

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Speaker 1: reading a report from IBIS World looks like some sort

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Speaker 1: of industry research type of report at two thousand fourteen,

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Speaker 1: and the authors were estimating that it's about a two

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Speaker 1: billion dollar market dating services in the US. So that's

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Speaker 1: the broader context. And within that, of course, online is

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Speaker 1: going to be you know, a slice of that, and

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Speaker 1: that slice is about so one point four billion is

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Speaker 1: what we're talking about now, and I can only see

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Speaker 1: that growing. Yeah, yeah, I agree, And we're seeing it

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Speaker 1: grow in interesting ways too. Whereas the desktop online dating

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Speaker 1: sites are still very much a thing, we're seeing an

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Speaker 1: explosion of this kind of stuff in the mobile space,

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Speaker 1: both mobile apps that are tied into an existing online

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Speaker 1: dating site and those that are its own experience ends.

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Speaker 1: And we'll talk about some of those two. And uh,

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Speaker 1: it's not it's not just that's big business, but for

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Speaker 1: the consumer, as in the person who's looking for a date,

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Speaker 1: it turns out to make sense financially too, right, So

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Speaker 1: this is pretty interesting. Um I. And another report um

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Speaker 1: from the Topeka Capital Markets that was again like two thousand,

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Speaker 1: fourteen or so. Um, they found that it was cheaper. Right,

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Speaker 1: So you're paying for your subscription to your online site,

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Speaker 1: but what you're looking at, according to this report, is

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Speaker 1: about a twenty three dollar tab before you finally wind

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Speaker 1: up making a match of your dreams. Yeah, so these

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Speaker 1: guys are saying that if you pay your subscription of

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Speaker 1: you know, maybe two d or some dollars, you're gonna

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Speaker 1: wind up with cost savings, like in a thousands of dollars.

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Speaker 1: So so online dating makes sense to your wallet, Yeah,

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Speaker 1: because it means that what what it means is that

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Speaker 1: while you're in pursuit of finding this person who's going

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Speaker 1: to compatible with you, you can do a lot of

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Speaker 1: that early work online as opposed to meeting people in places,

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Speaker 1: going out to take people out to to, you know, whatever,

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Speaker 1: a dinner or a movie or whatever, even if everyone's

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Speaker 1: paying for their own thing. Obviously, all of that stuff

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Speaker 1: starts to mount up, and not every date turns out

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Speaker 1: to be a success. Sometimes you realize, oh, you know,

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Speaker 1: this person is really nice, but we're not really clicking things. Yeah,

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Speaker 1: there's no spark there, and so yeah, I could I

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Speaker 1: could definitely see this. I am personally very thankful for

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Speaker 1: the money that the Internet has saved me in that sense.

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Speaker 1: So looking more closely at what's going on with these

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Speaker 1: dating sites, like how they work, you actually have to

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Speaker 1: go all the way back to nineteen sixty five. Now,

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Speaker 1: clearly I'm not talking about an Internet dating service that

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Speaker 1: far back, because that's pre Internet. We're talking arpennet days

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Speaker 1: back then. But ninety five was before the era of

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Speaker 1: the personal computer. We didn't even have PCs yet. But

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Speaker 1: a Harvard undergraduate named Jeff Tar was working on this idea.

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Speaker 1: He had come up with a notion. He noticed that

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Speaker 1: a lot of other Harvard undergraduate graduates were talking about

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Speaker 1: finding it difficult to find a date, like it's just

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Speaker 1: hard to go out and meet people that were compatible.

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Speaker 1: And he thought, hmm, there are these computer things that

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Speaker 1: crunched numbers really well. And he was he was a

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Speaker 1: math major, uh, and he he got to work with computers,

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Speaker 1: but he didn't really understand programming. At this point, they said,

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Speaker 1: you know, there are these computers that are really good

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Speaker 1: at number crunching. If we were to reduce the personality,

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Speaker 1: uh preferences of people to numbers, then a computer could

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Speaker 1: theoretically start matching people who have the most similar responses

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Speaker 1: to a survey. So that's why he did. He developed

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Speaker 1: a survey, gave it to tons of his classmates, and

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Speaker 1: he essentially relied on the second person to create a

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Speaker 1: computer program that would match up these were ponses, and

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Speaker 1: he rented time on one of the enormous computers at Harvard.

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Speaker 1: I think it was like a hundred dollars a day

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Speaker 1: or something in order for him to rent the time

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Speaker 1: on this machine. It might have even been higher than that,

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Speaker 1: but it was a wild success. People loved the idea

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Speaker 1: of being able to use a machine to take out

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Speaker 1: the guesswork of trying to find that perfect person. In fact,

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Speaker 1: there was one report of a young lady who was

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Speaker 1: matched up with her ex boyfriend and got back with

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Speaker 1: him because the computer told her to. So that we

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Speaker 1: started to act like the computer was like the oracle

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Speaker 1: and that we must obey the machine. Uh. But you

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Speaker 1: know again, it kind of showed a couple of different

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Speaker 1: things that showed how people really wanted to find someone

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Speaker 1: who was compatible. And it also showed that there was

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Speaker 1: this reverence for computers because they were objects a myth

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Speaker 1: and legend to most people back in the sixties, they

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Speaker 1: didn't have the experience with computers that we do today.

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Speaker 1: Once you've gone through a few blue screens of death,

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Speaker 1: you realize they're not infallible machines. But at any rate,

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Speaker 1: if you flash forward to the nineteen nineties, by then

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Speaker 1: you had had some computer dating services uh competing in

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Speaker 1: the United States. But now we see the rise of

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Speaker 1: the Internet, especially with the World Wide Web. The Internet

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Speaker 1: had been around, but the World Wide Web was what

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Speaker 1: made it accessible, and uh so you've got those earliest

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Speaker 1: connectivity opened up the opportunity for meeting new people that

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Speaker 1: you might never have ever encountered in your life otherwise.

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Speaker 1: So we've got an article actually on how Stuffworks dot

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Speaker 1: Com about how online dating works. So it'll cover all

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Speaker 1: the basics. But if anyone has ever done any browsing

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Speaker 1: on an online dating site, you know typically what they're about.

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Speaker 1: It's usually you you create a profile, probably include a picture. Absolutely,

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Speaker 1: you probably include the best pictures you possibly can to

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Speaker 1: present yourself in the best light possible professional head shot.

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Speaker 1: Then you are going to fill out a profile that

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Speaker 1: includes a lot of your preferences, things that you enjoy

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Speaker 1: things that you're you're not into. It might be things,

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Speaker 1: yeah I'm a non smoker, that kind of stuff. Political affiliation,

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Speaker 1: it could be is, and it really depends upon the site.

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Speaker 1: Like some sites, that's true. Also, are you are you

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Speaker 1: into pets? Do you like pets? Do you like kids,

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Speaker 1: you're not like kids? Do you want to have kids?

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Speaker 1: Do you already have kids? These are all the sorts

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Speaker 1: of questions that you would put it there, and then

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Speaker 1: when you go for a search, then you can say

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Speaker 1: which parameters you consider to be the most important, like say, uh,

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Speaker 1: they need their age needs to fall within this range,

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Speaker 1: or I'm not going to have anything in common with

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Speaker 1: this person, or height is a big one. Height is

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Speaker 1: a big one. I read that b m I in

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Speaker 1: regards to men looking for women was a big factor. Yeah, yeah,

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Speaker 1: I think it was around like eighteen point five percent.

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Speaker 1: Was one figure sided like they like women with that

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Speaker 1: sort of b m I, which is ridiculous. Well, now

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Speaker 1: there's a whole other discussion we could have about expectations

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Speaker 1: and realism. But at any rate, one of the interesting

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Speaker 1: things I found was that we don't necessarily know what

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Speaker 1: it is we're looking for when we're looking for it

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Speaker 1: nor or we may we may have a suspicion, but

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Speaker 1: we may not be honest about it when we're doing

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Speaker 1: our search. For example, let's say that I put in

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Speaker 1: there that I really want to meet someone who's really

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Speaker 1: interested in reading, but it turns out that there are

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Speaker 1: other factors that I think are way more important. But

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Speaker 1: I'm trying to present myself as someone who is an

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Speaker 1: intellectual and therefore value this. Some online dating sites can

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Speaker 1: figure out when you're fibbing, because it's your behavior that

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Speaker 1: tells the site what you're really into. Because if I

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Speaker 1: start going through profiles and I'm spending less than a

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Speaker 1: couple of seconds on them, and I'm zooming through them

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Speaker 1: really quickly, the the online dating stars can log all

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Speaker 1: that and say, all right, well, we gave him the

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Speaker 1: matches based upon what he said he wanted, but he

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Speaker 1: totally breathed through them all so except this one. He

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Speaker 1: spent a couple of months looking at this one. So

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Speaker 1: really he's looking more for what this person represents rather

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Speaker 1: than what he says he represents. And as more and

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Speaker 1: more data gets accumulated, the more people who use the site,

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Speaker 1: the dating site algorithms adjust themselves and start showing you

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Speaker 1: what you really want, even if you're not aware that

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Speaker 1: that's what you want to you. Yeah, which is kind

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Speaker 1: of weird. I mean, we've talked on tech stuff many

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Speaker 1: times about how it only takes a little data to

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Speaker 1: give a system a great idea of who you are

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Speaker 1: as a person, but it even is true in the

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Speaker 1: dating world. There's also approach called collaborative filter filtering. This

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Speaker 1: is where a system will organize people into large groups

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Speaker 1: just based on preferences which might not even be obvious

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Speaker 1: from the outside. So, all right, so let's say we've

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Speaker 1: we've at a population of like ten thousand people and

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Speaker 1: they've all created profiles. The algorithm will start to find

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Speaker 1: commonalities between those people that again, if you were just

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Speaker 1: to look at the profiles as a human being, you

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Speaker 1: might not even be able to pick out which things

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Speaker 1: they have in common. But because we're talking about sites

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Speaker 1: that have access to such huge amounts of data and

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Speaker 1: can run all these different types of comparisons against one another,

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Speaker 1: it makes perfect sense to the algorithm, which is kind

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Speaker 1: of creepy in a way when you think about it,

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Speaker 1: because it ultimately starts to divide people into large groups

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Speaker 1: and it suggests that there are a limited number of

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Speaker 1: groups that people fall into. In other words, it's kind

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Speaker 1: of like thinking about horoscopes. I don't like the idea

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Speaker 1: of a horoscope because it suggests that there are only

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Speaker 1: twelve types of people in the world, right, I mean,

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Speaker 1: if you if you leap to that, if you say,

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Speaker 1: my horoscope for today is, etcetera, that means that roughly

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Speaker 1: one twelfth of the world's population is going to have

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Speaker 1: the same sort of day I'm going to have, which

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Speaker 1: doesn't make sense. But these systems actually show that that's

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Speaker 1: not that far off from the truth in the sense

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Speaker 1: that there a limited number of categories that you can

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Speaker 1: actually shove people into, and from at least a mathematic perspective,

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Speaker 1: it makes sense. It works. Yeah, so little creepy um,

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Speaker 1: But it turns out like that's not it's not always

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Speaker 1: just about the data, the personal data about yourself, right right.

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Speaker 1: So one really interesting thing that I found, um was

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Speaker 1: I happened to stumble upon a gentleman by the name

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Speaker 1: of Dan Arielli. I believe that's how you say his

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Speaker 1: last name. And he's over a duke, and he's a

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Speaker 1: professor of psychology and behavioral economics. By the way, behavioral

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Speaker 1: economics is so fascinating. So um Dan gave an interview

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Speaker 1: to the big thing, and what he was saying was right,

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Speaker 1: it's not all about the personal data. It's not about

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Speaker 1: the boxes you check or you know, your particular preferences.

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Speaker 1: And what he was postulating after he kind of browsed

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Speaker 1: online dating sites and found them significantly lacking, was that

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Speaker 1: it's more about your interaction with the person. That you

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Speaker 1: can tell a lot more about an interaction with a

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Speaker 1: person than by simply like knowing that you're eyes are

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Speaker 1: blue and you like cats and whatever it is about you. Right,

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Speaker 1: It's kind of like the difference between a resume and

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Speaker 1: a job interview. Absolutely, And so his idea is, let's

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Speaker 1: get away from the check boxes and let's set up

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Speaker 1: ways for people to interact. And so he set up

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Speaker 1: this website and it was basically you can pick an

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Speaker 1: avatar and just really simple. It wasn't like one of

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Speaker 1: these crazy avatars. It was maybe a triangle and a square,

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Speaker 1: there's some color in there. And then he basically put

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Speaker 1: like movies and images and words, and you kind of

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Speaker 1: move around and navigate and you talk to other avatars

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Speaker 1: as you encounter them, and so how all these encounters went,

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Speaker 1: which is set up like a better interaction for people

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Speaker 1: to meet each other and get to know each other

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Speaker 1: and have a successful date ultimately. Well, that's really cool

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Speaker 1: that the channel of that is that it kind of

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Speaker 1: requires a synchronous approach, meaning that both parties need to

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Speaker 1: be active at the same time, whereas we're seeing a

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Speaker 1: lot of communication online is asynchronous, right, the idea that

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Speaker 1: I can send you a message, Allison, and then you

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Speaker 1: respond to it when you have the availability when you

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Speaker 1: may not even notice that you have a message until

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Speaker 1: an hour later, and you respond and I might not

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Speaker 1: notice till three hours later. But we can continue to

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Speaker 1: have this communication, which is effective in many ways, but

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Speaker 1: it because, yeah, it's disjointed. It's it's you don't have

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Speaker 1: a continuous experience. It takes away a lot of that

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Speaker 1: spontaneity that you would have in a conversation with an

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Speaker 1: actual person in real time. So it's not that there's

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Speaker 1: no value in that type of communication. There certainly is.

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Speaker 1: And uh, and I love using all the tools that

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Speaker 1: have this asynchronous communication aspect to them, but uh, you know,

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Speaker 1: this approach, while it might be more effective than say,

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Speaker 1: just a a collection of profiles. It demands that you

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Speaker 1: have this you know, real time interaction with somebody, which

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Speaker 1: limits the number of people that you can presumably encounter

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Speaker 1: because it all depends on when both parties are available

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Speaker 1: to interact, right, So if you're available to interact at

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Speaker 1: the same time, I'm thinking that a synchronous interaction, I mean,

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Speaker 1: it just seems like it would be more effective, right

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Speaker 1: because you're talking to somebody who's in the same frame

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Speaker 1: of minded view. Sure, yeah, I mean, and there are

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Speaker 1: a lot of dating sites that have a message system

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Speaker 1: where you know, either it's like an instant message type

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Speaker 1: thing or something along those lines, where you can set

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Speaker 1: that sort of thing up if both parties are online,

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Speaker 1: but they don't, they don't depend upon that, right. That's

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Speaker 1: that's an added benefit to those sites. You could totally

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Speaker 1: have and asynchronous conversation with someone in a series of messages,

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Speaker 1: you know, back and forth between each other. But I

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Speaker 1: do think that ari elli is onto something. I think

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Speaker 1: Arie Ellie is right and that these kind of interactions

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Speaker 1: tend to have more value to them than the asynchronous type.

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Speaker 1: So he had a funny stat and what he was

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Speaker 1: suggesting with that online dating right is ineffective and inefficient.

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Speaker 1: And so one of the things that he said was

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Speaker 1: that about six hours of chat for one lousy coffee date.

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Speaker 1: I mean that's a lot of time invested. There's a

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Speaker 1: lot of time invested. Yeah, I mean it's And that's

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Speaker 1: the thing is that you can't expect every single interaction

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Speaker 1: to go well. In fact, we'll be talking about expectations

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Speaker 1: a lot in this episode. Uh, you know, the people

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Speaker 1: are people, and you may think going into something that

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Speaker 1: you're going to have this incredible interaction, which might just

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Speaker 1: be unrealistic expectations. Um, And that's just a human problem

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Speaker 1: that's been around forever. I mean that has nothing to

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Speaker 1: do necessarily with the Internet. It's or or these dating

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Speaker 1: apps and sites. The dating sites often create kind of

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Speaker 1: a problem with this because they're built upon the promise

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Speaker 1: that their service will help you find someone special. So

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Speaker 1: it behooves them to kind of foster this image that

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Speaker 1: you are going to meet Mr or Mrs Wright just

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Speaker 1: by following, you know, us, creating a profile and seeking

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Speaker 1: them out this way. But human interaction is far more

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Speaker 1: complicated than that. That, however, is not the right way

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Speaker 1: to sell memberships to your dating site. Hey, it's complicated

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Speaker 1: and you may or may not like this person. Come

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Speaker 1: join our site for twenty bucks a month, but at

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Speaker 1: any rate. Um. You know, we also have the interesting

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Speaker 1: research that goes into, uh, how the dating sites create

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Speaker 1: these algorithms that match people up. Um. There have been

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Speaker 1: some folks who have looked into it from a personal perspective,

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Speaker 1: people who happened to work in statistics and mathematics and

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Speaker 1: computer science, who who were looking for a date and wondering, well,

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Speaker 1: what's the most effective way for me to use this tool?

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Speaker 1: Engineers tend to think in that way, like you gave

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Speaker 1: me a tool, and I can use it this way,

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Speaker 1: but is there a better way to use it? So,

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Speaker 1: people like Chris McKinley and Amy Webb have experimented with

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Speaker 1: various online dating sites to find out what was working

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Speaker 1: behind the scenes, How were these matches made the most

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Speaker 1: successful profiles, What what was it about those profiles that

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Speaker 1: made them successful? And so they really looked deeply into

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Speaker 1: these things to figure out how they work, so that

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Speaker 1: not that they could game the system, but so that

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Speaker 1: they could make the most effective profile to find the

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Speaker 1: people they're interested in meeting. Okay, so when we're talking

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Speaker 1: about an effective profile, do we mean like somebody who's

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Speaker 1: been successful at finding one relationship that the person is

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Speaker 1: stuck with or just having a lot of dates. I

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Speaker 1: think it was more about the number of responses. They

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Speaker 1: wanted to find a profile that got the most responses

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Speaker 1: from the people that seemed to be the target audience,

432
00:23:59,440 --> 00:24:03,680
Speaker 1: the people that the folks that the the individuals themselves

433
00:24:03,680 --> 00:24:06,760
Speaker 1: were interested in dating. And so Amy Web actually has

434
00:24:06,760 --> 00:24:09,480
Speaker 1: a fantastic ted talk where she goes through this whole

435
00:24:09,520 --> 00:24:13,560
Speaker 1: process and talked about how she identified the language that

436
00:24:13,640 --> 00:24:16,480
Speaker 1: was being used in very successful profiles. She had created

437
00:24:17,440 --> 00:24:23,320
Speaker 1: several fake profiles and populated them with different approaches to

438
00:24:23,480 --> 00:24:26,560
Speaker 1: kind of see which ones were the most effective, you

439
00:24:26,600 --> 00:24:29,840
Speaker 1: know what, what sort of UH profiles would get the

440
00:24:29,840 --> 00:24:34,440
Speaker 1: most responses. And the the results were dramatic. And some

441
00:24:34,480 --> 00:24:38,320
Speaker 1: people might say, well, as that totally ethical, I mean,

442
00:24:38,359 --> 00:24:40,560
Speaker 1: you've got actual people who are looking for a date

443
00:24:40,840 --> 00:24:44,760
Speaker 1: and they're pursuing a date with a fake persona. But

444
00:24:45,000 --> 00:24:47,600
Speaker 1: at any rate, she said, well, I was doing research,

445
00:24:47,760 --> 00:24:49,800
Speaker 1: you know, I needed to find out how this worked.

446
00:24:49,800 --> 00:24:52,240
Speaker 1: And once I knew that, I could tweak my own profile,

447
00:24:52,680 --> 00:24:55,040
Speaker 1: and sure enough she met a guy they ended up dating,

448
00:24:55,080 --> 00:24:58,560
Speaker 1: and then they ended up getting married. So she was

449
00:24:58,600 --> 00:25:01,000
Speaker 1: doing it both because she is interested in the system

450
00:25:01,000 --> 00:25:04,439
Speaker 1: and also because she genuinely was trying to find someone

451
00:25:04,520 --> 00:25:07,600
Speaker 1: to to go out on dates with. So it to

452
00:25:07,680 --> 00:25:09,840
Speaker 1: me what was interesting is that there are now two

453
00:25:09,880 --> 00:25:13,000
Speaker 1: different types of algorithms out there. There's the algorithm that's

454
00:25:13,040 --> 00:25:15,040
Speaker 1: being used by the dating site to figure out how

455
00:25:15,080 --> 00:25:17,600
Speaker 1: to match people up, and then there are the algorithms

456
00:25:17,640 --> 00:25:20,040
Speaker 1: that people have come up with to figure out how

457
00:25:20,080 --> 00:25:23,840
Speaker 1: to make their profile the most attractive in order to

458
00:25:23,880 --> 00:25:27,719
Speaker 1: get the most potential dates, therefore having the most potential

459
00:25:27,840 --> 00:25:30,919
Speaker 1: chances of finding that someone special. I'd be curious to

460
00:25:30,960 --> 00:25:32,840
Speaker 1: hear what she found out was effective. I mean, I

461
00:25:32,880 --> 00:25:35,760
Speaker 1: think that we've all kind of had the experience of

462
00:25:35,840 --> 00:25:37,560
Speaker 1: maybe your friend is going to go on an online

463
00:25:37,640 --> 00:25:40,920
Speaker 1: dating service, and I certainly, as an editor and lover

464
00:25:41,040 --> 00:25:44,679
Speaker 1: of words in general, have helped friends craft profiles. And

465
00:25:44,720 --> 00:25:48,199
Speaker 1: it's comical. I mean it is comical. So whatever the

466
00:25:48,520 --> 00:25:52,960
Speaker 1: your flaw is, say you're a big old procrastinator, Well,

467
00:25:53,000 --> 00:25:56,280
Speaker 1: I'm laid back, you know, I'll like to take my

468
00:25:56,400 --> 00:25:59,760
Speaker 1: time and enjoy life, right right, So all the code

469
00:25:59,760 --> 00:26:01,919
Speaker 1: were it's in the little editing that you do to

470
00:26:02,000 --> 00:26:06,040
Speaker 1: just tweak it enough. Yeah, it's it's again. It's a

471
00:26:06,040 --> 00:26:10,040
Speaker 1: lot like building a resume, which is both a good

472
00:26:10,080 --> 00:26:13,119
Speaker 1: and a bad thing, right because a resume is all

473
00:26:13,119 --> 00:26:16,200
Speaker 1: about putting your best professional face forwards that you get

474
00:26:16,200 --> 00:26:18,679
Speaker 1: the best opportunity to get a job interview. This is

475
00:26:18,840 --> 00:26:22,120
Speaker 1: putting your best personal face forward to get that opportunity

476
00:26:22,160 --> 00:26:26,160
Speaker 1: for a date. Uh yeah, it's and it's serious business.

477
00:26:26,200 --> 00:26:29,000
Speaker 1: I mean, this is this is these are people's lives

478
00:26:29,119 --> 00:26:31,919
Speaker 1: and not to mention, an entire one point four billion

479
00:26:31,920 --> 00:26:35,439
Speaker 1: dollar industry. So it's a big deal. So how do

480
00:26:35,560 --> 00:26:40,160
Speaker 1: these websites actually make money? Right? So, we talked about

481
00:26:40,160 --> 00:26:44,840
Speaker 1: the subscription service model, right, so you pay some feed

482
00:26:44,880 --> 00:26:47,479
Speaker 1: monthly and or maybe you get I mean, okay, Cupid

483
00:26:47,520 --> 00:26:50,840
Speaker 1: for example, does not it's all free. But then match

484
00:26:50,960 --> 00:26:53,480
Speaker 1: I believe an e Harmony and some of those uh

485
00:26:53,560 --> 00:26:55,240
Speaker 1: you know, to get messages and things like that, you

486
00:26:55,280 --> 00:26:59,640
Speaker 1: have to pay a subscription and then their ads of course, sure, yeah,

487
00:26:59,680 --> 00:27:02,240
Speaker 1: adds support is one of the big ways that any

488
00:27:02,359 --> 00:27:05,840
Speaker 1: web presence makes money. Right. So, but it's not clear

489
00:27:05,880 --> 00:27:07,840
Speaker 1: how some of these apps are making money, and I

490
00:27:07,880 --> 00:27:11,520
Speaker 1: think that they aren't I mean, yeah, no, that's a

491
00:27:11,560 --> 00:27:14,000
Speaker 1: lot of apps don't make money because what the app

492
00:27:14,280 --> 00:27:17,919
Speaker 1: developers trying to do is create a tool that becomes

493
00:27:18,160 --> 00:27:22,640
Speaker 1: so popular that some other company buys out the person

494
00:27:22,680 --> 00:27:25,960
Speaker 1: who developed it, right, I mean, that's the approaches. Let's

495
00:27:26,040 --> 00:27:28,840
Speaker 1: let's make a tool that everyone loves so much that

496
00:27:29,880 --> 00:27:32,119
Speaker 1: a company is going to swoop in here, pay me

497
00:27:32,200 --> 00:27:34,840
Speaker 1: a huge amount of money because of the value that

498
00:27:35,320 --> 00:27:38,440
Speaker 1: the potential or the potential value of that app, because

499
00:27:38,440 --> 00:27:40,240
Speaker 1: of all the people who are using it. You know,

500
00:27:40,320 --> 00:27:42,520
Speaker 1: keep in mind, whenever we're talking about a service or

501
00:27:42,560 --> 00:27:45,000
Speaker 1: an app like this kind of thing, ultimately the product

502
00:27:45,160 --> 00:27:49,200
Speaker 1: is us, the people using that service or app. Where

503
00:27:49,240 --> 00:27:52,160
Speaker 1: the product where the We're the thing that is making

504
00:27:52,200 --> 00:27:55,760
Speaker 1: the money, making money for whatever company owns it. So

505
00:27:55,960 --> 00:28:00,399
Speaker 1: if you are like a tender and you have no jones,

506
00:28:00,480 --> 00:28:03,320
Speaker 1: actually there you go. So if you if you had

507
00:28:03,359 --> 00:28:07,000
Speaker 1: created that app and uh, you didn't have a way

508
00:28:07,000 --> 00:28:10,080
Speaker 1: of monetizing it directly, it may just be that you're

509
00:28:10,119 --> 00:28:12,760
Speaker 1: doing it because it's a really useful thing. People are

510
00:28:12,760 --> 00:28:15,440
Speaker 1: really into it. People are a lot of people are

511
00:28:15,600 --> 00:28:18,960
Speaker 1: are downloading it and active on it. Someone is going

512
00:28:19,000 --> 00:28:21,600
Speaker 1: to find that valuable and they're going to purchase you.

513
00:28:22,680 --> 00:28:25,320
Speaker 1: A lot of them also just exist on venture capitalist

514
00:28:25,600 --> 00:28:30,840
Speaker 1: investment for the short term, which is that's risky because

515
00:28:31,000 --> 00:28:33,800
Speaker 1: that's an investment. People expect to have a return on

516
00:28:33,840 --> 00:28:36,960
Speaker 1: that investment, So you have to eventually figure out a

517
00:28:37,000 --> 00:28:40,360
Speaker 1: way to make some money or you're just gonna you know,

518
00:28:40,440 --> 00:28:43,120
Speaker 1: you've slid your reputation. If you are known as someone

519
00:28:43,160 --> 00:28:47,480
Speaker 1: who makes tools that ultimately never pay out, then you're

520
00:28:47,520 --> 00:28:50,200
Speaker 1: not going to get any financial backing for your future work.

521
00:28:50,680 --> 00:28:53,640
Speaker 1: So uh, I think that's the main way that these

522
00:28:53,640 --> 00:28:58,120
Speaker 1: apps are making money is they're getting bought, which that's

523
00:28:58,120 --> 00:29:00,200
Speaker 1: a risky move. But if you can make a really

524
00:29:00,240 --> 00:29:03,280
Speaker 1: good app, then that's something that you know, it's it's

525
00:29:03,280 --> 00:29:06,480
Speaker 1: something you can count on at least as a potential

526
00:29:06,480 --> 00:29:08,920
Speaker 1: opportunity down the road. It was reading the guy who

527
00:29:08,960 --> 00:29:13,360
Speaker 1: just created Cuddler, Charlie. Yeah, that old Charlie had no idea.

528
00:29:13,480 --> 00:29:15,880
Speaker 1: He was just planning for a soft launch of Cuddler.

529
00:29:15,920 --> 00:29:20,480
Speaker 1: I forget Charlie's last name, sorry Charlie, Yeah, sorry Charlie. Anyway,

530
00:29:20,800 --> 00:29:23,160
Speaker 1: he was just he was unprepared for the sheer amount

531
00:29:23,160 --> 00:29:26,360
Speaker 1: of attention that Cudler received. Yeah. Yeah, it got covered

532
00:29:26,400 --> 00:29:29,480
Speaker 1: by a couple of different UH news outlets like Huffington

533
00:29:29,560 --> 00:29:32,960
Speaker 1: Post and Slate I think wrote about it and uh,

534
00:29:33,080 --> 00:29:36,920
Speaker 1: and that attention meant that there was an explosion in

535
00:29:37,000 --> 00:29:41,360
Speaker 1: downloads and suddenly this app that Charlie probably felt was

536
00:29:41,400 --> 00:29:45,640
Speaker 1: not totally ready yet was being adopted by tons of people.

537
00:29:45,680 --> 00:29:49,640
Speaker 1: And and normally if you're launching, yeah, yeah, it was

538
00:29:49,680 --> 00:29:51,920
Speaker 1: supposed to be a soft launch where he could do

539
00:29:52,000 --> 00:29:56,200
Speaker 1: some testing, get feedback, tweak stuff. But now it goes

540
00:29:56,360 --> 00:29:59,520
Speaker 1: when you get that large adoption, it goes from testing

541
00:29:59,560 --> 00:30:02,960
Speaker 1: phase to now it's a product, and that is a problem.

542
00:30:03,040 --> 00:30:05,560
Speaker 1: Now we should probably mention what Cuddler is. In fact,

543
00:30:05,600 --> 00:30:07,840
Speaker 1: this is a great way of transitioning into just mobile

544
00:30:07,840 --> 00:30:10,880
Speaker 1: apps in general. So Cuddler, which was of course the

545
00:30:10,920 --> 00:30:13,320
Speaker 1: app that that Allison brought to my attention. I did

546
00:30:13,360 --> 00:30:17,640
Speaker 1: not know about this app until you mentioned it to me.

547
00:30:17,880 --> 00:30:20,320
Speaker 1: I had not heard about it. Yeah, my head was

548
00:30:20,400 --> 00:30:23,160
Speaker 1: under a rock apparently when this came out. So Cuddler

549
00:30:23,600 --> 00:30:26,280
Speaker 1: is pretty much what sounds like. It's an app that

550
00:30:26,480 --> 00:30:30,080
Speaker 1: is designed to allow someone who wants to just cuddle

551
00:30:30,520 --> 00:30:33,560
Speaker 1: with somebody else, you know, just find somebody to to

552
00:30:33,720 --> 00:30:39,520
Speaker 1: cuddle with, you know. That's it. Just some personal contact um. Right,

553
00:30:39,520 --> 00:30:43,160
Speaker 1: So it's geolocation base. So you're finally you're finding people

554
00:30:43,160 --> 00:30:45,960
Speaker 1: who are in need of a cuddle nearby you. And

555
00:30:46,080 --> 00:30:48,480
Speaker 1: it's pretty simple set up actually, if in case you

556
00:30:48,520 --> 00:30:50,360
Speaker 1: guys haven't experimented with it, and I know a lot

557
00:30:50,400 --> 00:30:55,280
Speaker 1: of people have, um, but the basic premises, Yeah, you

558
00:30:55,920 --> 00:30:57,920
Speaker 1: say that you're up for a cuddle, you find people

559
00:30:57,920 --> 00:30:59,720
Speaker 1: in your area who are up for it. Once you

560
00:30:59,760 --> 00:31:02,240
Speaker 1: get a match, both of your locations are shown, and

561
00:31:02,240 --> 00:31:05,640
Speaker 1: then you meet. I think you're allowed to send one message, yeah,

562
00:31:06,600 --> 00:31:10,800
Speaker 1: indicating the cuttle time and place. Right. Yeah, this is

563
00:31:11,080 --> 00:31:15,400
Speaker 1: the location thing is definitely an issue, I think because

564
00:31:15,440 --> 00:31:19,640
Speaker 1: it's a The way I've read it described is that

565
00:31:19,720 --> 00:31:22,720
Speaker 1: it shows a map and it plots the location of

566
00:31:22,760 --> 00:31:25,040
Speaker 1: the two parties on the map. Right, So if we

567
00:31:25,040 --> 00:31:26,840
Speaker 1: were looking for a cuddle, I could see you heading

568
00:31:26,880 --> 00:31:29,520
Speaker 1: across the park towards me, and you could see me

569
00:31:29,600 --> 00:31:31,560
Speaker 1: heading for that park bench that we decided we were

570
00:31:31,560 --> 00:31:33,520
Speaker 1: going to cuttle on. Right. It's just it's using the

571
00:31:33,600 --> 00:31:36,800
Speaker 1: GPS on your phone to track where you are. Maybe

572
00:31:36,840 --> 00:31:40,960
Speaker 1: even it could could use a cellular tower location even

573
00:31:41,000 --> 00:31:43,440
Speaker 1: if you don't have GPS turned on, because that can

574
00:31:43,480 --> 00:31:45,920
Speaker 1: at least give you an estimation of where the person is.

575
00:31:46,080 --> 00:31:48,600
Speaker 1: It's a little less accurate than GPS, but still works.

576
00:31:49,000 --> 00:31:52,400
Speaker 1: And so you could actually watch as the two people

577
00:31:52,520 --> 00:31:55,400
Speaker 1: converge by looking at the map and uh to to

578
00:31:55,560 --> 00:32:00,160
Speaker 1: you know, cuttle point zero where you're going to cuddle um.

579
00:32:00,520 --> 00:32:03,240
Speaker 1: And so that also the curious thing about Cuddler was

580
00:32:03,320 --> 00:32:06,480
Speaker 1: that I think that the founder or Charlie, he really

581
00:32:06,520 --> 00:32:09,200
Speaker 1: didn't anticipate, you know, that people would be using it

582
00:32:09,240 --> 00:32:13,000
Speaker 1: as they do Tinder, which is you know, for sex. Yeah. Yeah,

583
00:32:13,040 --> 00:32:15,080
Speaker 1: there are people using it to kind of hook up.

584
00:32:15,120 --> 00:32:17,760
Speaker 1: And a lot of folks have described Cuddler as being

585
00:32:17,800 --> 00:32:20,880
Speaker 1: kind of a creeper app, especially with the the fact

586
00:32:20,920 --> 00:32:23,680
Speaker 1: that it shows the location on the map. Um that

587
00:32:23,760 --> 00:32:27,080
Speaker 1: it could be an app for someone to to creep

588
00:32:27,120 --> 00:32:32,560
Speaker 1: on some boy, stalk someone harassed somebody. Uh. But Charlie

589
00:32:32,640 --> 00:32:34,600
Speaker 1: really seems to have his heart in the right place

590
00:32:34,600 --> 00:32:36,239
Speaker 1: in the sense that he just wanted to build a

591
00:32:36,240 --> 00:32:40,080
Speaker 1: tool that would let people who have a lack of

592
00:32:40,200 --> 00:32:44,440
Speaker 1: social interaction and personal contact meet up with other people

593
00:32:44,480 --> 00:32:47,760
Speaker 1: who are having the same sort of issue. And you

594
00:32:47,800 --> 00:32:51,320
Speaker 1: know personal contact, I mean actual physical contact. Yeah, it's

595
00:32:51,360 --> 00:32:54,160
Speaker 1: it's an important part of human interaction and it and

596
00:32:54,200 --> 00:32:58,040
Speaker 1: it definitely can contribute to our sense of well being,

597
00:32:58,320 --> 00:33:01,760
Speaker 1: our sense of fulfillness. If we go without it for

598
00:33:01,800 --> 00:33:04,840
Speaker 1: a long time, it can lead to depression. I mean,

599
00:33:04,880 --> 00:33:08,360
Speaker 1: they're there are real reasons why people could crave and

600
00:33:08,440 --> 00:33:13,640
Speaker 1: need personal contact, but this particular implementation raises a lot

601
00:33:13,680 --> 00:33:17,280
Speaker 1: of troubling questions. Part of it is just again the

602
00:33:17,800 --> 00:33:21,040
Speaker 1: way that the information is displayed. But another part of

603
00:33:21,040 --> 00:33:23,760
Speaker 1: it is just that if you have if you're catering

604
00:33:23,800 --> 00:33:26,320
Speaker 1: to a population of people who are lacking that kind

605
00:33:26,360 --> 00:33:30,560
Speaker 1: of contact, you're probably going to have at least a

606
00:33:30,600 --> 00:33:35,320
Speaker 1: few cases of negative outcomes, right, I mean you're talking

607
00:33:35,360 --> 00:33:38,720
Speaker 1: about people who maybe in a very either they themselves

608
00:33:38,720 --> 00:33:42,120
Speaker 1: are in a very vulnerable place, which can lead to problems,

609
00:33:42,280 --> 00:33:44,800
Speaker 1: or it could lead to people who are praying upon

610
00:33:44,960 --> 00:33:47,600
Speaker 1: folks who are in a vulnerable place. Right. So there

611
00:33:47,680 --> 00:33:49,720
Speaker 1: is that one account that we both read. The writer

612
00:33:49,880 --> 00:33:55,000
Speaker 1: from gig Um Carmel Yeah, d M mess I believe. Yeah,

613
00:33:55,080 --> 00:33:57,280
Speaker 1: she wrote of her experience. She wrote up an entire

614
00:33:57,400 --> 00:34:00,400
Speaker 1: article which was an entertaining read and also a little

615
00:34:00,480 --> 00:34:04,920
Speaker 1: a little scary. Yeah, she met up with another young lady. Well,

616
00:34:04,920 --> 00:34:06,800
Speaker 1: I don't know, young lady. She met up with another lady,

617
00:34:06,800 --> 00:34:09,760
Speaker 1: and I think she was actually an older woman who

618
00:34:10,160 --> 00:34:13,120
Speaker 1: Carmel called Monica. In the article, she explained that she

619
00:34:13,120 --> 00:34:16,040
Speaker 1: had changed the name to protect Monica's privacy, which I

620
00:34:16,040 --> 00:34:18,359
Speaker 1: think was the right choice to go to go with,

621
00:34:18,480 --> 00:34:22,360
Speaker 1: and that she met at Monica's home and yeah, for

622
00:34:22,400 --> 00:34:25,880
Speaker 1: a cuddle. So the problem there clearly is her not

623
00:34:25,920 --> 00:34:28,000
Speaker 1: being in a public place and going to the person's home.

624
00:34:28,040 --> 00:34:30,359
Speaker 1: And it seems like it worked out okay for this

625
00:34:30,440 --> 00:34:33,120
Speaker 1: writer and good for her for trying and bravery and

626
00:34:33,160 --> 00:34:35,040
Speaker 1: all that stuff, but also a little alarming that she

627
00:34:35,040 --> 00:34:38,160
Speaker 1: went to somebody's house. And as she added that the

628
00:34:38,239 --> 00:34:41,040
Speaker 1: woman Monica showed her a gun at one point and

629
00:34:41,160 --> 00:34:43,400
Speaker 1: showed her how to use it. Yeah, to say that,

630
00:34:43,680 --> 00:34:45,680
Speaker 1: you know, she had worried about safety, and that's when

631
00:34:45,719 --> 00:34:47,560
Speaker 1: she had gone out and got a gun. And this

632
00:34:47,600 --> 00:34:49,440
Speaker 1: was all part of the casual conversation. But at the

633
00:34:49,440 --> 00:34:53,160
Speaker 1: same time, the reporter says it's a little worrisome, and

634
00:34:53,200 --> 00:34:56,840
Speaker 1: that she had contacted Charlie, the creator of Cutler, and

635
00:34:56,880 --> 00:34:59,600
Speaker 1: he said, yeah, that was probably not a good idea.

636
00:34:59,680 --> 00:35:02,080
Speaker 1: I did and intend for that. When I wrote this app,

637
00:35:02,120 --> 00:35:05,279
Speaker 1: I was thinking that people would first meet in a

638
00:35:05,360 --> 00:35:10,640
Speaker 1: safe location, like a public space. But then Carmel's point is, well,

639
00:35:10,680 --> 00:35:14,520
Speaker 1: if you're already having this this problem of a lack

640
00:35:14,560 --> 00:35:18,759
Speaker 1: of physical contact, does it add even more anxiety to

641
00:35:19,280 --> 00:35:22,319
Speaker 1: require it to take place in public where people can

642
00:35:22,360 --> 00:35:25,920
Speaker 1: see you? And that is a little weird. Yeah. I

643
00:35:25,960 --> 00:35:28,680
Speaker 1: I respect the idea behind it, I really do. I

644
00:35:28,760 --> 00:35:31,160
Speaker 1: understand that we all need human interaction and I could

645
00:35:31,200 --> 00:35:34,160
Speaker 1: totally use a hug on most days. But but I

646
00:35:34,160 --> 00:35:37,160
Speaker 1: think we've outlined the problematic aspects of it. Yeah. Now,

647
00:35:37,200 --> 00:35:40,000
Speaker 1: on a on a personal level, I am I'm big

648
00:35:40,040 --> 00:35:43,120
Speaker 1: into hugs. I'm a big I'm a big fan of hugs,

649
00:35:43,120 --> 00:35:46,279
Speaker 1: but only with certain circles of my friends. I have

650
00:35:46,400 --> 00:35:49,480
Speaker 1: never gotten hug just by the way from me, No,

651
00:35:49,600 --> 00:35:53,240
Speaker 1: because I don't hug coworkers. Yeah, thinks like a decent policy.

652
00:35:53,239 --> 00:35:57,200
Speaker 1: There's Yeah, there's there's certain like like worker, Well, I

653
00:35:57,239 --> 00:35:59,640
Speaker 1: have to because Candice. I mean, how can you How

654
00:35:59,680 --> 00:36:02,399
Speaker 1: can you not hug Candice? She's like probably the most

655
00:36:02,480 --> 00:36:06,040
Speaker 1: huggable person on the planet. But um, yeah, I don't.

656
00:36:06,080 --> 00:36:08,319
Speaker 1: I don't tend to hug co workers. I put them

657
00:36:08,320 --> 00:36:10,520
Speaker 1: in a circle where I think these are the types

658
00:36:10,560 --> 00:36:13,279
Speaker 1: of social interactions that are appropriate for people that I

659
00:36:13,320 --> 00:36:15,759
Speaker 1: work with. And if I meet them outside of that

660
00:36:15,920 --> 00:36:19,240
Speaker 1: and we socialize outside of that and they enter another

661
00:36:19,280 --> 00:36:22,440
Speaker 1: circle of friends, like, if that then diagram has overlap,

662
00:36:22,880 --> 00:36:26,799
Speaker 1: that's perfectly acceptable. But otherwise, yeah, I don't. I don't

663
00:36:26,800 --> 00:36:29,760
Speaker 1: think of it as acceptable for co workers in general.

664
00:36:30,080 --> 00:36:33,359
Speaker 1: I'm not against it, but on principle, it's just that's

665
00:36:33,440 --> 00:36:36,839
Speaker 1: kind of how I think. But uh, and strangers don't

666
00:36:36,840 --> 00:36:39,560
Speaker 1: tend to hug them. Uh, there are exceptions. There have

667
00:36:39,560 --> 00:36:41,759
Speaker 1: been some people who have been introduced to me and

668
00:36:41,840 --> 00:36:44,600
Speaker 1: upon introduction, they immediately hugged me. But they did so

669
00:36:44,719 --> 00:36:49,640
Speaker 1: with such uh genuine charm that I was all right

670
00:36:49,680 --> 00:36:52,600
Speaker 1: with it. But it's a really rare thing. In fact,

671
00:36:52,680 --> 00:36:56,160
Speaker 1: I interviewed one of them just the other day protect stuff.

672
00:36:56,280 --> 00:36:58,480
Speaker 1: So do you want to hear my idea for an app? Yes,

673
00:36:59,400 --> 00:37:02,640
Speaker 1: I think that they should be a backscratcher app. You know,

674
00:37:02,760 --> 00:37:06,239
Speaker 1: I can totally agree to that. So a similar thing,

675
00:37:06,360 --> 00:37:07,839
Speaker 1: but you have to be I think you have to

676
00:37:07,920 --> 00:37:10,279
Speaker 1: make the premise or the area of to put the

677
00:37:10,320 --> 00:37:12,719
Speaker 1: call at to you much smaller. You don't want to

678
00:37:12,760 --> 00:37:15,600
Speaker 1: cross town to find finally get that person toscribe because

679
00:37:15,600 --> 00:37:18,200
Speaker 1: by then the itch is gone, right, the itch is gone,

680
00:37:18,239 --> 00:37:20,640
Speaker 1: but sometimes you just can't reach it. It's just right

681
00:37:20,680 --> 00:37:22,680
Speaker 1: there between the shoulder blades. And you know, the more

682
00:37:22,719 --> 00:37:24,640
Speaker 1: we talk about, the more it's going to actually start

683
00:37:24,640 --> 00:37:26,200
Speaker 1: to creep into my mind. So I'm going to change

684
00:37:26,239 --> 00:37:29,000
Speaker 1: the subject. But that's a great idea. Yeah, it's much

685
00:37:29,040 --> 00:37:31,480
Speaker 1: better than a phone that has a backscratcher that swings

686
00:37:31,520 --> 00:37:35,400
Speaker 1: out from it, because that would just bulk. So you

687
00:37:35,440 --> 00:37:39,280
Speaker 1: mentioned Tender, which is a great app to to refer

688
00:37:39,360 --> 00:37:41,760
Speaker 1: to as well, because it's so popular that one debuted

689
00:37:41,760 --> 00:37:43,560
Speaker 1: back in two thousand twelve, and you mentioned that it's

690
00:37:43,600 --> 00:37:47,400
Speaker 1: owned by match dot com. Uh. Now, the founders like

691
00:37:47,560 --> 00:37:51,720
Speaker 1: to talk about it as being a social discovery tool

692
00:37:52,160 --> 00:37:55,160
Speaker 1: that you're you use it to find people to hang

693
00:37:55,200 --> 00:37:57,760
Speaker 1: out with. And the way tender works is it pulls

694
00:37:58,200 --> 00:38:01,480
Speaker 1: photos from Facebook profile. Else then you look at the

695
00:38:01,520 --> 00:38:04,480
Speaker 1: profile and you can swipe left, left to dismiss it

696
00:38:04,640 --> 00:38:06,799
Speaker 1: or right if you're interested and you want to make

697
00:38:06,840 --> 00:38:10,839
Speaker 1: contact with this person. Um. But while they talk about

698
00:38:10,840 --> 00:38:15,080
Speaker 1: it as a social discovery tool, that's not necessarily it's

699
00:38:15,080 --> 00:38:17,319
Speaker 1: all about hooking up. It's about you know, it's the

700
00:38:17,320 --> 00:38:20,160
Speaker 1: hot or not approach. It's you know, this person is

701
00:38:20,520 --> 00:38:24,520
Speaker 1: this person I find attractive this one I don't find attractive. No, no, no, yes, no,

702
00:38:24,520 --> 00:38:28,120
Speaker 1: no no. And um, you know the fact that it

703
00:38:28,200 --> 00:38:32,080
Speaker 1: has this kind of swipe to dismiss or swipe to accept,

704
00:38:33,000 --> 00:38:36,479
Speaker 1: really I think drives that home. It actually is, making

705
00:38:36,520 --> 00:38:39,520
Speaker 1: it a physical activity that you associate with either accepting

706
00:38:39,640 --> 00:38:44,560
Speaker 1: or rejecting. So I think there's something interesting psychologically there.

707
00:38:44,760 --> 00:38:48,719
Speaker 1: I'm not a psychologist, so I certainly can't draw any conclusions,

708
00:38:48,760 --> 00:38:50,880
Speaker 1: but I would love to hear a study about this

709
00:38:51,000 --> 00:38:52,960
Speaker 1: kind of behavior and what it sort of feeds into

710
00:38:53,040 --> 00:38:56,080
Speaker 1: because one of the things one of the criticisms I've

711
00:38:56,080 --> 00:38:59,320
Speaker 1: read about online dating in general is that it promotes

712
00:38:59,400 --> 00:39:03,280
Speaker 1: this kind of shopping behavior. Absolutely, so the idea of

713
00:39:03,280 --> 00:39:06,080
Speaker 1: of your You're like, it's like you're going through a catalog,

714
00:39:06,760 --> 00:39:10,960
Speaker 1: and it's not it's not really promoting an interaction so

715
00:39:11,040 --> 00:39:15,840
Speaker 1: much as this this very rapid except reject kind of approach,

716
00:39:15,880 --> 00:39:18,319
Speaker 1: and Tender sort of just exemplifies that because of the

717
00:39:18,320 --> 00:39:21,080
Speaker 1: way the app is built, right, Well, so I wonder

718
00:39:21,320 --> 00:39:24,120
Speaker 1: what the outcomes ultimately would be from that, Right, So

719
00:39:24,239 --> 00:39:26,719
Speaker 1: you hook up with somebody on Tender and then you know,

720
00:39:27,400 --> 00:39:29,080
Speaker 1: are you If you're just looking for a hook up,

721
00:39:29,120 --> 00:39:32,359
Speaker 1: that's fun. But if you're looking to date somebody, I mean,

722
00:39:32,440 --> 00:39:34,400
Speaker 1: what are the outcomes? You know, do you wind up

723
00:39:34,480 --> 00:39:38,640
Speaker 1: dating having successful like partnerships with people are not so much. Yeah,

724
00:39:38,680 --> 00:39:41,600
Speaker 1: I don't know. I don't know what basis is that

725
00:39:41,680 --> 00:39:44,960
Speaker 1: split second decision in which you're swiping left or swiping right? Like,

726
00:39:45,160 --> 00:39:48,600
Speaker 1: how true is that instinct? Well, and there are people

727
00:39:48,600 --> 00:39:52,000
Speaker 1: who have said that perhaps the activity of using Tinder

728
00:39:52,040 --> 00:39:57,600
Speaker 1: itself is more exciting than any actual interaction that follows,

729
00:39:58,000 --> 00:40:01,879
Speaker 1: that that the thrill of ender is just the use

730
00:40:01,960 --> 00:40:05,640
Speaker 1: of Tinder, not not not any kind of actual encounter

731
00:40:05,760 --> 00:40:09,799
Speaker 1: that might follow, but just the the feeling of rejecting

732
00:40:10,360 --> 00:40:13,960
Speaker 1: or saying this person is attractive to me itself is

733
00:40:14,360 --> 00:40:16,560
Speaker 1: social activity. It's one that you can do with your friends.

734
00:40:16,560 --> 00:40:18,960
Speaker 1: I was reading an article about in the Wall Street

735
00:40:19,000 --> 00:40:22,359
Speaker 1: Journal about some football players, professional football players I think

736
00:40:22,360 --> 00:40:24,720
Speaker 1: out of New York, maybe the Jets or the Giants,

737
00:40:24,840 --> 00:40:28,640
Speaker 1: and they were essentially using Tinder to um find people

738
00:40:28,680 --> 00:40:32,239
Speaker 1: without advertising that they were professional football players. And so

739
00:40:32,360 --> 00:40:35,759
Speaker 1: you know they're sitting around though swipe left, yeah, swipe right,

740
00:40:36,120 --> 00:40:38,160
Speaker 1: and they were you know, meeting up with some of

741
00:40:38,160 --> 00:40:40,680
Speaker 1: the people they found on Tinder, and they found it

742
00:40:41,120 --> 00:40:43,439
Speaker 1: useful for when they were they were away from home

743
00:40:43,520 --> 00:40:45,640
Speaker 1: at training camp I think, maybe an upstate New York

744
00:40:46,200 --> 00:40:48,520
Speaker 1: and also to kind of give them a little bit

745
00:40:48,520 --> 00:40:51,440
Speaker 1: of a layer of anonymity until they were ready to

746
00:40:51,480 --> 00:40:53,400
Speaker 1: say like, hey, you know, I do this for a living.

747
00:40:53,840 --> 00:40:57,040
Speaker 1: And so in that case, they were actually looking at

748
00:40:57,080 --> 00:41:01,000
Speaker 1: to strip away some of the identifying information that would

749
00:41:01,000 --> 00:41:05,600
Speaker 1: otherwise bias someone towards them, like, you know, I want

750
00:41:05,640 --> 00:41:07,640
Speaker 1: to see if this person would be interested in meeting

751
00:41:07,719 --> 00:41:10,319
Speaker 1: up with me and or at least carrying on a

752
00:41:10,320 --> 00:41:13,400
Speaker 1: conversation with me before they know what I do for

753
00:41:13,440 --> 00:41:15,120
Speaker 1: a living, because if they know what I do for

754
00:41:15,160 --> 00:41:17,480
Speaker 1: a living, I'll never be sure if that's the reason

755
00:41:17,560 --> 00:41:20,800
Speaker 1: why they pursued me. Yeah, I think that was the idea. Interesting.

756
00:41:20,880 --> 00:41:23,520
Speaker 1: And then for those uh you know, Tinder is not

757
00:41:24,200 --> 00:41:26,600
Speaker 1: itself a new idea. There was actually an app that

758
00:41:26,840 --> 00:41:31,040
Speaker 1: pre uh that predated Tinder, uh called Grinder that was

759
00:41:31,080 --> 00:41:35,319
Speaker 1: specifically for gay and bisexual and by curious men to

760
00:41:35,800 --> 00:41:39,080
Speaker 1: find one another for essentially the purpose of hooking up. Yeah,

761
00:41:39,080 --> 00:41:40,920
Speaker 1: it was the first one, I believe. Yeah, so that

762
00:41:41,000 --> 00:41:43,640
Speaker 1: was that was something that led to the development of

763
00:41:43,680 --> 00:41:45,920
Speaker 1: other apps, So you can kind of see that as

764
00:41:45,960 --> 00:41:48,520
Speaker 1: being the genesis of the same sort of idea that

765
00:41:48,560 --> 00:41:51,240
Speaker 1: we've seen with Tinder and to maybe some extent, Cuddler,

766
00:41:51,880 --> 00:41:55,760
Speaker 1: even though again Cudler is mostly it's it's intended for

767
00:41:56,200 --> 00:42:00,520
Speaker 1: non sexual cuddling, or at least that's you know, that

768
00:42:00,640 --> 00:42:03,640
Speaker 1: seems to be the intention. It's hard for me to

769
00:42:03,680 --> 00:42:06,880
Speaker 1: ever say that what was intended without speaking directly to

770
00:42:06,920 --> 00:42:09,640
Speaker 1: the person who created these acts, but just based upon

771
00:42:09,680 --> 00:42:12,439
Speaker 1: what I've read, Yeah, so I guess I'm wondering if

772
00:42:12,480 --> 00:42:14,840
Speaker 1: things like Tinder and Grinder and all these things that

773
00:42:14,880 --> 00:42:17,040
Speaker 1: are sort of more geared at hooking up, if that

774
00:42:17,120 --> 00:42:20,359
Speaker 1: makes people change your behavior on online dating sites, Right,

775
00:42:20,520 --> 00:42:23,960
Speaker 1: so you can kind of segment out your behavior. Okay,

776
00:42:23,960 --> 00:42:25,640
Speaker 1: this is what I'm gonna use for hooking up, and

777
00:42:25,640 --> 00:42:27,200
Speaker 1: this is what I'm going to use to find my

778
00:42:27,480 --> 00:42:31,359
Speaker 1: lifelong partner. So essentially, the difference between like a real

779
00:42:31,400 --> 00:42:35,320
Speaker 1: life situation where you might go to a specific club

780
00:42:35,520 --> 00:42:38,560
Speaker 1: or bar in order for you to find someone to

781
00:42:38,640 --> 00:42:41,520
Speaker 1: hook up with, versus you know, you're looking seriously for

782
00:42:41,560 --> 00:42:44,919
Speaker 1: that person who's going to be taking an important part

783
00:42:45,000 --> 00:42:48,319
Speaker 1: of your life like from that point forward. Absolutely, I

784
00:42:48,360 --> 00:42:50,719
Speaker 1: expect that that actually is the case. I mean, I

785
00:42:50,719 --> 00:42:53,720
Speaker 1: imagine that that is true. UM. I don't know which

786
00:42:54,000 --> 00:42:56,319
Speaker 1: online dating sites are the most popular for the people

787
00:42:56,360 --> 00:43:00,440
Speaker 1: who tend to use the apps like Tinder. There are

788
00:43:00,440 --> 00:43:03,080
Speaker 1: other apps that are more meant to try and bring

789
00:43:03,120 --> 00:43:07,160
Speaker 1: people together in a social setting without the pressure of

790
00:43:07,200 --> 00:43:10,320
Speaker 1: this one on one meeting. One of them is called Grouper.

791
00:43:10,520 --> 00:43:12,880
Speaker 1: Group sounds really fun. I have to say Grouper is

792
00:43:12,960 --> 00:43:15,399
Speaker 1: kind of a neat idea, and that you end up

793
00:43:16,000 --> 00:43:19,000
Speaker 1: creating a group of three and usually, at least the

794
00:43:19,040 --> 00:43:21,560
Speaker 1: way I've seen it portrayed, it's three people of the

795
00:43:21,600 --> 00:43:25,799
Speaker 1: same gender who are going after a chance to meet

796
00:43:25,880 --> 00:43:29,200
Speaker 1: three other people of whichever gender the three prefer. So

797
00:43:29,400 --> 00:43:31,319
Speaker 1: you know, it doesn't have to be opposite sex, it

798
00:43:31,320 --> 00:43:33,799
Speaker 1: could be same sex. But the idea being that you

799
00:43:33,840 --> 00:43:37,680
Speaker 1: have these three people who have paid into the service

800
00:43:38,200 --> 00:43:40,600
Speaker 1: to be matched up with three other people that the

801
00:43:40,640 --> 00:43:45,120
Speaker 1: service has decided appear to be uh compatible for an

802
00:43:45,360 --> 00:43:51,080
Speaker 1: enjoyable evening. Yet and and the app also includes uh

803
00:43:51,160 --> 00:43:53,320
Speaker 1: it pays for the first round of drinks for everybody,

804
00:43:53,320 --> 00:43:56,040
Speaker 1: so everyone gets one free drink. Yeah, so you get

805
00:43:56,080 --> 00:43:59,280
Speaker 1: a group of six people together to hang out, and

806
00:43:59,440 --> 00:44:03,320
Speaker 1: it takes pressure off of the one on one meeting,

807
00:44:03,320 --> 00:44:08,200
Speaker 1: although it could lead to other really socially awkward situations

808
00:44:08,200 --> 00:44:11,080
Speaker 1: where maybe two people have interest in one person or

809
00:44:11,320 --> 00:44:14,359
Speaker 1: let's get out of here man, yeah, which right? Or

810
00:44:14,480 --> 00:44:18,040
Speaker 1: yeah or you get it, where like, you know, one

811
00:44:18,080 --> 00:44:20,880
Speaker 1: person gets left out because two of the people are

812
00:44:20,920 --> 00:44:24,120
Speaker 1: interested in you know, and and in member number one,

813
00:44:24,239 --> 00:44:26,600
Speaker 1: one person's interested in member number two. Remember number three

814
00:44:26,600 --> 00:44:28,839
Speaker 1: is out. Meanwhile, remember number one is like, well great,

815
00:44:28,920 --> 00:44:31,360
Speaker 1: now I've got these two people after me. Um. So

816
00:44:31,400 --> 00:44:33,160
Speaker 1: there are a lot of different things that could come up,

817
00:44:33,360 --> 00:44:35,319
Speaker 1: and it doesn't necessarily have to lead to that. It

818
00:44:35,360 --> 00:44:37,919
Speaker 1: could just be oh, that was a fun evening out,

819
00:44:37,960 --> 00:44:39,600
Speaker 1: and now I've got a new group of friends and

820
00:44:39,640 --> 00:44:41,440
Speaker 1: I can hang out with them and do stuff. So,

821
00:44:41,480 --> 00:44:43,320
Speaker 1: you know, when you I could see for this is

822
00:44:43,560 --> 00:44:47,640
Speaker 1: uh so I am not available, but one of my

823
00:44:47,800 --> 00:44:50,560
Speaker 1: friends is available. And I would totally be a wing woman.

824
00:44:50,600 --> 00:44:52,520
Speaker 1: And I think that is a position you can take

825
00:44:52,600 --> 00:44:54,960
Speaker 1: up when you do these group of things. You can

826
00:44:55,000 --> 00:44:57,520
Speaker 1: be a wing woman or a wingman. Sure, I actually

827
00:44:57,520 --> 00:44:59,440
Speaker 1: like to think of myself as a rather good wing woman.

828
00:44:59,680 --> 00:45:05,239
Speaker 1: I'm terrible. Yeah, I'm a great talker, but I'm also oblivious,

829
00:45:05,360 --> 00:45:09,839
Speaker 1: so I'm I'm just not in that headspace right So

830
00:45:10,160 --> 00:45:12,160
Speaker 1: for me, I would be terrible. I would be trying

831
00:45:12,200 --> 00:45:13,799
Speaker 1: to think of the next funny thing to say just

832
00:45:13,840 --> 00:45:17,120
Speaker 1: to make everybody laugh. And I meanwhile, whoever I'm being

833
00:45:17,120 --> 00:45:19,719
Speaker 1: wingman for is just thinking, just shut up, Jonathan, just

834
00:45:19,719 --> 00:45:23,279
Speaker 1: just shut up for a minute. Um. What's cool and

835
00:45:23,440 --> 00:45:25,759
Speaker 1: maybe not cool about Grouper at the same time is

836
00:45:26,680 --> 00:45:28,600
Speaker 1: you know, how does it come up with how to

837
00:45:28,640 --> 00:45:31,600
Speaker 1: match you up with another group of people, and it

838
00:45:31,600 --> 00:45:36,040
Speaker 1: it minds your Facebook information. Now, keep in mind you

839
00:45:36,080 --> 00:45:39,520
Speaker 1: have to, uh, you have to authorize the app to

840
00:45:39,719 --> 00:45:43,360
Speaker 1: be able to mind that information. And you can always

841
00:45:43,400 --> 00:45:45,160
Speaker 1: keep stuff private. I mean a lot of this ends

842
00:45:45,200 --> 00:45:48,239
Speaker 1: up being information that's publicly available because you have put

843
00:45:48,280 --> 00:45:51,040
Speaker 1: it up on Facebook and you didn't set the privacy

844
00:45:51,040 --> 00:45:54,320
Speaker 1: setting so that it couldn't be seen by other entities.

845
00:45:55,239 --> 00:45:57,360
Speaker 1: But it does mean that it's going to be looking

846
00:45:57,400 --> 00:45:59,759
Speaker 1: at everything from your age. It's also gonna look at

847
00:45:59,760 --> 00:46:03,319
Speaker 1: your ends list because it doesn't want to match up

848
00:46:03,640 --> 00:46:07,160
Speaker 1: three people with folks that they already know. That's not

849
00:46:07,239 --> 00:46:09,719
Speaker 1: the perfect problem in a small town setting, I would think. Yeah,

850
00:46:09,760 --> 00:46:12,560
Speaker 1: I mean it's it's even a problem just for neighborhoods, right,

851
00:46:12,600 --> 00:46:16,960
Speaker 1: I mean, Atlanta is in most cities are collections of neighborhoods,

852
00:46:17,360 --> 00:46:20,880
Speaker 1: and you have people who tend to be very um

853
00:46:20,920 --> 00:46:25,040
Speaker 1: like like they'll they'll range outward from their neighborhood, but

854
00:46:25,120 --> 00:46:28,799
Speaker 1: it's it gets increasingly smaller, like the they'll they'll spend

855
00:46:28,920 --> 00:46:31,239
Speaker 1: less time the further out right, unless they happen to

856
00:46:31,280 --> 00:46:32,840
Speaker 1: live in a part of town that they just considered

857
00:46:32,840 --> 00:46:34,600
Speaker 1: to be dead and they need to go to a

858
00:46:34,600 --> 00:46:38,279
Speaker 1: different part of town for stuff that happens. But I

859
00:46:38,320 --> 00:46:40,480
Speaker 1: can definitely see that becoming a challenge, especially if you're

860
00:46:40,480 --> 00:46:44,640
Speaker 1: a really social person, particularly if you're really social online,

861
00:46:44,960 --> 00:46:49,120
Speaker 1: because I know people who accept friend requests online. Yeah,

862
00:46:49,239 --> 00:46:51,680
Speaker 1: they'll have hundreds of them, and most studies say that

863
00:46:51,880 --> 00:46:55,279
Speaker 1: we're only capable of supporting about a hundred fifty relationships.

864
00:46:55,440 --> 00:46:57,600
Speaker 1: Oh did you just see that great video we did

865
00:46:57,600 --> 00:46:59,759
Speaker 1: on that? I know that Ben did a video on

866
00:47:00,080 --> 00:47:01,680
Speaker 1: sure it's on brain stuff. I was good. I thought

867
00:47:01,680 --> 00:47:05,839
Speaker 1: it was super interesting. It's a really good video, right, yeah, yeah,

868
00:47:05,880 --> 00:47:07,880
Speaker 1: And I had heard about that before we before he

869
00:47:07,920 --> 00:47:09,359
Speaker 1: had done the video, but he did a great job

870
00:47:09,400 --> 00:47:12,200
Speaker 1: explaining it. So if you keep that in mind, you

871
00:47:12,280 --> 00:47:14,920
Speaker 1: might be someone who accepts lots of friend requests anyway.

872
00:47:14,960 --> 00:47:18,200
Speaker 1: And it may be that you know you've got hundreds

873
00:47:18,239 --> 00:47:21,520
Speaker 1: of friends on Facebook. That's gonna narrow down your options

874
00:47:21,560 --> 00:47:24,880
Speaker 1: when you use something like Grouper that's specifically looking to

875
00:47:24,920 --> 00:47:27,239
Speaker 1: try and match you up with people you don't know.

876
00:47:27,760 --> 00:47:30,480
Speaker 1: The one cool thing I will say about Grouper is um, actually,

877
00:47:30,480 --> 00:47:33,400
Speaker 1: I think it's pretty cool in general. But the one

878
00:47:33,440 --> 00:47:35,520
Speaker 1: thing I would say about Grouper though, is that I

879
00:47:35,560 --> 00:47:37,440
Speaker 1: think it's in line with a lot of with how

880
00:47:37,480 --> 00:47:39,880
Speaker 1: people go out these days, especially the young people. If

881
00:47:39,880 --> 00:47:42,000
Speaker 1: you got a big group and so it's got that

882
00:47:42,080 --> 00:47:44,160
Speaker 1: going on for it's right in line with that. Yeah.

883
00:47:44,200 --> 00:47:47,879
Speaker 1: And I think again it all depends upon the expectations

884
00:47:47,920 --> 00:47:50,840
Speaker 1: you bring, right, So if you bring the expectation of

885
00:47:50,920 --> 00:47:52,920
Speaker 1: I just want to go out and meet some folks,

886
00:47:53,400 --> 00:47:56,320
Speaker 1: get to know them, have some fun, and then maybe

887
00:47:56,920 --> 00:47:59,600
Speaker 1: we find out that some of us click and that's awesome.

888
00:47:59,640 --> 00:48:01,319
Speaker 1: And may be it doesn't happen, but as long as

889
00:48:01,360 --> 00:48:04,160
Speaker 1: we're having a good time and enjoying ourselves, that's cool too.

890
00:48:04,400 --> 00:48:06,680
Speaker 1: Like I think, if you go in with the right expectations.

891
00:48:06,680 --> 00:48:09,480
Speaker 1: Then you're you're much less likely to you know, pen

892
00:48:09,600 --> 00:48:12,000
Speaker 1: all your hopes on something that may or may not happen,

893
00:48:12,120 --> 00:48:15,359
Speaker 1: and thus avoid a crash if it doesn't turn out

894
00:48:15,360 --> 00:48:18,160
Speaker 1: the way you had hoped. But that's easier said than done.

895
00:48:18,200 --> 00:48:20,399
Speaker 1: That's said by a guy who's been married seventeen years.

896
00:48:20,400 --> 00:48:24,359
Speaker 1: So I don't you know, I don't. It's no, I'm not.

897
00:48:24,960 --> 00:48:28,520
Speaker 1: Then there's a how about we, which is an interesting

898
00:48:28,560 --> 00:48:32,080
Speaker 1: app It lets people propose a specific date experience. Now

899
00:48:32,080 --> 00:48:35,720
Speaker 1: this can actually be between existing couples, where it's really

900
00:48:35,760 --> 00:48:39,040
Speaker 1: just you could send a message to your your partner

901
00:48:39,080 --> 00:48:42,000
Speaker 1: and say, how about we, you know, go out for

902
00:48:42,040 --> 00:48:45,319
Speaker 1: sushi tonight. That could be your thing, Or it could

903
00:48:45,320 --> 00:48:47,120
Speaker 1: be a way of trying to look for a date

904
00:48:47,440 --> 00:48:50,080
Speaker 1: where you describe a date that you think would be fun.

905
00:48:50,520 --> 00:48:54,520
Speaker 1: You say, how about we go to karaoke, you know

906
00:48:54,680 --> 00:49:00,480
Speaker 1: and seeing John Cougar Mellencamp song really loudly, and and

907
00:49:00,560 --> 00:49:02,680
Speaker 1: so you say that, and then you wait to see

908
00:49:02,680 --> 00:49:05,759
Speaker 1: if anyone responds, and if they do, and it's and

909
00:49:05,800 --> 00:49:07,960
Speaker 1: it's truly a date experience that you think would be

910
00:49:08,000 --> 00:49:10,000
Speaker 1: fun and they also think it would be fun. The

911
00:49:10,040 --> 00:49:12,680
Speaker 1: idea there is that you would be very compatible to

912
00:49:12,760 --> 00:49:16,759
Speaker 1: have a good time. Maybe nothing romantic comes out of it,

913
00:49:16,800 --> 00:49:18,880
Speaker 1: but you would be able to have a fun interaction

914
00:49:18,960 --> 00:49:22,759
Speaker 1: with another human being doing something you both enjoy. So, uh,

915
00:49:23,080 --> 00:49:25,840
Speaker 1: from why I understand the people who use how about

916
00:49:25,840 --> 00:49:28,560
Speaker 1: we tend to be in an older age bracket than

917
00:49:28,600 --> 00:49:31,279
Speaker 1: the folks who use Tender, but they're using it for

918
00:49:31,680 --> 00:49:34,520
Speaker 1: you know, kind of similar purpose, not necessarily to hook up,

919
00:49:34,560 --> 00:49:37,000
Speaker 1: but to have these kind of interactions with people that

920
00:49:37,040 --> 00:49:40,680
Speaker 1: they haven't met before. So this was interesting. There's this

921
00:49:40,719 --> 00:49:42,640
Speaker 1: one called Siren then I came across when I was

922
00:49:42,680 --> 00:49:45,640
Speaker 1: researching this podcast, and this one is a two thousand

923
00:49:45,719 --> 00:49:48,920
Speaker 1: fourteen invitation only entrant in the app world, in the

924
00:49:49,320 --> 00:49:51,960
Speaker 1: dating app world, and the spin here is that the

925
00:49:52,040 --> 00:49:55,800
Speaker 1: women control their visibility. Right. So the founders is, um,

926
00:49:55,880 --> 00:49:59,200
Speaker 1: she's actually very interesting, Susie Lee. She's an artist and

927
00:49:59,280 --> 00:50:01,879
Speaker 1: she's also the sa EO, and she wanted to give

928
00:50:01,960 --> 00:50:05,000
Speaker 1: women the power back in these online dating sites and

929
00:50:05,080 --> 00:50:09,480
Speaker 1: dating apps, and so instead of profiles or swiping left

930
00:50:09,560 --> 00:50:11,600
Speaker 1: or right right. So we've kind of already gone through

931
00:50:11,640 --> 00:50:14,560
Speaker 1: like what maybe problematic with the profile and talked about

932
00:50:14,560 --> 00:50:17,320
Speaker 1: the swiping business what you do here is you respond

933
00:50:17,320 --> 00:50:20,000
Speaker 1: to these daily q and a's posted by a sponsor

934
00:50:20,280 --> 00:50:22,560
Speaker 1: and there I think the sponsors are cultural types like

935
00:50:22,640 --> 00:50:26,640
Speaker 1: museums or you know, music organizations stuff like that, so

936
00:50:26,719 --> 00:50:29,520
Speaker 1: not like fast food restaurants or something. Right, but one

937
00:50:29,520 --> 00:50:31,719
Speaker 1: of the sample questions, one of the sample q and

938
00:50:31,760 --> 00:50:34,719
Speaker 1: as they said, was that describe your favorite sandwich from

939
00:50:34,760 --> 00:50:37,760
Speaker 1: top to bottom. Right, so you see this one pop

940
00:50:37,840 --> 00:50:40,440
Speaker 1: up on your siren app and you describe it. I

941
00:50:40,440 --> 00:50:43,120
Speaker 1: think you can also post video and then you can

942
00:50:43,120 --> 00:50:46,440
Speaker 1: make it visible. And people, I mean, people are pretty witty,

943
00:50:46,480 --> 00:50:49,080
Speaker 1: people are funny, and for me as an editor, one

944
00:50:49,080 --> 00:50:51,560
Speaker 1: of the things that I find really attractive about people

945
00:50:51,640 --> 00:50:55,680
Speaker 1: is their their way with words. So I think reading something,

946
00:50:55,760 --> 00:50:58,680
Speaker 1: it's it just gets that more of somebody's personality, like

947
00:50:58,719 --> 00:51:01,680
Speaker 1: that they're able to show right there. Yeah, yeah, the

948
00:51:01,680 --> 00:51:04,319
Speaker 1: the way that someone answers a question can tell you

949
00:51:04,360 --> 00:51:08,160
Speaker 1: a lot about their general thinking process, whether or not

950
00:51:08,200 --> 00:51:11,719
Speaker 1: you find that to be an attractive feature or not.

951
00:51:12,320 --> 00:51:15,160
Speaker 1: And yeah, I could certainly see that as being a

952
00:51:15,200 --> 00:51:17,960
Speaker 1: really cool way of deciding whether or not to try

953
00:51:18,120 --> 00:51:22,560
Speaker 1: and take that further with an actual interaction. Right. So,

954
00:51:22,560 --> 00:51:24,840
Speaker 1: so you like the way that this person described their

955
00:51:24,880 --> 00:51:27,600
Speaker 1: favorite sandwich, and what do you know, The next question

956
00:51:27,760 --> 00:51:29,920
Speaker 1: is who's your favorite beatle? The next day and the

957
00:51:30,040 --> 00:51:32,520
Speaker 1: same person says, like, you know, makes you laugh because

958
00:51:32,520 --> 00:51:35,280
Speaker 1: it's John Lennon and your favorite beatle is Shohn Lennon.

959
00:51:35,280 --> 00:51:38,440
Speaker 1: You've got to meet this person. So what you do

960
00:51:38,480 --> 00:51:41,280
Speaker 1: then is you'd make your information visible to the man.

961
00:51:41,440 --> 00:51:44,279
Speaker 1: And so that's that's pretty interesting. Again, it's it's kind

962
00:51:44,280 --> 00:51:47,279
Speaker 1: of a feminist dating app in that, um, you the

963
00:51:47,320 --> 00:51:50,840
Speaker 1: woman is unlocking her data for the man at her choice.

964
00:51:51,120 --> 00:51:53,560
Speaker 1: That's the big premise here. And I know people, some

965
00:51:53,600 --> 00:51:55,560
Speaker 1: people are gonna be unhappy and why do you need that?

966
00:51:55,680 --> 00:51:59,160
Speaker 1: But she thought there was a need for it, and

967
00:51:59,200 --> 00:52:01,799
Speaker 1: I think it's pretty no. I I do too, I think,

968
00:52:02,160 --> 00:52:05,920
Speaker 1: you know, considering that we're talking about something that in

969
00:52:06,160 --> 00:52:10,640
Speaker 1: our culture, and in the United States in particular, uh,

970
00:52:10,719 --> 00:52:15,000
Speaker 1: it tends to be the cultural idea tends to be

971
00:52:15,080 --> 00:52:17,920
Speaker 1: that the man is in pursuit of the woman and

972
00:52:18,000 --> 00:52:20,440
Speaker 1: that women are things to be pursued. And that's the

973
00:52:20,480 --> 00:52:25,440
Speaker 1: problem there. It's viewing women as things as exactly exactly.

974
00:52:25,520 --> 00:52:28,520
Speaker 1: So this is an approach that to try and kind

975
00:52:28,520 --> 00:52:32,200
Speaker 1: of counteract that in a way and Uh, and you know,

976
00:52:32,280 --> 00:52:34,840
Speaker 1: it's it's a problematic thing because we're talking about a

977
00:52:35,000 --> 00:52:39,440
Speaker 1: cultural issue. It's deep seated, and it's something that changes

978
00:52:39,560 --> 00:52:42,759
Speaker 1: very gradually with time and only with effort. Right, It's

979
00:52:42,760 --> 00:52:47,280
Speaker 1: not something that's gonna spontaneously change. So I like seeing

980
00:52:47,320 --> 00:52:50,400
Speaker 1: this kind of creative approach because I do want to

981
00:52:50,440 --> 00:52:54,560
Speaker 1: see that model eventually change. I would like to see

982
00:52:54,680 --> 00:52:58,920
Speaker 1: there to be a little more equality here between the genders. Um. So,

983
00:52:59,360 --> 00:53:01,399
Speaker 1: once you just side you like somebody, and if maybe

984
00:53:01,400 --> 00:53:03,520
Speaker 1: you're feeling like you want to meet somebody, you can

985
00:53:03,520 --> 00:53:06,400
Speaker 1: put out what's called a siren call, and that's basically

986
00:53:06,440 --> 00:53:08,880
Speaker 1: like you're interacting with people to see if anybody's up

987
00:53:08,920 --> 00:53:11,200
Speaker 1: for something. I love that it's a siren call. Yeah,

988
00:53:11,239 --> 00:53:13,759
Speaker 1: it's kind of awesome, right, yeah, because that doesn't have

989
00:53:13,800 --> 00:53:17,560
Speaker 1: any kind of uh, you know, sinister overtones, do it

990
00:53:17,640 --> 00:53:19,880
Speaker 1: at all? For those of us who enjoy things like

991
00:53:19,920 --> 00:53:24,000
Speaker 1: the Odyssey? But no, it is pretty funny. Uh. We

992
00:53:24,080 --> 00:53:28,320
Speaker 1: can't have this discussion without bringing to light an app

993
00:53:28,400 --> 00:53:32,359
Speaker 1: that was truly problematic, one that came up in two

994
00:53:32,400 --> 00:53:36,400
Speaker 1: thousand and twelve called Girls Around Me. Now, this app

995
00:53:36,640 --> 00:53:39,399
Speaker 1: was one that that Allison, you had not heard about right,

996
00:53:39,600 --> 00:53:41,799
Speaker 1: I don't think so. I heard about it because I

997
00:53:41,840 --> 00:53:45,080
Speaker 1: was very much following all the tech news at the time,

998
00:53:45,719 --> 00:53:48,439
Speaker 1: and it was one that I immediately found to be troubling. Now,

999
00:53:48,680 --> 00:53:51,919
Speaker 1: it was troubling in a very kind of, hey, it's

1000
00:53:51,960 --> 00:53:55,600
Speaker 1: not our fault kind of way, which makes it doubly

1001
00:53:55,680 --> 00:53:59,920
Speaker 1: troubling to me. The app pulled information from four Square

1002
00:54:00,080 --> 00:54:05,680
Speaker 1: and from Facebook. Now again, to use these things, you uh,

1003
00:54:05,880 --> 00:54:08,520
Speaker 1: you know, you create your profiles and you are actively

1004
00:54:08,600 --> 00:54:11,279
Speaker 1: sharing things, so that that seems to be the justification

1005
00:54:11,320 --> 00:54:13,359
Speaker 1: of well, it's okay for us to make this app then,

1006
00:54:13,400 --> 00:54:17,600
Speaker 1: because people are active, Yeah, they're they're the ones presenting

1007
00:54:17,600 --> 00:54:21,640
Speaker 1: this information. We're just aggregating it and displaying it um.

1008
00:54:21,640 --> 00:54:24,680
Speaker 1: But part of the problem is, I think not everyone

1009
00:54:24,760 --> 00:54:28,000
Speaker 1: is aware of exactly the implications of sharing their data.

1010
00:54:28,040 --> 00:54:31,399
Speaker 1: They're thinking, oh, I'm I'm checking into this restaurant because

1011
00:54:31,440 --> 00:54:33,719
Speaker 1: I really like the restaurant and I just want my

1012
00:54:33,840 --> 00:54:35,560
Speaker 1: friends to know, and I think it's kind of cool,

1013
00:54:35,680 --> 00:54:37,840
Speaker 1: and you know, get and I get bonuses if I

1014
00:54:37,920 --> 00:54:40,680
Speaker 1: check in enough times. So what this app was doing

1015
00:54:40,840 --> 00:54:43,239
Speaker 1: was it was pulling the check in information from four

1016
00:54:43,280 --> 00:54:48,640
Speaker 1: Square and pulling Facebook profiles that were connected to those

1017
00:54:48,680 --> 00:54:52,000
Speaker 1: four square profiles and pulling in pictures and information about people.

1018
00:54:52,080 --> 00:54:54,000
Speaker 1: So if I had the app and I wanted to

1019
00:54:54,080 --> 00:54:55,680
Speaker 1: use it, I could pull it up. It would pull

1020
00:54:55,760 --> 00:54:59,680
Speaker 1: up a map show the check ins surrounding my area.

1021
00:55:00,080 --> 00:55:01,839
Speaker 1: If I click on any of them, it would show

1022
00:55:01,840 --> 00:55:04,879
Speaker 1: me pictures from the Facebook profile of the person who

1023
00:55:04,880 --> 00:55:07,160
Speaker 1: had checked in. I could even look at their profile

1024
00:55:07,200 --> 00:55:09,440
Speaker 1: and get more information about them, like what they like,

1025
00:55:09,600 --> 00:55:13,000
Speaker 1: what their name is, how old they are, And so

1026
00:55:13,200 --> 00:55:15,160
Speaker 1: a lot of people pointed out that this could really

1027
00:55:15,200 --> 00:55:19,600
Speaker 1: facilitate stalkers, right, I mean, if I look up a person,

1028
00:55:19,680 --> 00:55:22,120
Speaker 1: I think, oh, she's cute. Oh, and she likes these

1029
00:55:22,160 --> 00:55:24,560
Speaker 1: bands and this is her name. I could walk up

1030
00:55:24,560 --> 00:55:27,640
Speaker 1: to her and say, hey, there Susie. Uh yeah, you

1031
00:55:27,680 --> 00:55:30,440
Speaker 1: know this band is coming to town again and I

1032
00:55:30,480 --> 00:55:33,600
Speaker 1: was just thinking maybe we could go check it out. Yeah. Especially,

1033
00:55:33,719 --> 00:55:36,920
Speaker 1: you could present yourself as if this person already knew you,

1034
00:55:37,560 --> 00:55:43,279
Speaker 1: and that is very problematic. So especially find that problematic

1035
00:55:43,800 --> 00:55:48,600
Speaker 1: for for younger people. Yeah, yeah, especially for anyone again

1036
00:55:48,640 --> 00:55:51,920
Speaker 1: who is not truly aware of the implications of sharing.

1037
00:55:52,360 --> 00:55:54,520
Speaker 1: And we see this a lot where people just don't

1038
00:55:54,600 --> 00:55:58,080
Speaker 1: really think of the consequences of sharing. A lot of information. Well,

1039
00:55:58,239 --> 00:56:01,640
Speaker 1: it caused so much commotion, and that four Square pulled

1040
00:56:01,640 --> 00:56:05,280
Speaker 1: the API, the part of their their programming that allows

1041
00:56:05,480 --> 00:56:09,160
Speaker 1: people to develop apps to take advantage of four squares capabilities.

1042
00:56:09,400 --> 00:56:12,640
Speaker 1: They pulled it, so it took away the functionality of

1043
00:56:12,680 --> 00:56:15,680
Speaker 1: the app, and eventually the the Russian company that created

1044
00:56:15,680 --> 00:56:18,040
Speaker 1: the app removed it from the iTunes store because it

1045
00:56:18,080 --> 00:56:21,040
Speaker 1: was broken. You couldn't use it anymore because the four

1046
00:56:21,080 --> 00:56:24,480
Speaker 1: Square functionality have been pulled from it. But it certainly

1047
00:56:24,560 --> 00:56:26,000
Speaker 1: was one of those things that opened up a lot

1048
00:56:26,000 --> 00:56:29,399
Speaker 1: of eyes about the potential dangers of using these kind

1049
00:56:29,400 --> 00:56:33,360
Speaker 1: of apps. So it is important to have this human interaction,

1050
00:56:34,160 --> 00:56:37,080
Speaker 1: and we don't want to discourage people from having human interaction,

1051
00:56:37,120 --> 00:56:39,960
Speaker 1: but you have to do it with the right context.

1052
00:56:40,080 --> 00:56:42,000
Speaker 1: You have to do it with the right mind for

1053
00:56:42,080 --> 00:56:45,880
Speaker 1: your safety, into your security and just whatever it is

1054
00:56:45,920 --> 00:56:47,360
Speaker 1: that you're hoping to get out of it, that you

1055
00:56:47,360 --> 00:56:52,080
Speaker 1: have the right expectations for it, because otherwise bad things

1056
00:56:52,120 --> 00:56:57,520
Speaker 1: could happen. It's just that's that's the Yeah. Yeah, as

1057
00:56:57,560 --> 00:57:00,839
Speaker 1: we pointed out, a lot of solid relationships, it's true. Yeah,

1058
00:57:00,880 --> 00:57:03,239
Speaker 1: there's been a lot of studies about online dating that

1059
00:57:03,280 --> 00:57:06,920
Speaker 1: have suggested that there are lots of benefits. Gives you

1060
00:57:07,040 --> 00:57:09,520
Speaker 1: a lot more chances to meet a potential partner, so

1061
00:57:09,920 --> 00:57:15,080
Speaker 1: your your h pool of potential partners is increased, meaning

1062
00:57:15,080 --> 00:57:17,640
Speaker 1: that you have a chance of finding that relationship that

1063
00:57:17,680 --> 00:57:21,160
Speaker 1: gives you real meaning and in a sense of fulfillment. Um.

1064
00:57:21,280 --> 00:57:24,280
Speaker 1: It helps cut down on potentially threatening context because you

1065
00:57:24,280 --> 00:57:27,640
Speaker 1: can have those early interactions in an online space as

1066
00:57:27,680 --> 00:57:31,880
Speaker 1: opposed to a physical space, and you can determine quickly

1067
00:57:32,600 --> 00:57:35,040
Speaker 1: which ones are the ones that are most promising and

1068
00:57:35,120 --> 00:57:37,480
Speaker 1: which ones you think are not going to lead anywhere

1069
00:57:37,560 --> 00:57:42,320
Speaker 1: or are undesirable. So that's an advantage as well. Uh,

1070
00:57:42,440 --> 00:57:44,840
Speaker 1: it gives you the chance to omit people from that

1071
00:57:44,920 --> 00:57:47,440
Speaker 1: pool if you realize very early on, like no, this

1072
00:57:47,480 --> 00:57:49,240
Speaker 1: is not what I want, this person is not and

1073
00:57:49,280 --> 00:57:52,640
Speaker 1: I are not going to click. Um. Now, we talked

1074
00:57:52,680 --> 00:57:56,560
Speaker 1: about the shopping downside with the objectification of people. You

1075
00:57:57,000 --> 00:57:59,919
Speaker 1: treat them as objects. This person is hot, this person

1076
00:58:00,120 --> 00:58:04,120
Speaker 1: not hot. That is an issue. Uh, it's really easy

1077
00:58:04,200 --> 00:58:07,600
Speaker 1: to to just blast through people as if they are

1078
00:58:07,680 --> 00:58:12,440
Speaker 1: just data and that isn't that's a problem. Objectifying people

1079
00:58:12,520 --> 00:58:16,840
Speaker 1: is not not a great outcome psychologically speaking. Um. And

1080
00:58:16,880 --> 00:58:19,680
Speaker 1: also that matching with personality types appears to have a

1081
00:58:19,720 --> 00:58:23,800
Speaker 1: relatively minor role in romantic attraction or relationship success. So

1082
00:58:23,880 --> 00:58:26,360
Speaker 1: even if you find that person who on paper is

1083
00:58:26,360 --> 00:58:28,520
Speaker 1: a perfect match for you, it doesn't guarantee that you

1084
00:58:28,560 --> 00:58:31,840
Speaker 1: will have a happy relationship with that person. It's more

1085
00:58:31,880 --> 00:58:35,720
Speaker 1: to it than that. And uh, again, it doesn't help

1086
00:58:35,720 --> 00:58:39,040
Speaker 1: that we can't necessarily know what we're actually looking for

1087
00:58:39,080 --> 00:58:41,600
Speaker 1: when we go out looking for that potential someone. We

1088
00:58:42,480 --> 00:58:45,160
Speaker 1: think we do, yeah, because we think we know exactly

1089
00:58:45,200 --> 00:58:47,200
Speaker 1: the things that are going to appeal to us. But

1090
00:58:47,400 --> 00:58:49,920
Speaker 1: that's not always the case, you know. They say like

1091
00:58:49,960 --> 00:58:53,560
Speaker 1: the opposites attract. Part of that is to say that

1092
00:58:53,600 --> 00:58:55,840
Speaker 1: if you go and find someone who's exactly like yourself,

1093
00:58:55,880 --> 00:58:58,320
Speaker 1: you may not find that to be a rewarding experience.

1094
00:58:58,360 --> 00:59:01,120
Speaker 1: I know that if my wife are exactly like I am,

1095
00:59:01,640 --> 00:59:03,520
Speaker 1: one of us would have killed the other one. By now,

1096
00:59:04,240 --> 00:59:07,160
Speaker 1: it would have happened. One of me is more than enough,

1097
00:59:07,240 --> 00:59:10,480
Speaker 1: is what I'm saying. But the studies show that online

1098
00:59:10,480 --> 00:59:13,760
Speaker 1: relationships can be just as stable as those that were

1099
00:59:13,760 --> 00:59:18,920
Speaker 1: formed offline. So online is a great way to meet people,

1100
00:59:19,040 --> 00:59:23,440
Speaker 1: it's and it can lead to a happy, stable relationship. Um,

1101
00:59:23,480 --> 00:59:27,040
Speaker 1: it's just important that you know, you take that expectation

1102
00:59:27,080 --> 00:59:29,000
Speaker 1: and you check it to make sure that you're not

1103
00:59:29,040 --> 00:59:32,480
Speaker 1: going in with with with online stars in your eyes

1104
00:59:33,080 --> 00:59:36,040
Speaker 1: and m so I think the end of the day,

1105
00:59:36,080 --> 00:59:39,480
Speaker 1: we say use use online tools if that's what you're

1106
00:59:39,760 --> 00:59:41,560
Speaker 1: You know, when you're looking for someone, whether you're looking

1107
00:59:41,560 --> 00:59:43,400
Speaker 1: for someone to hang out with or you're looking for

1108
00:59:43,440 --> 00:59:47,320
Speaker 1: someone to potentially be uh, you know that that special

1109
00:59:47,360 --> 00:59:51,360
Speaker 1: someone in your life, but do so with critical thinking,

1110
00:59:51,560 --> 00:59:54,480
Speaker 1: do so with safety in mind. Do so knowing that

1111
00:59:54,480 --> 00:59:57,920
Speaker 1: that's another person at the end of that profile, you know,

1112
00:59:58,040 --> 01:00:01,280
Speaker 1: not an object. That is another person, eman being with feelings.

1113
01:00:01,720 --> 01:00:04,439
Speaker 1: They've got hopes, they've got dreams, they've got aspirations, they've

1114
01:00:04,440 --> 01:00:07,560
Speaker 1: got fears, they've got doubts about themselves. And if you

1115
01:00:07,680 --> 01:00:09,560
Speaker 1: keep that in mind, and you're more likely to have

1116
01:00:09,680 --> 01:00:13,480
Speaker 1: a human interaction as opposed to something that crashes and

1117
01:00:13,560 --> 01:00:17,600
Speaker 1: burns and is a terrible experience for everybody. UM, I

1118
01:00:17,640 --> 01:00:20,240
Speaker 1: don't know why I'm giving dating advice. I'm not necessarily

1119
01:00:20,240 --> 01:00:22,680
Speaker 1: an authority on the subject. I'm just a very empathetic

1120
01:00:22,760 --> 01:00:25,120
Speaker 1: kind of person that I did have a blast researching

1121
01:00:25,120 --> 01:00:29,400
Speaker 1: this podcast. Yeah, it's fascinating world of modern love. Yeah,

1122
01:00:29,400 --> 01:00:32,520
Speaker 1: I'm really uh and that's a great song by David Bowie.

1123
01:00:32,720 --> 01:00:36,680
Speaker 1: I'm really um hoping that we can find more studies

1124
01:00:36,960 --> 01:00:40,560
Speaker 1: that show really what was the psychological impact of some

1125
01:00:40,640 --> 01:00:44,000
Speaker 1: of these approaches. I'm very curious to see what the

1126
01:00:44,360 --> 01:00:48,200
Speaker 1: tender approach is like. Uh. From that, From that a

1127
01:00:48,240 --> 01:00:51,920
Speaker 1: psychological perspective, I often I also think that most of

1128
01:00:51,920 --> 01:00:54,120
Speaker 1: the people who are using tender tend to be in

1129
01:00:54,160 --> 01:00:57,560
Speaker 1: an age group where it's you know, they're not necessarily

1130
01:00:57,600 --> 01:00:59,520
Speaker 1: looking for the person who's going to be with them

1131
01:00:59,520 --> 01:01:01,560
Speaker 1: for the rest of their lives. And there's nothing necessarily

1132
01:01:01,560 --> 01:01:05,040
Speaker 1: wrong with that. Again, assuming that everyone's going in with

1133
01:01:05,080 --> 01:01:10,160
Speaker 1: equal expectations. Um, So I don't necessarily think it's harmful

1134
01:01:10,240 --> 01:01:12,840
Speaker 1: in the long run. It may just be one of

1135
01:01:12,880 --> 01:01:17,360
Speaker 1: those phases of maturity, right so um. But again I'm

1136
01:01:17,400 --> 01:01:19,200
Speaker 1: not an expert on that either. This is a lot

1137
01:01:19,280 --> 01:01:23,120
Speaker 1: of armchair psychology from Jonathan today. Alison, thank you so

1138
01:01:23,200 --> 01:01:26,280
Speaker 1: much for joining me. I had a blast, Jonathan, thanks

1139
01:01:26,320 --> 01:01:31,000
Speaker 1: for having me. Yeah, Alison is an incredibly busy woman.

1140
01:01:31,200 --> 01:01:33,640
Speaker 1: She and it's a lot of the articles that you

1141
01:01:33,720 --> 01:01:36,280
Speaker 1: see at how stuff works dot com and if you've

1142
01:01:36,280 --> 01:01:38,640
Speaker 1: ever visited the site and thought, Wow, this site is awesome.

1143
01:01:39,200 --> 01:01:42,360
Speaker 1: A huge part of that comes from Allison makes make

1144
01:01:42,400 --> 01:01:44,640
Speaker 1: sure that the awesome gets through and they'm not awesome

1145
01:01:44,720 --> 01:01:50,080
Speaker 1: doesn't get through. So uh, Alison, keep fighting the good fight.

1146
01:01:50,160 --> 01:01:52,840
Speaker 1: You're doing great work. And guys, if you have any

1147
01:01:52,880 --> 01:01:55,600
Speaker 1: suggestions for future episodes of tech Stuff, maybe there's some

1148
01:01:55,680 --> 01:01:59,400
Speaker 1: other aspect of technology that you've always wondered more about,

1149
01:01:59,520 --> 01:02:02,360
Speaker 1: like what's the cultural impact of something, or just how

1150
01:02:02,480 --> 01:02:05,880
Speaker 1: something works? Right in ask me a question my email

1151
01:02:05,880 --> 01:02:09,160
Speaker 1: addresses tex stuff at how stuff works dot com, or

1152
01:02:09,240 --> 01:02:12,080
Speaker 1: dropped me a line on Facebook, Twitter or Tumbler. The

1153
01:02:12,160 --> 01:02:14,920
Speaker 1: handle at all three is tech Stuff H. S W

1154
01:02:15,280 --> 01:02:21,640
Speaker 1: and I'll talk to you again. Really sick for more

1155
01:02:21,640 --> 01:02:24,040
Speaker 1: on this and bathands of other topics because it has

1156
01:02:24,040 --> 01:02:34,680
Speaker 1: to have works dot Com