WEBVTT - Week in Tech: CheatGPT

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<v Speaker 1>Welcome to Tech Stuff, a production of iHeart Podcasts and Kaleidoscope.

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<v Speaker 1>I'm os Vlosian, and today Karen Price and I will

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<v Speaker 1>bring you the headlines this week, including how Interpol is

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<v Speaker 1>keeping up with new types of crime. Then on tech Support,

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<v Speaker 1>we'll talk to the Washington Posts Drew Holwell about one

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<v Speaker 1>woman's three year twenty four to seven live stream experiment.

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<v Speaker 2>Some of the people I talked to who were Emily's fans,

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<v Speaker 2>they would go to sleep listening to Emily's voice.

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<v Speaker 1>All of that. On the Weekend Tech It's Friday, May Night.

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<v Speaker 1>So Carol, we have become quite fascinated on this program

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<v Speaker 1>by personas online who aren't exactly what they seem.

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<v Speaker 3>That is absolutely right.

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<v Speaker 4>In last week, you'll remember we did the deep dive

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<v Speaker 4>on AI John Cena, who's the metabot, getting into all

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<v Speaker 4>kinds of illegal sexual situations, which was very disturbing.

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<v Speaker 1>Yeah, well that's right. I've got a story this week

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<v Speaker 1>though about real people pretending to be something they're not

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<v Speaker 1>online and a novel way of catching them out.

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<v Speaker 3>Is that called a dating app?

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<v Speaker 1>They tell me this is basically this is geopolitical catfishing.

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<v Speaker 1>According to cybersecurity experts, thousands of North Korean infiltrators are

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<v Speaker 1>getting hired by Fortune five hundred companies.

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<v Speaker 4>So the North Koreans who aren't fighting with Russia on

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<v Speaker 4>the battlefields of Ukraine are working for large American corporations.

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<v Speaker 1>That's exactly right. And then once they get hired, they

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<v Speaker 1>collect their wages, but they also steal intellectual property and

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<v Speaker 1>insert malware.

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<v Speaker 3>So in a way, this is another battlefield.

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<v Speaker 1>That's very well put Cara. There's a publication called The

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<v Speaker 1>Register which reported that these North Korean infiltrators have gone

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<v Speaker 1>undetected by masking their IP addresses by creating farms of

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<v Speaker 1>laptops which are physically situated in the US, and then

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<v Speaker 1>they basically pay US people to allow them to remotely

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<v Speaker 1>dial into these laptop farms. They're also of course using

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<v Speaker 1>AI to write job applications as everyone is, and making

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<v Speaker 1>fake LinkedIn profiles. Once they actually get hired there, they

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<v Speaker 1>tend to do very well because they have a whole

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<v Speaker 1>army of other North Koreans helping them do their jobs

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<v Speaker 1>in the background.

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<v Speaker 3>So they have actual coworkers, they have.

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<v Speaker 1>Co workers there as a front man who gets the

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<v Speaker 1>job and then dozens of people who help them do

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<v Speaker 1>an excellent job. And part of the story is actually

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<v Speaker 1>that even when companies become aware, they don't want to

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<v Speaker 1>fire these people because they're so much better than all

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<v Speaker 1>the other employees.

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<v Speaker 3>So they're keeping they get to keep their job.

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<v Speaker 1>I think they probably do in the end to have

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<v Speaker 1>to get rid of them. One cybersecurity expert, however, has

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<v Speaker 1>found a full proof way to catch out a suspected

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<v Speaker 1>North Korean infiltrator in a job interview.

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<v Speaker 3>That's something that I need to know in my every

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<v Speaker 3>day life.

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<v Speaker 1>It all starts with a question, do you know what

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<v Speaker 1>the question is?

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<v Speaker 3>I have no idea.

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<v Speaker 1>How fat is Kim Johnkwun? Ask me the question, how

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<v Speaker 1>fat is Kim junk Wun? Well, you're not too long.

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<v Speaker 1>North Korean infiltrated would immediately close out of the video

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<v Speaker 1>conference because even contemplating that question is to.

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<v Speaker 3>As Wow, that's so interesting.

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<v Speaker 1>So that's fake fake people of the wheat story.

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<v Speaker 4>I'll have one next week for you, maybe about me.

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<v Speaker 4>So you love stories about fake people online. I love

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<v Speaker 4>Peanut M and MS very good match.

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<v Speaker 3>Very good. You know who eats Pean and M and MS.

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<v Speaker 4>Probably Kim Johnon He may do he may If you

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<v Speaker 4>can get an eminem into.

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<v Speaker 1>Big red wine enthusiasts.

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<v Speaker 4>French red wine really attressive, of course, not chatewed Diana

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<v Speaker 4>so well. Speaking of Chateau Diana and peanut m and ms,

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<v Speaker 4>there's a new app that is gaining popularity that a

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<v Speaker 4>lot of my friends actually use, and it's this app

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<v Speaker 4>that tells you how guilty your guilty snacking pleasure.

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<v Speaker 1>Is like a calorie counter apple, what.

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<v Speaker 3>Sort of it's like calorie counter adjacent.

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<v Speaker 1>It's called yuka, like the vegetable. That's correct, but it

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<v Speaker 1>also has yuck in it.

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<v Speaker 3>I just made up a new word. That's correct. It's correct.

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<v Speaker 4>That's correct for those of you, like OZ who are

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<v Speaker 4>unfamiliar with it. The app actually lets you scan the

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<v Speaker 4>barcodes of different foods and personal products and then gives

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<v Speaker 4>them a score based on how healthy it is. Everything

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<v Speaker 4>that I've ever scanned is like you will die.

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<v Speaker 1>So you basically you take a photo of the barcode

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<v Speaker 1>and upload it to the app, and then it kind

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<v Speaker 1>of spits out what the product has in it.

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<v Speaker 3>That's right, that's right.

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<v Speaker 1>How did the M and ms do?

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<v Speaker 3>Zero out of one hundred?

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<v Speaker 1>Is actually true?

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<v Speaker 3>Yes?

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<v Speaker 1>Yes, the nuts in them?

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<v Speaker 3>What you said?

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<v Speaker 4>They contain at least six additives, four of which it

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<v Speaker 4>rated as high risk.

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<v Speaker 3>Whatever high risk means.

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<v Speaker 4>It's already I'm too far gone because I eat pan

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<v Speaker 4>and Eminem's every single night.

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<v Speaker 3>I call them my night chocolate.

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<v Speaker 1>You know. I read that the app sometimes offers healthier

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<v Speaker 1>alternatives for products that you've scanned or looked up, and

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<v Speaker 1>I'll produce a tory. Actually tried scanning some Twinkies. Sadly,

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<v Speaker 1>there are no alternatives.

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<v Speaker 4>This is like when people say, oh, do you want

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<v Speaker 4>to have sex? Free sex? You know what I'm saying,

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<v Speaker 4>It's just that to me, Well, it's like how I

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<v Speaker 4>feel about all these alternatives. So I actually have a

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<v Speaker 4>friend who was pushing Yuka on me so hard, and

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<v Speaker 4>I'm like, leave me out of this drama. I don't

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<v Speaker 4>want to see what's in the products that I'm eating.

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<v Speaker 4>But it actually looks like she's not alone. Unsurprisingly, our

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<v Speaker 4>dear RFK Junior and his wife both use Yuka.

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<v Speaker 1>This is the app you use if you want to

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<v Speaker 1>have the feeling of the United States Secretary of Health

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<v Speaker 1>and Human Services constantly whispering over your shoulder about food additives.

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<v Speaker 1>And indeed, those emin ms have red forty, which.

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<v Speaker 4>Is so sad because red eminems are my favorite m

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<v Speaker 4>and ms. You know, I think it speaks to a

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<v Speaker 4>sort of health conscious, make America healthy moment people are having.

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<v Speaker 3>Like if you've been to.

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<v Speaker 4>The grocery store recently, they're putting protein on everything, like

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<v Speaker 4>protein waffles.

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<v Speaker 3>Like, why do I need prote in my popcorn? It's

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<v Speaker 3>just popcorn?

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<v Speaker 1>You know.

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<v Speaker 4>There are sodas with extra fiber and probiotics in them.

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<v Speaker 4>You've got steak and shake transitioning away from using seed

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<v Speaker 4>oils in French fry, Like if I go to steak

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<v Speaker 4>a chake, I want to eat a French fry. I'm

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<v Speaker 4>not trying to eat like an avocado oil French fry.

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<v Speaker 1>The wood Street Channal reported that Yuka has sixty eight

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<v Speaker 1>million users worldwide, and an average of twenty five thousand

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<v Speaker 1>new US users have joined daily since the beginning of

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<v Speaker 1>this year, twenty five thousand people every day. At the

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<v Speaker 1>beginning of May, Yuka rank as the number one health

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<v Speaker 1>and fitness app in Apple's app store. Not only that,

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<v Speaker 1>major food brands like Campbell's and Chabani have responded to

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<v Speaker 1>customers complaining about the ingredients they find in their products

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<v Speaker 1>while using Yuka.

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<v Speaker 4>I don't want to think that we are all becoming

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<v Speaker 4>Rfki junior. But I think at least once you download

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<v Speaker 4>the app, you can think that you're being health conscious,

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<v Speaker 4>even if it's one time.

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<v Speaker 1>I mean, I think the thing is like if you're

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<v Speaker 1>reaching for a bag of M and m's no judgment,

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<v Speaker 1>you kind of know it's not besting anyway.

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<v Speaker 4>Anything that I reach for, It's like, I don't need

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<v Speaker 4>an app to tell me if I'm doing something right now.

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<v Speaker 1>I think if you're choosing between like different frozen dinners,

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<v Speaker 1>for example, and one is like categorically best than the other,

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<v Speaker 1>that like, if you're like it's an input to a

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<v Speaker 1>switching decision versus like should I eat the eminems, I

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<v Speaker 1>can imagine it being more useful.

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<v Speaker 4>Yes, and I do think people are interested in finding

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<v Speaker 4>healthy alternatives, which is an interesting thing.

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<v Speaker 3>I guess that comes out of Yuca. Yes, that's absolutely true.

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<v Speaker 1>Well, some people are looking into what's going into their food,

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<v Speaker 1>others into what's going into their clusrooms.

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<v Speaker 3>Very nice.

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<v Speaker 1>Thank You've got a headline for us about this.

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<v Speaker 4>I do have a news story for you about what's

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<v Speaker 4>going on in the classroom, a place I haven't been

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<v Speaker 4>in at least fifteen years. Recently, over two hundred and

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<v Speaker 4>fifty CEOs, from Microsoft's Satya Nadella to Josh Kushner's Karly

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<v Speaker 4>Klaus to the CEO of the College Board signed an

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<v Speaker 4>open letter calling for computer science and AI to be

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<v Speaker 4>quote a core part of US kindergarten through twelve curricula.

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<v Speaker 4>The letter states that taking just one high school computer

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<v Speaker 4>science course can boost students few wages by eight percent,

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<v Speaker 4>regardless of career path or college attendance.

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<v Speaker 1>One of these moments where we were like in peak,

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<v Speaker 1>everyone should learn to code, and then it was like

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<v Speaker 1>no one should learn to code, and now it's like

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<v Speaker 1>people should learn to code again.

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<v Speaker 4>I know I'd to use a computer very young, and

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<v Speaker 4>my income has not been boosted by eight percent.

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<v Speaker 3>I'll tell you that.

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<v Speaker 1>The letter doesn't specify really how this curriculum should be

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<v Speaker 1>developed and rolled out, but it does point to countries

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<v Speaker 1>like Singapore, China, and South Korea as examples of countries

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<v Speaker 1>they've done this successfully. The letter reads, quote in the

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<v Speaker 1>age of AI, we must prepare our children for the

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<v Speaker 1>future to be AI creators, not just consumers. A basic

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<v Speaker 1>foundation in computer science and AI is crucial for helping

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<v Speaker 1>every student thrive in a technology driven world. Without it,

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<v Speaker 1>there is falling behind.

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<v Speaker 4>Yeah, there's a huge investment in AI education from countries

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<v Speaker 4>who want to get a long term edge in the

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<v Speaker 4>AI race, Like the UAE. The Amoradi school system will

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<v Speaker 4>add AI as a subject in the upcoming school year

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<v Speaker 4>and will include concepts like ethical awareness and real world applications.

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<v Speaker 4>Schools in Beijing will start offering AI courses in September

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<v Speaker 4>as well.

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<v Speaker 1>Here in the US, President Trump recently signed an executive

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<v Speaker 1>order calling to emphasize AI competency in schools. The executive

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<v Speaker 1>order also called the establishment of a Presidential Artificial Intelligence

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<v Speaker 1>Challenge and nationwide competition for students and educators demonstrate their

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<v Speaker 1>AI skills.

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<v Speaker 4>This reminds me of the Bass pro fishing Python Hunter

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<v Speaker 4>Bowl in Florida, which is something I really loved. But no, honestly,

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<v Speaker 4>it seems like kids are demonstrating their AI skills, just

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<v Speaker 4>not in the ways that teachers would perhaps like them to.

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<v Speaker 4>New York Magazine actually ran an article titled quote everyone

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<v Speaker 4>is cheating their way through college, And there was actually

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<v Speaker 4>a statistic in there that was really striking, which is

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<v Speaker 4>that in a survey of one thousand college students, nearly

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<v Speaker 4>ninety percent the other ten percenter line had used chat

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<v Speaker 4>gpt for homework help. And this was back in twenty

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<v Speaker 4>twenty three, before chat gpt became you know, every eighty

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<v Speaker 4>year old's best friend.

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<v Speaker 1>Yeah, that last ten percent, I think it's probably been

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<v Speaker 1>accounted for since twenty twenty three. One of the students said, quote,

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<v Speaker 1>with chat gipt, I can write an essay in two

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<v Speaker 1>hours that normally takes twelve. It can't be easy being

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<v Speaker 1>k through twelve teacher or college professor these days. Some

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<v Speaker 1>of them have tried devising their own ways to detect

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<v Speaker 1>chatchipt usage in their student's essays. Others say, you can

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<v Speaker 1>tell when an essay is written by a chatbot because

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<v Speaker 1>it's written clunkily or random words. But of course these

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<v Speaker 1>models are just getting better and better.

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<v Speaker 4>I mean, we got away with it in the script,

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<v Speaker 4>didn't we know? I'm kidding, But the way that I

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<v Speaker 4>would have exploited chat gypt at sixteen seventeen eighteen. You know,

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<v Speaker 4>all I had back in my day was free translation

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<v Speaker 4>dot com, which allowed me to write long French essays.

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<v Speaker 1>Yes, you can work well enough to did it depends on.

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<v Speaker 3>As my B plus baby as MYB plus.

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<v Speaker 1>So our next headline is about competition between the US

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<v Speaker 1>and China, but not in the classroom and not really

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<v Speaker 1>an AI, rather in the realm of vehicles. The Wall

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<v Speaker 1>Street Journal around this headline with the story what a

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<v Speaker 1>fifteen thousand dollars electric suv says about the US China

0:11:01.720 --> 0:11:05.640
<v Speaker 1>car rivalry. The car in question is the Toyota BZ

0:11:05.920 --> 0:11:09.440
<v Speaker 1>three X, which is a compact electric suv about the

0:11:09.440 --> 0:11:12.120
<v Speaker 1>same size as the Toyota RAV four, which of course

0:11:12.200 --> 0:11:15.040
<v Speaker 1>is ubiquitous here in the US. But the car has

0:11:15.080 --> 0:11:16.800
<v Speaker 1>a jaw droppingly low price tag.

0:11:17.600 --> 0:11:20.200
<v Speaker 4>If an electric car costs fifteen thousand dollars, it would

0:11:20.200 --> 0:11:21.600
<v Speaker 4>be like a plug and chug driver.

0:11:22.000 --> 0:11:22.760
<v Speaker 3>It's amazing.

0:11:23.200 --> 0:11:26.080
<v Speaker 1>Yeah, Well, you can thank China's supply chains for the

0:11:26.080 --> 0:11:28.880
<v Speaker 1>price of the car. Toyota are obviously a Japanese company,

0:11:29.320 --> 0:11:32.200
<v Speaker 1>but the cars are localized in different parts of the world,

0:11:32.400 --> 0:11:35.520
<v Speaker 1>and this suv is made in China using Chinese batteries

0:11:35.640 --> 0:11:39.640
<v Speaker 1>and Chinese driver assistance technology. But when Toyotas are sold

0:11:39.640 --> 0:11:42.319
<v Speaker 1>in the US, the supply chain is way more expensive.

0:11:42.720 --> 0:11:46.199
<v Speaker 1>There's a similar model available here for about forty thousand dollars,

0:11:46.559 --> 0:11:48.480
<v Speaker 1>so someone else, why don't you buy the Chinese version

0:11:48.480 --> 0:11:51.520
<v Speaker 1>and import it. Well, that'd be the most beautiful word

0:11:51.720 --> 0:11:55.480
<v Speaker 1>in English language tariffs, except in this case, bidener are

0:11:55.559 --> 0:11:58.600
<v Speaker 1>tariffs which put one hundred percent tariff on Chinese evs.

0:11:58.800 --> 0:12:02.280
<v Speaker 4>And I don't see Trump reversing that one.

0:12:02.640 --> 0:12:04.160
<v Speaker 1>That's not one of the ones he's going to be

0:12:04.520 --> 0:12:05.600
<v Speaker 1>running back gus for sure.

0:12:05.600 --> 0:12:07.480
<v Speaker 4>But it's a weird thing how much we live in

0:12:07.480 --> 0:12:11.400
<v Speaker 4>this parallel universe with China, Like fifteen thousand versus forty thousand,

0:12:11.480 --> 0:12:13.000
<v Speaker 4>is I guess a one hundred percent tariff?

0:12:13.040 --> 0:12:14.040
<v Speaker 3>There you go, that's that.

0:12:16.080 --> 0:12:19.960
<v Speaker 1>More. And China people buy local car brands that we've

0:12:19.960 --> 0:12:23.640
<v Speaker 1>never heard of here in the US Zeka Ion there

0:12:23.679 --> 0:12:26.120
<v Speaker 1>is one that's slightly more well known called BYD not

0:12:26.160 --> 0:12:30.880
<v Speaker 1>by me. And the technology around these Chinese evs is

0:12:30.960 --> 0:12:35.240
<v Speaker 1>very impressive. C ATL, a Chinese battery manufacturer, recently showed

0:12:35.240 --> 0:12:37.640
<v Speaker 1>off a new EV battery that can put three hundred

0:12:37.720 --> 0:12:40.840
<v Speaker 1>miles of charge into a car battery in just five minutes.

0:12:41.040 --> 0:12:41.840
<v Speaker 3>That's insane.

0:12:41.960 --> 0:12:45.559
<v Speaker 1>These companies in China, these battery companies and car companies

0:12:46.080 --> 0:12:48.160
<v Speaker 1>are really really pulling ahead in the race.

0:12:48.280 --> 0:12:49.120
<v Speaker 3>That's incredible.

0:12:49.360 --> 0:12:52.040
<v Speaker 4>It just seems like cars are a really good reflection

0:12:52.120 --> 0:12:54.960
<v Speaker 4>of the sort of siling off of global economies, at

0:12:55.040 --> 0:12:57.640
<v Speaker 4>least between the US and China, and with the addition

0:12:57.720 --> 0:13:00.880
<v Speaker 4>of more tariffs on Chinese imports, this it probably isn't

0:13:00.880 --> 0:13:02.400
<v Speaker 4>going to change anytime soon.

0:13:03.120 --> 0:13:04.679
<v Speaker 3>Bye. By globalization.

0:13:05.360 --> 0:13:08.440
<v Speaker 1>There is one area though, where countries still work together,

0:13:09.120 --> 0:13:10.439
<v Speaker 1>and that's Interpol.

0:13:10.800 --> 0:13:12.000
<v Speaker 3>You know, you're right about that.

0:13:12.480 --> 0:13:14.120
<v Speaker 4>And I wanted to tell you a little bit about

0:13:14.120 --> 0:13:17.360
<v Speaker 4>this Financial Time story that I read about how Interpol

0:13:17.400 --> 0:13:20.520
<v Speaker 4>has been adapting to the technologies modern criminals are using.

0:13:20.960 --> 0:13:25.360
<v Speaker 4>Interpol you know, is, of course the International Criminal Police Organization.

0:13:25.840 --> 0:13:28.240
<v Speaker 1>Of course I didn't know that. I thought you would.

0:13:28.720 --> 0:13:29.960
<v Speaker 3>You're supposed to know all this stuff.

0:13:30.120 --> 0:13:31.479
<v Speaker 1>I thought it was French Interpol.

0:13:31.640 --> 0:13:34.200
<v Speaker 4>So let me say it again for you, international criminal

0:13:34.280 --> 0:13:37.720
<v Speaker 4>police organization. And they have been engaged in a technological

0:13:37.840 --> 0:13:40.319
<v Speaker 4>arms race with the world's most wanted criminals. I always

0:13:40.360 --> 0:13:42.280
<v Speaker 4>think of inspector Gadget when I think of this stuff.

0:13:42.400 --> 0:13:45.160
<v Speaker 1>The article is a great read, and it describes Interpol's

0:13:45.200 --> 0:13:48.840
<v Speaker 1>innovation lab, which is in Singapore, with an opening scene

0:13:49.080 --> 0:13:53.440
<v Speaker 1>quote a fleet of underwater drones, gleaming and ready for action,

0:13:53.800 --> 0:13:57.280
<v Speaker 1>is lined up along the wall. Nearby a small armory

0:13:57.400 --> 0:14:00.680
<v Speaker 1>of brightly colored three D printed guns displayed on a

0:14:00.720 --> 0:14:05.000
<v Speaker 1>side table. A robot dog named Ino lies prone on

0:14:05.040 --> 0:14:07.280
<v Speaker 1>the floor waiting to be activated.

0:14:07.480 --> 0:14:08.640
<v Speaker 3>There's something filthy.

0:14:08.800 --> 0:14:10.240
<v Speaker 4>When I first read that, I was like, you know,

0:14:10.320 --> 0:14:12.000
<v Speaker 4>I do not like the way they're talking about you

0:14:12.000 --> 0:14:14.600
<v Speaker 4>in this article. He lies prone on the floor. That's

0:14:14.600 --> 0:14:17.319
<v Speaker 4>how you know FT is a British newspaper. But yeah,

0:14:17.400 --> 0:14:21.280
<v Speaker 4>the FT actually interviewed the head of Interpol's Digital Forensics

0:14:21.320 --> 0:14:23.920
<v Speaker 4>team and he said that the advancement of technology in

0:14:23.920 --> 0:14:26.480
<v Speaker 4>the last couple of years is the biggest he's seen,

0:14:26.760 --> 0:14:28.640
<v Speaker 4>which is saying a lot because he's actually been working

0:14:28.720 --> 0:14:31.000
<v Speaker 4>there since the late nineties to keep up with the

0:14:31.000 --> 0:14:34.800
<v Speaker 4>evolution of cybercrime. Interpol actually opened the Singapore Lab in

0:14:34.840 --> 0:14:38.160
<v Speaker 4>twenty fifteen, and these days one of their main focuses

0:14:38.440 --> 0:14:41.840
<v Speaker 4>is identifying AI enabled scams, which, as you know and

0:14:41.880 --> 0:14:44.840
<v Speaker 4>as we know as a listenership, are getting more and.

0:14:44.760 --> 0:14:46.760
<v Speaker 3>More sophisticated with the use of deep fakes.

0:14:47.280 --> 0:14:50.280
<v Speaker 4>Just a decade ago we were dealing with the Nigerian

0:14:50.320 --> 0:14:52.720
<v Speaker 4>print scam, and now we are trying to tackle deep

0:14:52.720 --> 0:14:57.360
<v Speaker 4>fake romance scams, sextortion and multimillion dollar phishing attacks. So

0:14:57.400 --> 0:15:00.280
<v Speaker 4>when the FT reporter visited the Interpol lab, it was

0:15:00.360 --> 0:15:05.120
<v Speaker 4>monitoring nearly three point five million attempted cyber attacks, and

0:15:05.160 --> 0:15:07.640
<v Speaker 4>he was told that that was fairly typical.

0:15:08.040 --> 0:15:11.120
<v Speaker 1>I especially like the section about the robot canine units.

0:15:11.320 --> 0:15:14.040
<v Speaker 1>Some of the models Interpol has are the size of

0:15:14.040 --> 0:15:16.920
<v Speaker 1>a German shepherd, and they can run up to seven

0:15:16.920 --> 0:15:19.160
<v Speaker 1>and a half miles per hour, and they can jump

0:15:19.240 --> 0:15:22.760
<v Speaker 1>pretty high. And they can also be sort of two

0:15:22.840 --> 0:15:27.360
<v Speaker 1>way microphone systems carrying audio messages, which apparently can be

0:15:27.400 --> 0:15:29.360
<v Speaker 1>quite handy in hostage situations.

0:15:29.640 --> 0:15:32.240
<v Speaker 4>Yeah, so say what you want about technology being used

0:15:32.240 --> 0:15:35.520
<v Speaker 4>for morally dubious ends, but if I were the hostage

0:15:35.520 --> 0:15:38.360
<v Speaker 4>in that situation, at least my confusion would distract from

0:15:38.360 --> 0:15:40.840
<v Speaker 4>my panic, Like you'd be waiting for your captors to

0:15:40.920 --> 0:15:43.000
<v Speaker 4>untie you while they argue with a robot dog.

0:15:43.040 --> 0:15:47.280
<v Speaker 3>Like. Also, robot dogs can't retire or get sick or

0:15:47.280 --> 0:15:47.800
<v Speaker 3>get sick.

0:15:48.080 --> 0:15:51.680
<v Speaker 4>I actually just heard this story about how bomb squad

0:15:51.760 --> 0:15:54.280
<v Speaker 4>unit dogs have to retire with their owners.

0:15:54.360 --> 0:15:57.520
<v Speaker 1>Essentially, so the New York Police dogs basically they're one

0:15:57.520 --> 0:15:58.640
<v Speaker 1>person dogs.

0:15:58.520 --> 0:16:01.960
<v Speaker 4>And if they're handle or retire, they're like woh, Wow,

0:16:01.960 --> 0:16:03.200
<v Speaker 4>come to my retirement party.

0:16:03.280 --> 0:16:04.480
<v Speaker 1>Where's these robot dogs?

0:16:05.200 --> 0:16:08.360
<v Speaker 4>Exactly the root, completely owner agnostic.

0:16:08.440 --> 0:16:08.760
<v Speaker 3>Yeah.

0:16:08.840 --> 0:16:11.160
<v Speaker 4>But one of the big takeaways from the piece, this

0:16:11.400 --> 0:16:14.680
<v Speaker 4>ft piece, is that even with the innovation Lab, Interpol's

0:16:14.760 --> 0:16:15.880
<v Speaker 4>job is never over.

0:16:16.040 --> 0:16:18.480
<v Speaker 1>We talked about dogs, Now it's time for game of

0:16:18.840 --> 0:16:19.560
<v Speaker 1>cat and mouse.

0:16:22.000 --> 0:16:24.680
<v Speaker 4>Criminals will catch up and vice versa. You know, take

0:16:24.720 --> 0:16:28.000
<v Speaker 4>ghost guns for example. They are popular amongst criminals because,

0:16:28.080 --> 0:16:31.520
<v Speaker 4>unlike traditional firearms, they do not have serial numbers, and

0:16:31.560 --> 0:16:34.040
<v Speaker 4>so Interpol is now trying to figure out how to

0:16:34.120 --> 0:16:37.800
<v Speaker 4>link a ghost gun to their specific printers by analyzing

0:16:37.840 --> 0:16:40.280
<v Speaker 4>the composition of the materials in order to figure out

0:16:40.280 --> 0:16:40.840
<v Speaker 4>their origin.

0:16:41.120 --> 0:16:43.120
<v Speaker 1>I joked about cat and mouse gains. But you can

0:16:43.160 --> 0:16:46.600
<v Speaker 1>just imagine how the next innovation will be disguising the

0:16:46.720 --> 0:16:50.480
<v Speaker 1>variable compositions of these ghost guns. We've got a couple

0:16:50.480 --> 0:16:53.440
<v Speaker 1>more headlines to run through, Starting with another crime story.

0:16:54.000 --> 0:16:57.320
<v Speaker 1>The Guardian reports that a trial over a road rage

0:16:57.400 --> 0:17:01.160
<v Speaker 1>induced killing of a man called Chris Pelk is underway,

0:17:01.760 --> 0:17:06.119
<v Speaker 1>starring Chris Pelke and Ai. Generated Pelky appeared in a

0:17:06.200 --> 0:17:09.840
<v Speaker 1>video calling for forgiveness for the man accused of shooting

0:17:09.920 --> 0:17:13.520
<v Speaker 1>him in what maybe the first AI delivered victim impact

0:17:13.560 --> 0:17:16.280
<v Speaker 1>statement ever delivered in a courtroom. I'm going to play

0:17:16.320 --> 0:17:16.600
<v Speaker 1>a fore.

0:17:16.600 --> 0:17:20.080
<v Speaker 3>Now, in another life, we probably could have been friends.

0:17:20.800 --> 0:17:23.200
<v Speaker 3>I believe in forgiveness and in God who forgives.

0:17:23.480 --> 0:17:25.600
<v Speaker 1>I always have and I still do.

0:17:26.080 --> 0:17:28.280
<v Speaker 3>I love what does he keep saying.

0:17:28.280 --> 0:17:30.240
<v Speaker 1>I love that AI Judge shows out towards I love

0:17:30.280 --> 0:17:30.639
<v Speaker 1>that AI.

0:17:31.320 --> 0:17:33.719
<v Speaker 3>Oh my god, yea incredible.

0:17:34.080 --> 0:17:34.240
<v Speaker 4>You know.

0:17:34.320 --> 0:17:38.840
<v Speaker 1>The script was written by Pelky's sister and brother in law.

0:17:38.840 --> 0:17:41.160
<v Speaker 1>They fed the AI model, you know, images and video

0:17:41.280 --> 0:17:43.720
<v Speaker 1>of Pelki, but they actually wrote this script and I

0:17:43.720 --> 0:17:45.680
<v Speaker 1>thought it was quite quite moving that they would want

0:17:45.720 --> 0:17:48.240
<v Speaker 1>to go so far and above and beyond to give

0:17:48.280 --> 0:17:51.359
<v Speaker 1>a victim impact statement asking for forgiveness for the shooter.

0:17:51.800 --> 0:17:55.000
<v Speaker 4>It's incredible. Also, this is essentially a deep fake because

0:17:55.080 --> 0:17:58.200
<v Speaker 4>of their brother. And I've seen a lot of deep fakes.

0:17:58.200 --> 0:18:00.000
<v Speaker 4>This one is very good. Other than that it looked

0:18:00.240 --> 0:18:05.920
<v Speaker 4>sort of computer generated. It is computer generated, so another

0:18:05.960 --> 0:18:07.679
<v Speaker 4>deep fake news. Do you remember that picture of the

0:18:07.760 --> 0:18:10.320
<v Speaker 4>late Pope France is wearing a Montclair puffer jacket.

0:18:10.520 --> 0:18:13.880
<v Speaker 1>Yeah, this Ski Ski Sheek. It was like supreme Pope.

0:18:14.080 --> 0:18:18.120
<v Speaker 4>It was the Supreme Pope. It was AI generated but beloved. Nonetheless,

0:18:18.440 --> 0:18:20.160
<v Speaker 4>and now we sort of have a sequel to this.

0:18:20.640 --> 0:18:24.040
<v Speaker 4>The White House posted an AI generated picture of President

0:18:24.080 --> 0:18:29.560
<v Speaker 4>Trump dressed as the Pope hat robe, cross everything.

0:18:29.880 --> 0:18:31.880
<v Speaker 1>True, respect, that's right.

0:18:32.240 --> 0:18:35.080
<v Speaker 4>This post on X comes weeks after the passing of

0:18:35.119 --> 0:18:38.240
<v Speaker 4>Pope Francis and days after Trump said to media I'd

0:18:38.280 --> 0:18:42.160
<v Speaker 4>like to be Pope. There's been plenty of backlash from

0:18:42.400 --> 0:18:45.600
<v Speaker 4>state leaders to the New York archbishop, but when the

0:18:45.600 --> 0:18:50.200
<v Speaker 4>BBC asked a spokesperson for the Vatican to comment, they declined.

0:18:50.720 --> 0:18:56.080
<v Speaker 1>Finally, move over Hershey, Pennsylvania. According to The New York Times,

0:18:56.240 --> 0:19:00.479
<v Speaker 1>SpaceX is building a company town. Officially, residents of an

0:19:00.520 --> 0:19:03.320
<v Speaker 1>area surrounding SpaceX's launch site in the southern tip of

0:19:03.359 --> 0:19:06.760
<v Speaker 1>Texas have voted to create a city called star Base.

0:19:07.359 --> 0:19:09.920
<v Speaker 1>Starbase will be home to some three thy five hundred

0:19:10.000 --> 0:19:14.280
<v Speaker 1>SpaceX employees, and the proposed city boundaries include land owned

0:19:14.280 --> 0:19:17.280
<v Speaker 1>by the company and planned areas to build more housing.

0:19:17.920 --> 0:19:20.359
<v Speaker 1>SpaceX has filed paperwork with the state of Texas to

0:19:20.400 --> 0:19:23.080
<v Speaker 1>build a school, a power plant, and of course, a

0:19:23.160 --> 0:19:27.320
<v Speaker 1>sushi restaurant near He's hose. Yeah, that's why his main

0:19:27.359 --> 0:19:30.600
<v Speaker 1>residence is wild and where he voted. Apparently, the new

0:19:30.640 --> 0:19:34.959
<v Speaker 1>designation will also allow SpaceX to close a nearby beach

0:19:35.200 --> 0:19:38.359
<v Speaker 1>for rocket launches without the permission of the wider community.

0:19:38.680 --> 0:19:40.640
<v Speaker 4>And today we take you out on a joke from

0:19:40.720 --> 0:19:44.480
<v Speaker 4>care Price, which is, yes, I work at the Starbucks

0:19:44.600 --> 0:19:45.920
<v Speaker 4>in Starbase. That's good.

0:19:45.960 --> 0:19:46.600
<v Speaker 2>That's very good.

0:19:51.280 --> 0:19:53.000
<v Speaker 1>We're going to take a quick break now, and then

0:19:53.040 --> 0:19:56.639
<v Speaker 1>we're joined by the Washington Posts Drew Harwell to learn

0:19:56.720 --> 0:20:00.800
<v Speaker 1>about the three year live streaming marathon of Emily CC.

0:20:01.400 --> 0:20:18.159
<v Speaker 4>Stay with us, I can help, but wonder would I

0:20:18.320 --> 0:20:22.840
<v Speaker 4>watch someone drink a Starbucks from starbas on a live

0:20:22.840 --> 0:20:23.840
<v Speaker 4>stream or.

0:20:23.800 --> 0:20:30.439
<v Speaker 1>Eat a Starburst from Stargate. This brings us to our

0:20:30.480 --> 0:20:33.320
<v Speaker 1>next segment, which is a story I can't stop thinking about.

0:20:33.800 --> 0:20:35.680
<v Speaker 1>For a lot of teens and young adults, sitting down

0:20:35.720 --> 0:20:38.280
<v Speaker 1>and watching your favorite streamer play a video game or

0:20:38.359 --> 0:20:41.080
<v Speaker 1>live react to an event is as natural as watching

0:20:41.119 --> 0:20:44.720
<v Speaker 1>the Kardashians. And the Bravo of the live streaming world

0:20:45.000 --> 0:20:48.000
<v Speaker 1>is Twitch, a subsidiary of Amazon. Some of Twitch's most

0:20:48.000 --> 0:20:51.920
<v Speaker 1>popular streamers have tens of thousands of paid subscribers and

0:20:52.040 --> 0:20:55.880
<v Speaker 1>millions of views on their streams. They include political commentators

0:20:55.920 --> 0:21:00.399
<v Speaker 1>like Hassan Pika, gamers like Ninja, and marathon streamers like

0:21:00.520 --> 0:21:03.160
<v Speaker 1>kai sannot who will stream for hours at a time,

0:21:03.440 --> 0:21:07.960
<v Speaker 1>interacting with their subscribers and even performing requested stunts for

0:21:08.000 --> 0:21:08.760
<v Speaker 1>a fee, of course.

0:21:09.000 --> 0:21:11.960
<v Speaker 4>But there's one streamer in particular, a twenty eight year

0:21:12.000 --> 0:21:15.040
<v Speaker 4>old Texas woman who goes by the username Emily CC,

0:21:15.560 --> 0:21:18.480
<v Speaker 4>who has taken this concept of the live stream marathon

0:21:18.760 --> 0:21:21.520
<v Speaker 4>to a whole different level. For the past three years,

0:21:21.640 --> 0:21:24.560
<v Speaker 4>Emily has streamed her life twenty four hours a day,

0:21:24.840 --> 0:21:28.639
<v Speaker 4>seven days a week. She streams while driving, sleeping, shopping,

0:21:28.720 --> 0:21:31.800
<v Speaker 4>and only disappears from the camera to use the restroom.

0:21:32.320 --> 0:21:35.240
<v Speaker 1>As you can imagine, it is a huge sacrifice to

0:21:35.240 --> 0:21:38.080
<v Speaker 1>broadcast your life NonStop. I think I read the last

0:21:38.119 --> 0:21:40.520
<v Speaker 1>time she went on a date was seven years ago.

0:21:41.080 --> 0:21:44.480
<v Speaker 4>This to me is like peak parasocial And what surprises

0:21:44.520 --> 0:21:47.399
<v Speaker 4>me most is that she has over three hundred and

0:21:47.560 --> 0:21:49.040
<v Speaker 4>twenty thousand followers.

0:21:49.280 --> 0:21:53.520
<v Speaker 1>Yeah, it's part social experiment, it's part next generation reality TV,

0:21:54.080 --> 0:21:56.879
<v Speaker 1>it's part monetizing your own life with the hustle, and

0:21:56.920 --> 0:22:00.600
<v Speaker 1>it encapsulates everything you said in terms of this increasingly personal,

0:22:00.880 --> 0:22:03.800
<v Speaker 1>parasocial way that people interact with other people they don't

0:22:03.880 --> 0:22:08.240
<v Speaker 1>know online. And recently, The Washington Post published a profile

0:22:08.280 --> 0:22:10.960
<v Speaker 1>of EMILYCC and with thrilled to have the author, the

0:22:11.000 --> 0:22:14.119
<v Speaker 1>technology reporter Drew Harwell here with us today, Drew, Welcome

0:22:14.160 --> 0:22:16.280
<v Speaker 1>to tech stuff. Thanks for having me. So I actually

0:22:16.280 --> 0:22:20.040
<v Speaker 1>have Twitch dot tv slash EMILYCC open in front of

0:22:20.040 --> 0:22:23.680
<v Speaker 1>me right now. Emily is unfortunately asleep while her dog

0:22:23.880 --> 0:22:25.639
<v Speaker 1>is awake in the crate in front of her bed,

0:22:26.040 --> 0:22:28.240
<v Speaker 1>and she has the subhead on her Twitch. I'm in

0:22:28.280 --> 0:22:33.000
<v Speaker 1>an article watch post exclamation mark, Social record exclamation mark.

0:22:33.119 --> 0:22:36.000
<v Speaker 1>So evidently she wasn't too upset with your reporting. But

0:22:36.040 --> 0:22:36.960
<v Speaker 1>how did this come about?

0:22:37.440 --> 0:22:40.240
<v Speaker 2>I cover creators to the post And one day I

0:22:40.359 --> 0:22:43.280
<v Speaker 2>was just sort of, you know, procrastinating on X and

0:22:43.320 --> 0:22:46.560
<v Speaker 2>I saw this clip of Kai Sanai. He's like the

0:22:46.600 --> 0:22:49.199
<v Speaker 2>biggest star there is on Twitch. He was doing this

0:22:49.280 --> 0:22:53.200
<v Speaker 2>month long stream called Mafia than Io from his mansion

0:22:53.280 --> 0:22:55.560
<v Speaker 2>and between a couple of his stunts, they were just

0:22:55.600 --> 0:22:57.359
<v Speaker 2>kind of sitting around the computer and they were like, hey,

0:22:57.440 --> 0:23:01.200
<v Speaker 2>let's look up the longest streaming which person we can,

0:23:01.720 --> 0:23:04.520
<v Speaker 2>And they pulled up Emily and she was just shocked,

0:23:04.560 --> 0:23:06.800
<v Speaker 2>right because she was at home, like playing some goofy

0:23:06.880 --> 0:23:10.080
<v Speaker 2>video game and they both had this connection and she

0:23:10.240 --> 0:23:14.040
<v Speaker 2>was crying and Kai was really blown away, and she

0:23:14.320 --> 0:23:16.520
<v Speaker 2>talked about, you know, how she had been streaming for

0:23:16.560 --> 0:23:19.800
<v Speaker 2>three years twenty four to seven, never stopped, how she

0:23:19.920 --> 0:23:22.560
<v Speaker 2>was so tired, and yet she felt like she couldn't

0:23:22.640 --> 0:23:24.600
<v Speaker 2>quit the stream because she was so committed to it.

0:23:24.800 --> 0:23:27.000
<v Speaker 2>And it just struck me as such a fascinating human

0:23:27.040 --> 0:23:30.240
<v Speaker 2>story because the things she has to do to abide

0:23:30.240 --> 0:23:33.840
<v Speaker 2>by this like crazy challenge are wild, but to just

0:23:33.880 --> 0:23:39.200
<v Speaker 2>a great example of how inhuman the demands for streamers

0:23:39.240 --> 0:23:41.240
<v Speaker 2>can be, right. I mean, these are people who really

0:23:41.280 --> 0:23:43.440
<v Speaker 2>want to stand out on the Internet, and to do so,

0:23:43.480 --> 0:23:46.680
<v Speaker 2>they have to push themselves to the limits, and they

0:23:46.720 --> 0:23:49.280
<v Speaker 2>do so not knowing whether it'll pay off, not knowing

0:23:49.280 --> 0:23:51.960
<v Speaker 2>whether they'll even be streaming to anybody, or just you know,

0:23:52.119 --> 0:23:54.480
<v Speaker 2>five people and just sort of wasted time. So just

0:23:54.520 --> 0:23:56.520
<v Speaker 2>struck me as, you know, a fascinating example of so

0:23:56.560 --> 0:23:58.640
<v Speaker 2>many things we have to deal with on the modern Internet.

0:23:58.880 --> 0:24:01.560
<v Speaker 1>How did you persuade her to sit? First? Story? And

0:24:01.560 --> 0:24:03.119
<v Speaker 1>then will you in the twitch? While you were doing

0:24:03.200 --> 0:24:04.439
<v Speaker 1>your reporting, I guess you were.

0:24:04.600 --> 0:24:07.320
<v Speaker 2>So I'll start with her. I just reached out to her,

0:24:07.359 --> 0:24:10.919
<v Speaker 2>you know, I'd like doing profiles on creators, influencers and

0:24:10.960 --> 0:24:13.679
<v Speaker 2>the creator economy. I'd like doing narrative journalism, and so

0:24:13.720 --> 0:24:15.280
<v Speaker 2>I reach out to them and say, hey, just let

0:24:15.280 --> 0:24:17.280
<v Speaker 2>me tell your story. I want to understand you. I

0:24:17.320 --> 0:24:20.159
<v Speaker 2>want our readers to understand you. We have a pretty

0:24:20.200 --> 0:24:22.240
<v Speaker 2>old reader base, so a lot of this stuff is

0:24:22.320 --> 0:24:23.840
<v Speaker 2>very new to them. But I think, you know, in

0:24:23.840 --> 0:24:25.880
<v Speaker 2>my mind, I always see them as labor stories. These

0:24:25.920 --> 0:24:29.600
<v Speaker 2>are people who see the Internet as a career and

0:24:29.960 --> 0:24:33.320
<v Speaker 2>you know, the workplace for them is their home and

0:24:33.359 --> 0:24:35.280
<v Speaker 2>the Internet, and they don't really have a lot of

0:24:35.359 --> 0:24:39.680
<v Speaker 2>labor protections. They work for faceless companies who they hope

0:24:39.720 --> 0:24:42.840
<v Speaker 2>to make money from, but who basically don't care if

0:24:42.840 --> 0:24:44.679
<v Speaker 2>they live or die, right because there's always going to

0:24:44.680 --> 0:24:46.960
<v Speaker 2>be another twenty three year old streamer. So yeah, I

0:24:47.080 --> 0:24:49.080
<v Speaker 2>just took reaching out to Emily, and you know, she

0:24:49.240 --> 0:24:52.960
<v Speaker 2>was very game, and it was funny because everything I

0:24:53.040 --> 0:24:55.000
<v Speaker 2>talked with her about was on stream and it was

0:24:55.000 --> 0:24:58.520
<v Speaker 2>a really new experience for crazy, you know, it was crazy.

0:24:58.760 --> 0:25:01.040
<v Speaker 2>It was great. When I do these stories, I have

0:25:01.119 --> 0:25:03.200
<v Speaker 2>a kind of pre interview phase where I talked to

0:25:03.240 --> 0:25:05.720
<v Speaker 2>them over the phone. I walked them through this whole

0:25:05.760 --> 0:25:09.159
<v Speaker 2>weird experience of having a reporter shadow them, and so

0:25:09.200 --> 0:25:11.479
<v Speaker 2>we did some phone calls, we did some video calls

0:25:11.520 --> 0:25:14.920
<v Speaker 2>over Discord, which is kind of like a twitch communication

0:25:15.040 --> 0:25:17.720
<v Speaker 2>platform of choice. And then yeah, of course I spent

0:25:17.800 --> 0:25:20.360
<v Speaker 2>time with her in Austin. All of it was live streamed,

0:25:20.520 --> 0:25:23.480
<v Speaker 2>and so I could see in the chat as a

0:25:23.560 --> 0:25:26.560
<v Speaker 2>thousand people were watching. They were commenting on every question

0:25:26.600 --> 0:25:28.919
<v Speaker 2>I was asking, and you know, I'm asking sensitive questions

0:25:28.920 --> 0:25:32.880
<v Speaker 2>about like her lack of sex life, her bad experiences

0:25:32.880 --> 0:25:36.000
<v Speaker 2>with her parents, and how depressed she is. And this

0:25:36.119 --> 0:25:39.119
<v Speaker 2>whole time, the commenters are like either making fun of

0:25:39.160 --> 0:25:40.760
<v Speaker 2>the question or saying like, oh, well, I knew you

0:25:40.800 --> 0:25:43.080
<v Speaker 2>could ask about that, or you know, if I ask

0:25:43.160 --> 0:25:45.760
<v Speaker 2>a nice question, they're like, oh w like when for

0:25:45.880 --> 0:25:48.159
<v Speaker 2>mister Washington Post, or they'd call me unk as in

0:25:48.280 --> 0:25:51.879
<v Speaker 2>like uncle, like the old guy. So it was just

0:25:51.960 --> 0:25:54.520
<v Speaker 2>like so funny, and you know, for her, it was

0:25:54.560 --> 0:25:56.919
<v Speaker 2>like the most usual, normal thing in the world to

0:25:56.920 --> 0:25:58.960
<v Speaker 2>have people just commenting on that. But actually, when I

0:25:59.040 --> 0:26:01.080
<v Speaker 2>was in Austin with her, she stepped the way to

0:26:01.119 --> 0:26:03.200
<v Speaker 2>the bathroom for a minute and I was just sitting

0:26:03.200 --> 0:26:05.360
<v Speaker 2>alone in front of her computer while everybody was still

0:26:05.400 --> 0:26:08.720
<v Speaker 2>watching me. Everybody was posting these comments, and I felt

0:26:08.760 --> 0:26:11.680
<v Speaker 2>like my face flush. It just it's such an unusual

0:26:11.720 --> 0:26:14.399
<v Speaker 2>experience to have so many people watching you. And I

0:26:14.480 --> 0:26:16.919
<v Speaker 2>really felt in that moment like I understood more of

0:26:16.920 --> 0:26:20.560
<v Speaker 2>what she put herself through. Our lizard brains are not

0:26:20.880 --> 0:26:24.359
<v Speaker 2>built to process this amount of attention at all times,

0:26:24.400 --> 0:26:26.399
<v Speaker 2>and yet that was just normal for her, So it

0:26:26.400 --> 0:26:27.920
<v Speaker 2>gave me a good sense of what she has to

0:26:27.960 --> 0:26:28.359
<v Speaker 2>go through.

0:26:28.840 --> 0:26:32.720
<v Speaker 4>That's an incredible image, just imagining the journalist as the

0:26:32.760 --> 0:26:36.240
<v Speaker 4>subject moves away, sort of doing exactly what the subject

0:26:36.320 --> 0:26:39.560
<v Speaker 4>is used to doing, and just yes looked at in

0:26:39.600 --> 0:26:40.000
<v Speaker 4>that way.

0:26:40.560 --> 0:26:42.840
<v Speaker 2>It was wild. I mean you could basically still pull

0:26:42.920 --> 0:26:44.639
<v Speaker 2>up the clips now with me with her and like

0:26:44.880 --> 0:26:47.439
<v Speaker 2>petting her dog. You know, it's to see it on

0:26:47.480 --> 0:26:49.040
<v Speaker 2>the other side of the screen and to see that

0:26:49.119 --> 0:26:51.439
<v Speaker 2>place where she lives, not just in the box on

0:26:51.480 --> 0:26:53.240
<v Speaker 2>my monitor, but actually in real life.

0:26:53.280 --> 0:26:55.199
<v Speaker 1>It was like it's like you got to watch The

0:26:55.240 --> 0:26:57.280
<v Speaker 1>Truman Show and then play a character in it for

0:26:57.320 --> 0:26:59.880
<v Speaker 1>a moment and then leave again. Talk about the record.

0:27:00.320 --> 0:27:04.240
<v Speaker 1>This is as of Friday May ninth, How long will

0:27:04.280 --> 0:27:05.320
<v Speaker 1>Emily have been doing this for?

0:27:05.960 --> 0:27:09.000
<v Speaker 2>She has been online streaming twenty four to seven for

0:27:09.520 --> 0:27:12.760
<v Speaker 2>one two hundred and seventy nine days, and that's twenty

0:27:12.800 --> 0:27:14.800
<v Speaker 2>four to seven. You know, she does go to sleep,

0:27:14.920 --> 0:27:17.159
<v Speaker 2>she takes showers, you know, there's stuff when she's not

0:27:17.320 --> 0:27:19.600
<v Speaker 2>on camera, but all of that the camera has been

0:27:19.600 --> 0:27:21.800
<v Speaker 2>on recording and you can actually see in the data

0:27:21.800 --> 0:27:24.800
<v Speaker 2>it's wild. Like nobody really attempts that. It is a

0:27:24.840 --> 0:27:27.240
<v Speaker 2>crazy record, probably for good reason. But there are a

0:27:27.280 --> 0:27:31.160
<v Speaker 2>lot of marathon streamers who do long streams a month,

0:27:31.280 --> 0:27:34.840
<v Speaker 2>a week, two months, and they put themselves through these

0:27:35.040 --> 0:27:38.600
<v Speaker 2>wild challenges right where they'll lock themselves into a closet

0:27:38.720 --> 0:27:41.840
<v Speaker 2>or like ty Sinai, he basically created his own circus

0:27:41.840 --> 0:27:45.520
<v Speaker 2>with over like stunts and celebrity cameos, and you know,

0:27:45.560 --> 0:27:48.240
<v Speaker 2>it's a really interesting kind of entertainment because we're used

0:27:48.280 --> 0:27:50.840
<v Speaker 2>to these disparate blocks of like I watch a TV

0:27:50.880 --> 0:27:53.960
<v Speaker 2>show for thirty minutes, but these streamers, like they foster

0:27:54.080 --> 0:27:57.560
<v Speaker 2>that parasocial relationship with people where it's like my fans

0:27:57.560 --> 0:27:59.399
<v Speaker 2>are going to wake up, They're going to turn on

0:27:59.480 --> 0:28:01.240
<v Speaker 2>my Twitch, They're going to see what I'm doing. They're

0:28:01.240 --> 0:28:02.800
<v Speaker 2>going to watch me all day. They're just going to

0:28:02.880 --> 0:28:06.240
<v Speaker 2>have me in a tab on their computer thinking about me.

0:28:06.280 --> 0:28:07.640
<v Speaker 2>And some of the people I talk to who were

0:28:07.680 --> 0:28:10.840
<v Speaker 2>Emily's fans. They would go to sleep listening to Emily's voice,

0:28:11.240 --> 0:28:14.080
<v Speaker 2>and she was the background noise of their life. And

0:28:14.520 --> 0:28:16.760
<v Speaker 2>the stuff Emily puts herself through is I think fascinating.

0:28:16.760 --> 0:28:19.800
<v Speaker 2>But also these people who devote their lives to her

0:28:19.840 --> 0:28:22.000
<v Speaker 2>are really interesting too, because they really do see Emily

0:28:22.000 --> 0:28:25.359
<v Speaker 2>as a friend. And the more time I spent with Emily,

0:28:25.400 --> 0:28:27.639
<v Speaker 2>the more I got it. If I'm going to be

0:28:27.640 --> 0:28:31.160
<v Speaker 2>spending a lot of time alone by myself, it makes

0:28:31.160 --> 0:28:33.080
<v Speaker 2>sense to just have this person kind of there. It's

0:28:33.080 --> 0:28:34.600
<v Speaker 2>sort of like there's a person in the room, like

0:28:34.600 --> 0:28:37.800
<v Speaker 2>I have a roommate, and you know, if I can

0:28:37.840 --> 0:28:39.720
<v Speaker 2>relate to somebody like Emily, if I can relate to

0:28:39.720 --> 0:28:42.200
<v Speaker 2>the people I see on TV, why wouldn't I want

0:28:42.200 --> 0:28:45.120
<v Speaker 2>them around all the time. So you kind of get

0:28:45.320 --> 0:28:48.520
<v Speaker 2>where it comes from. We can kind of like scrutinize

0:28:48.760 --> 0:28:51.360
<v Speaker 2>are these real relationships? Are these real friendships? Like? Are

0:28:51.360 --> 0:28:51.600
<v Speaker 2>they real?

0:28:51.720 --> 0:28:51.880
<v Speaker 1>You know?

0:28:52.040 --> 0:28:54.760
<v Speaker 2>Is this just like an illusion? But I think people

0:28:54.800 --> 0:28:56.960
<v Speaker 2>do kind of get something from it, and I think

0:28:57.000 --> 0:29:00.680
<v Speaker 2>it's kind of interesting to understand the gift and the

0:29:00.720 --> 0:29:02.520
<v Speaker 2>curse of how this stuff comes together.

0:29:02.880 --> 0:29:04.840
<v Speaker 4>Can you just talk a little bit about how she

0:29:04.920 --> 0:29:08.200
<v Speaker 4>got started doing this because it started differently than it

0:29:08.240 --> 0:29:08.640
<v Speaker 4>is now.

0:29:09.200 --> 0:29:11.280
<v Speaker 2>So she was an only child. She grew up you know,

0:29:11.320 --> 0:29:14.880
<v Speaker 2>on screens, watching TV shows and video games. She was nineteen,

0:29:14.960 --> 0:29:18.280
<v Speaker 2>she was working at a CBS as a cashier, not

0:29:18.360 --> 0:29:20.760
<v Speaker 2>really knowing what she wanted to do with her life.

0:29:20.840 --> 0:29:22.760
<v Speaker 2>A lot of her friends had moved away. She kind

0:29:22.800 --> 0:29:24.520
<v Speaker 2>of stayed home. She didn't have a lot of money.

0:29:25.280 --> 0:29:28.480
<v Speaker 2>She had a boyfriend who was obsessed with playing video games,

0:29:29.000 --> 0:29:31.080
<v Speaker 2>and she would go over to his house and kind

0:29:31.080 --> 0:29:34.239
<v Speaker 2>of bring her laptop and basically entertain herself. Why he

0:29:34.320 --> 0:29:38.400
<v Speaker 2>was busy gaming, and I think basically to put her off,

0:29:38.880 --> 0:29:41.360
<v Speaker 2>he said, you know, why don't you like stream yourself

0:29:41.360 --> 0:29:43.680
<v Speaker 2>on Twitch? Like you've got no friends, right, Like you

0:29:43.800 --> 0:29:45.800
<v Speaker 2>just do your own thing on the internet. And she

0:29:45.880 --> 0:29:47.840
<v Speaker 2>saw that as like, Okay, maybe this is a way

0:29:47.880 --> 0:29:51.040
<v Speaker 2>to build friendships and make friends, and so she started

0:29:51.040 --> 0:29:53.640
<v Speaker 2>like a lot of streamers do, where she was playing

0:29:53.720 --> 0:29:58.400
<v Speaker 2>you know, World of Warcraft, a multiplayer games and recording

0:29:58.440 --> 0:30:00.680
<v Speaker 2>her face in the box on the corn the screen.

0:30:00.880 --> 0:30:02.920
<v Speaker 2>And you can go back and actually see the statistics

0:30:02.960 --> 0:30:05.400
<v Speaker 2>of her first streams, like nobody was watching, right, A

0:30:05.440 --> 0:30:08.680
<v Speaker 2>couple people here and there, and she just kept doing

0:30:08.720 --> 0:30:11.000
<v Speaker 2>it and she felt I think, a sense of purpose

0:30:11.040 --> 0:30:14.000
<v Speaker 2>from it because she wasn't getting purpose from her school,

0:30:14.480 --> 0:30:17.040
<v Speaker 2>wasn't really feeling it in her job, and this was

0:30:17.080 --> 0:30:19.080
<v Speaker 2>something that she could do on her own, devote her

0:30:19.120 --> 0:30:21.280
<v Speaker 2>life to, and she just kept doing it and doing

0:30:21.360 --> 0:30:23.040
<v Speaker 2>it and doing it. And this happens with a lot

0:30:23.080 --> 0:30:25.880
<v Speaker 2>of creators where you know they are really driven to

0:30:26.600 --> 0:30:28.960
<v Speaker 2>be the best they can be, and their computer is

0:30:29.000 --> 0:30:31.160
<v Speaker 2>always there, their webcam is always there. So she just

0:30:31.240 --> 0:30:33.840
<v Speaker 2>really kind of fell into it and now jumped to

0:30:34.520 --> 0:30:37.520
<v Speaker 2>three years later, it has become her life and you know,

0:30:37.600 --> 0:30:39.800
<v Speaker 2>she doesn't even really know a way to stop because

0:30:39.800 --> 0:30:42.440
<v Speaker 2>it's been so so critical to how she lives.

0:30:43.520 --> 0:30:45.360
<v Speaker 4>And the numbers are important, but I want to also

0:30:45.400 --> 0:30:48.560
<v Speaker 4>talk about the money, like she has paying subscribers, but

0:30:48.600 --> 0:30:50.760
<v Speaker 4>can she actually live on this wage?

0:30:51.240 --> 0:30:52.880
<v Speaker 2>Let me break down kind of the revenue of how

0:30:52.880 --> 0:30:55.400
<v Speaker 2>this works for creators, because it is really interesting. I

0:30:55.400 --> 0:30:59.200
<v Speaker 2>think she can make a living wage. She's not a millionaire.

0:30:59.200 --> 0:31:01.719
<v Speaker 2>There is a class of people who are millionaires on Twitch,

0:31:02.600 --> 0:31:05.080
<v Speaker 2>like a lot of creator platforms, it's a one percent problem.

0:31:05.080 --> 0:31:06.880
<v Speaker 3>There's the one percent of Twitch.

0:31:06.800 --> 0:31:08.959
<v Speaker 2>Totally kind of like the one percent of Hollywood, right,

0:31:08.960 --> 0:31:11.720
<v Speaker 2>and the one percent of Major League sports where there's

0:31:12.120 --> 0:31:15.320
<v Speaker 2>a lot of people who just basically straight by. She's

0:31:15.440 --> 0:31:17.760
<v Speaker 2>kind of I would say, maybe the upper middle class.

0:31:17.800 --> 0:31:21.640
<v Speaker 2>It sounds like based off of her following, she makes

0:31:21.680 --> 0:31:25.360
<v Speaker 2>probably around five thousand dollars a month, maybe more, maybe

0:31:25.360 --> 0:31:28.400
<v Speaker 2>ten thousand dollars a month, so it's nothing to sneer at.

0:31:28.800 --> 0:31:31.880
<v Speaker 2>And on Twitch, if you get a number of followers,

0:31:32.080 --> 0:31:35.080
<v Speaker 2>you can get a share of the subscriptions. People pay

0:31:35.720 --> 0:31:39.200
<v Speaker 2>Twitch six dollars a month to subscribe to her channel.

0:31:39.240 --> 0:31:41.520
<v Speaker 2>You can watch her for free, but if you subscribe,

0:31:41.560 --> 0:31:45.600
<v Speaker 2>you get special emojis, you can you know, send her messages.

0:31:45.640 --> 0:31:48.680
<v Speaker 2>You get these little perks of subscriptions. So there's that.

0:31:48.880 --> 0:31:51.680
<v Speaker 2>Then on Twitch, people can donate to you outright. They

0:31:51.720 --> 0:31:54.760
<v Speaker 2>can give you tips. A lot of times people will

0:31:55.240 --> 0:31:57.880
<v Speaker 2>drop into your stream, maybe make fun of you or

0:31:58.000 --> 0:32:00.880
<v Speaker 2>do a crazy sound effect. There's been situations where like

0:32:01.160 --> 0:32:03.040
<v Speaker 2>Emily will go out to the grocery store and an

0:32:03.040 --> 0:32:05.200
<v Speaker 2>elevator and someone will prank her by like paying a

0:32:05.240 --> 0:32:07.840
<v Speaker 2>dollar to play like a fart noise over her cell

0:32:07.840 --> 0:32:11.479
<v Speaker 2>phone just kind of embarrass her in person. So you know,

0:32:11.600 --> 0:32:14.640
<v Speaker 2>she lives alone. She lives in an apartment. She doesn't

0:32:14.680 --> 0:32:16.840
<v Speaker 2>really do anything, but she makes more than she would

0:32:16.840 --> 0:32:19.200
<v Speaker 2>have made at CBS. And this is something she talked

0:32:19.200 --> 0:32:22.520
<v Speaker 2>about where she feels like this is capitalism. She's just

0:32:22.600 --> 0:32:25.680
<v Speaker 2>making a living. However, she feels like she can you know,

0:32:25.840 --> 0:32:28.880
<v Speaker 2>she felt like, I could finish at community college and

0:32:29.000 --> 0:32:31.440
<v Speaker 2>stay working at CVS, or I could do this other

0:32:31.520 --> 0:32:34.200
<v Speaker 2>risky thing, And why would I not do it? Because

0:32:34.200 --> 0:32:36.680
<v Speaker 2>I'm making more than I ever would have done, you know,

0:32:36.840 --> 0:32:38.120
<v Speaker 2>moving groceries around.

0:32:38.280 --> 0:32:40.720
<v Speaker 1>What's it costing her to do this? I don't mean

0:32:40.720 --> 0:32:42.800
<v Speaker 1>financially so much as personally.

0:32:43.520 --> 0:32:46.320
<v Speaker 2>Yeah, it's costing her a lot, I think, And she

0:32:46.360 --> 0:32:49.760
<v Speaker 2>talks about this pretty openly. You know, for three years

0:32:49.760 --> 0:32:52.880
<v Speaker 2>she has devoted her life to being online all the time.

0:32:53.000 --> 0:32:54.640
<v Speaker 2>So there's kind of the tangible stuff.

0:32:54.720 --> 0:32:54.880
<v Speaker 4>Right.

0:32:55.200 --> 0:32:59.760
<v Speaker 2>She wasn't flying anywhere because then she would be offline

0:32:59.760 --> 0:33:02.160
<v Speaker 2>for a little bit, so she couldn't stream. She was

0:33:02.200 --> 0:33:05.400
<v Speaker 2>saying no to wedding invitations, right. She's talked about she

0:33:05.440 --> 0:33:07.600
<v Speaker 2>went to like a club with a friend one time

0:33:07.640 --> 0:33:09.680
<v Speaker 2>and the service was really bad in the club, so

0:33:09.720 --> 0:33:12.400
<v Speaker 2>she had to leave. And she's talked about losing friends

0:33:12.440 --> 0:33:15.760
<v Speaker 2>because not everybody wants to be on a stream with

0:33:16.160 --> 0:33:18.640
<v Speaker 2>hanging out with her. She doesn't have a good relationship

0:33:18.680 --> 0:33:21.440
<v Speaker 2>with her parents. Her parents don't really understand what she's doing.

0:33:21.520 --> 0:33:23.400
<v Speaker 2>They don't want to be on stream. So there's a

0:33:23.440 --> 0:33:26.120
<v Speaker 2>lot of kind of like human losses. But I think also,

0:33:26.280 --> 0:33:30.120
<v Speaker 2>you know, she started to wonder just about the opportunity cost.

0:33:30.480 --> 0:33:35.440
<v Speaker 2>When you're devoting twenty four seven to your stream, you're

0:33:35.440 --> 0:33:37.120
<v Speaker 2>not doing a bunch of other things that might make

0:33:37.160 --> 0:33:40.120
<v Speaker 2>you happier, might lead to something else. And so you know,

0:33:40.200 --> 0:33:43.480
<v Speaker 2>she's still making those judgments every day, but there's a

0:33:43.520 --> 0:33:45.840
<v Speaker 2>lot that goes into it that she's had to sacrifice

0:33:46.000 --> 0:33:48.840
<v Speaker 2>just to be part of this crowd.

0:33:49.720 --> 0:33:52.040
<v Speaker 1>Why do you put this in let's say the history

0:33:52.080 --> 0:33:56.000
<v Speaker 1>of like reality TV experiments and as a famous Doky

0:33:56.080 --> 0:33:59.280
<v Speaker 1>series recently about the Japanese man who lived in that

0:33:59.440 --> 0:34:02.120
<v Speaker 1>room being broadcast for like two years and you know,

0:34:02.600 --> 0:34:05.000
<v Speaker 1>was really at the edge of his sanity by the

0:34:05.080 --> 0:34:07.800
<v Speaker 1>end of that experience. And the contestant, right, there's a

0:34:07.840 --> 0:34:10.399
<v Speaker 1>woman you mentioned in your piece called Jennifer Ringley who

0:34:10.800 --> 0:34:12.920
<v Speaker 1>had a continuous broadcast of her life back in the

0:34:12.960 --> 0:34:16.240
<v Speaker 1>early two thousands. I guess what's new and what's old

0:34:16.280 --> 0:34:18.160
<v Speaker 1>and what does all of this say about us?

0:34:18.640 --> 0:34:22.080
<v Speaker 2>So I find them really interesting examples because it shows

0:34:22.160 --> 0:34:24.839
<v Speaker 2>that some of this is not new, and I think

0:34:24.840 --> 0:34:29.680
<v Speaker 2>it speaks to this human impulse in us that desires

0:34:29.719 --> 0:34:33.560
<v Speaker 2>to watch people be people and to just look at

0:34:33.560 --> 0:34:36.239
<v Speaker 2>them through the glass. It's why we watch reality TV.

0:34:36.560 --> 0:34:38.600
<v Speaker 2>So why I watch reality TV, right, I want to

0:34:38.640 --> 0:34:43.440
<v Speaker 2>see people interact in these situations and process that. I

0:34:43.480 --> 0:34:46.800
<v Speaker 2>think what's changed from that is that it has become

0:34:46.840 --> 0:34:50.239
<v Speaker 2>normalized to the point where we are all creators in

0:34:50.239 --> 0:34:52.560
<v Speaker 2>a way. Right. We use social media all the time,

0:34:52.680 --> 0:34:56.480
<v Speaker 2>we perform for our family and friends on the internet.

0:34:56.800 --> 0:35:00.239
<v Speaker 2>It's just become something that seems not so crazy more.

0:35:00.280 --> 0:35:02.280
<v Speaker 2>And I think it's kind of expanded the Overton window

0:35:02.320 --> 0:35:04.920
<v Speaker 2>on what we feel is acceptable. When you know, one

0:35:04.960 --> 0:35:06.600
<v Speaker 2>hundred years ago, it would have been crazy that we

0:35:06.640 --> 0:35:09.960
<v Speaker 2>would ever watch somebody in all of these private moments

0:35:10.320 --> 0:35:11.560
<v Speaker 2>or even make money off of it.

0:35:11.719 --> 0:35:16.200
<v Speaker 1>There's also this kind of algorithmic bias towards extreme content, right,

0:35:16.239 --> 0:35:19.239
<v Speaker 1>But there's this interesting element of this story where the

0:35:19.280 --> 0:35:24.320
<v Speaker 1>algorithmic bias towards extreme content mix people behave or incentivizes

0:35:24.360 --> 0:35:27.720
<v Speaker 1>people to behave in more extreme ways. In real life,

0:35:28.000 --> 0:35:30.680
<v Speaker 1>there is a British only fans creator who you mentioned

0:35:30.680 --> 0:35:33.920
<v Speaker 1>in your story called Lily Phillips, who ran a stunt

0:35:33.920 --> 0:35:35.880
<v Speaker 1>where she slept I think, with one hundred men in

0:35:35.920 --> 0:35:38.240
<v Speaker 1>twenty four hours and it kind of broke the internet

0:35:38.280 --> 0:35:41.280
<v Speaker 1>a few months ago, and then another sort of YouTube

0:35:41.280 --> 0:35:44.160
<v Speaker 1>creator made a kind of interview piece with her where

0:35:44.480 --> 0:35:47.000
<v Speaker 1>she broke down, which kind of broke the internet a

0:35:47.000 --> 0:35:49.160
<v Speaker 1>second time. Can you tell us a bit about how

0:35:49.160 --> 0:35:50.640
<v Speaker 1>it intersects with this story.

0:35:51.080 --> 0:35:52.680
<v Speaker 2>Yeah, I mean we have to remember this is a

0:35:52.960 --> 0:35:56.040
<v Speaker 2>this is a business, right, and with only fans with Twitch,

0:35:56.080 --> 0:35:59.160
<v Speaker 2>with a lot of social media, these people are competing

0:35:59.480 --> 0:36:02.239
<v Speaker 2>for the currency of the Internet, which is attention. Right,

0:36:02.560 --> 0:36:05.840
<v Speaker 2>the only way to get attention versus all of the

0:36:06.000 --> 0:36:09.399
<v Speaker 2>thousands of other people you're competing with is to raise

0:36:09.440 --> 0:36:12.279
<v Speaker 2>the bar, to do something crazier, to do something that

0:36:12.320 --> 0:36:15.160
<v Speaker 2>people can't look away from. I mean, you see it

0:36:15.160 --> 0:36:18.800
<v Speaker 2>on x formerly Twitter right, where people will say crazy,

0:36:18.920 --> 0:36:23.080
<v Speaker 2>outlandish conspiracy theories and they want to outdo the next

0:36:23.360 --> 0:36:27.319
<v Speaker 2>right wing influencer by saying something crazier because they know

0:36:27.440 --> 0:36:29.520
<v Speaker 2>that it doesn't matter if what they're saying is right,

0:36:29.680 --> 0:36:32.560
<v Speaker 2>it matters that it pisses people off. And engages people,

0:36:32.719 --> 0:36:35.319
<v Speaker 2>gets people to watch them. What if I'm kind of

0:36:35.400 --> 0:36:39.280
<v Speaker 2>unusual about Twitch? Is that unlike with TikTok, where people

0:36:39.320 --> 0:36:42.920
<v Speaker 2>really want like the most just gut punching five second

0:36:43.000 --> 0:36:46.120
<v Speaker 2>video that they can make, Twitch really relishes and being

0:36:46.200 --> 0:36:48.920
<v Speaker 2>this long form thing that people can watch for six hours.

0:36:49.080 --> 0:36:52.320
<v Speaker 2>So there's a lot of like banal content on Twitch

0:36:52.640 --> 0:36:55.120
<v Speaker 2>that you wonder like why would somebody watch somebody playing

0:36:55.200 --> 0:37:00.600
<v Speaker 2>video games or playing chess, or studying or coding a

0:37:00.600 --> 0:37:03.000
<v Speaker 2>computer program, all of which is on Twitch. But then

0:37:03.040 --> 0:37:04.799
<v Speaker 2>you see people like Emily who it's kind of the

0:37:04.840 --> 0:37:07.600
<v Speaker 2>mix of just a banal kind of normal life, but

0:37:07.719 --> 0:37:10.080
<v Speaker 2>also you want to watch to see is she going

0:37:10.120 --> 0:37:12.880
<v Speaker 2>to finally quit? Is she going to reach her breaking point?

0:37:13.000 --> 0:37:16.879
<v Speaker 2>She's gone three years, Like is she going to you know,

0:37:17.080 --> 0:37:20.120
<v Speaker 2>just freak out and run away? So there's that kind

0:37:20.160 --> 0:37:23.360
<v Speaker 2>of mix of wanting to see somebody in their normal element,

0:37:23.440 --> 0:37:26.759
<v Speaker 2>but also kind of expecting something bad is going to

0:37:26.800 --> 0:37:29.120
<v Speaker 2>happen from this crazy challenge she's putting herself through.

0:37:29.520 --> 0:37:31.800
<v Speaker 4>I mean, she's talked about having a kind of end point,

0:37:31.800 --> 0:37:33.600
<v Speaker 4>like she's not just doing this to do this, she

0:37:33.640 --> 0:37:35.600
<v Speaker 4>wants to do it so that she can have a house,

0:37:36.080 --> 0:37:38.239
<v Speaker 4>and be married by the time she's thirty years old.

0:37:38.280 --> 0:37:41.600
<v Speaker 4>So do you, now having interviewed her, feel like there's

0:37:41.600 --> 0:37:45.560
<v Speaker 4>an endpoint for her and is it looking like she's

0:37:45.560 --> 0:37:47.759
<v Speaker 4>on the trajectory to have the things that she wants.

0:37:48.080 --> 0:37:52.080
<v Speaker 2>I think with Emily, she shifts her end goal out

0:37:52.320 --> 0:37:54.520
<v Speaker 2>all the time, so it's hard to know when she

0:37:54.560 --> 0:37:56.839
<v Speaker 2>will ever reach an endpoint. And she even says now

0:37:56.920 --> 0:38:00.279
<v Speaker 2>she doesn't see any reason to quit yet kind of

0:38:00.320 --> 0:38:03.320
<v Speaker 2>hears these clocks in her head of I want to

0:38:03.320 --> 0:38:05.760
<v Speaker 2>buy a house by thirty, I want to get married,

0:38:05.800 --> 0:38:09.400
<v Speaker 2>you know, all these kind of like basic societal impulses

0:38:09.440 --> 0:38:11.879
<v Speaker 2>that a lot of us here. But you know, it's

0:38:11.880 --> 0:38:13.799
<v Speaker 2>hard for her to think of like what a life

0:38:13.800 --> 0:38:16.359
<v Speaker 2>would be like not on camera. I think it would

0:38:16.360 --> 0:38:20.120
<v Speaker 2>be a big culture shock when or if it ever happens.

0:38:20.520 --> 0:38:22.359
<v Speaker 2>When you're doing something day in and day out for

0:38:22.400 --> 0:38:24.279
<v Speaker 2>three years, to be able to break away from that

0:38:24.320 --> 0:38:26.840
<v Speaker 2>will be really challenging. And you know, I tried to

0:38:26.880 --> 0:38:29.120
<v Speaker 2>press her on this point because she said she wants

0:38:29.160 --> 0:38:31.799
<v Speaker 2>to be married in a couple of years, but she

0:38:31.880 --> 0:38:34.160
<v Speaker 2>still thinks she might be streaming in five years, And

0:38:34.200 --> 0:38:37.280
<v Speaker 2>I said, well, are you going to be like pregnant

0:38:37.280 --> 0:38:40.360
<v Speaker 2>and streaming. Are you going to be like streaming your wedding? Like,

0:38:40.400 --> 0:38:43.160
<v Speaker 2>how does this work? And so I think she's still

0:38:43.160 --> 0:38:45.839
<v Speaker 2>trying to figure out what bat'll look like and if

0:38:45.880 --> 0:38:47.440
<v Speaker 2>it will work or if she'll have to kind of

0:38:47.800 --> 0:38:50.480
<v Speaker 2>bend on either the life goals she has or kind

0:38:50.480 --> 0:38:51.680
<v Speaker 2>of these twitch goals.

0:39:01.239 --> 0:39:02.799
<v Speaker 3>Drew, thank you so much for your time.

0:39:03.120 --> 0:39:03.680
<v Speaker 1>Thank you, Drew.

0:39:03.800 --> 0:39:04.799
<v Speaker 2>Yeah, thanks for having me.

0:39:25.040 --> 0:39:27.759
<v Speaker 3>That's it for this week for tech Stuff, I'm Kara Price.

0:39:27.520 --> 0:39:30.520
<v Speaker 1>And I'm os Valosan. This episode was produced by Eliza

0:39:30.560 --> 0:39:33.840
<v Speaker 1>Dennis and Victoria Domingez. It was executive produced by me,

0:39:34.200 --> 0:39:38.160
<v Speaker 1>Kara Price and Kate Osborne for Kaleidoscope and Katrina Norvel

0:39:38.239 --> 0:39:44.560
<v Speaker 1>for iHeart Podcasts. The engineer is Beheath Fraser and Jack

0:39:44.640 --> 0:39:48.080
<v Speaker 1>Insley mixed this episode. Kyle Murdoch rode Themesol.

0:39:48.200 --> 0:39:50.879
<v Speaker 4>Join us next Wednesday for tex Stuff The Story, when

0:39:50.920 --> 0:39:53.280
<v Speaker 4>we will share an in depth conversation with game designer

0:39:53.360 --> 0:39:57.279
<v Speaker 4>him Gingold about every millennial's favorite game, Simsony.

0:39:57.560 --> 0:40:00.360
<v Speaker 1>Please rate, review and reach out to us at text

0:40:00.360 --> 0:40:02.839
<v Speaker 1>aff podcast at gmail dot com. We want to hear

0:40:02.880 --> 0:40:03.239
<v Speaker 1>from you.