WEBVTT - Week in Tech: Tariffs, Ands Or Buts

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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 Osvoloshin and today Kara Price and I will bring

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<v Speaker 1>you the headlines this week, well tariffs, obviously, but also

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<v Speaker 1>a dating game. Then on Tech Support, we'll talk to

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<v Speaker 1>The Wall Street Journal's Family and Tech columnist Julie Jargon

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<v Speaker 1>about a mother's worst fear, a cry for help over

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<v Speaker 1>the phone that sounded like her youngest daughter, all of

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<v Speaker 1>that on the Weekend Tech. It's Friday, April eleventh. Kara, Hello, Hello, Hello, ohs.

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<v Speaker 2>I think I'm going to start this thing called Kara's

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<v Speaker 2>Hats of the Week. And just for people who can't

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<v Speaker 2>see me, I'm wearing a hat today that says, and

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<v Speaker 2>this is from a show called Summer Heatsie. If you

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<v Speaker 2>ever watched Summerheatsie, I'm a naughty girl with a bad habit.

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<v Speaker 1>What is the bad habit in the.

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<v Speaker 2>Show, It's for drugs. If I had preempted today's top story,

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<v Speaker 2>it would have said, with a bad habit for tariffs.

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<v Speaker 1>Uh huh. That would have been fast fashion. Indeed, that's

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<v Speaker 1>a good one. But today's news is all about quote.

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<v Speaker 1>The most beautiful word in the dictionary.

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<v Speaker 2>Well, I don't know anything about the dictionary, but I

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<v Speaker 2>looked up the word tariff with chat GPT.

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<v Speaker 1>The Dictionary twenty twenty five correct.

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<v Speaker 2>Correct, and the thesaurus and also what we'll eventually write

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<v Speaker 2>someone's wedding vesse. I asked chat Gpt what a tariff is,

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<v Speaker 2>and she responded because she's a she yea in my book.

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<v Speaker 2>In your book, a tariff is a tax or fee

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<v Speaker 2>that a government imposes on imported or exported goods. But

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<v Speaker 2>most importantly, chat Gpt says tariffs can impact the price

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<v Speaker 2>of goods, trade relationships, and the global economy.

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<v Speaker 1>Oh my prophetic soul can and do.

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<v Speaker 2>Chat Gipt was onto something there because Trump's tariff announcement

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<v Speaker 2>definitely shook up the global economy and trade relationships, and

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<v Speaker 2>everything is still evolving. I mean, there's basically a new

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<v Speaker 2>update every hour. Just this week, tariffs on about ninety

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<v Speaker 2>countries went into effect. Then Trump issued a pause on

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<v Speaker 2>most of them. But the country who's been pummeled the

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<v Speaker 2>most is China. As of Thursday midday, Trump has increased

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<v Speaker 2>tariffs on the country's imports by one hundred and twenty

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<v Speaker 2>five percent. So with everything going on, the technology industry

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<v Speaker 2>has been feeling some effects.

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<v Speaker 1>There's a headline in the Washington Post earlier this week

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<v Speaker 1>that was delicious in its understated irony. Big tech bet

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<v Speaker 1>on Trump. It's still waiting for the payoff.

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<v Speaker 2>I'm just thinking about when we first started this version

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<v Speaker 2>of tech stuff. All of those tech bros were at

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<v Speaker 2>the inauguration, and now they're all scrambling to rethink their

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<v Speaker 2>supply chains.

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<v Speaker 1>But it's also about the threat of reciprocal tariffs. And

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<v Speaker 1>in that Washington Post story, the writers quip those tech

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<v Speaker 1>giants are in another front row, lol, not the front

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<v Speaker 1>row the inauguration as targets for US trade partners looking

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<v Speaker 1>for ways to strike back at the US economy.

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<v Speaker 2>Yeah. I heard at one point the EU is considering

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<v Speaker 2>tariffs on digital products like Netflix subscriptions and Google Cloud storage,

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<v Speaker 2>which I honestly didn't even know was possible. But another

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<v Speaker 2>area of concern for the tech industry is how these

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<v Speaker 2>tariffs will affect semiconductors, because they really do power the

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<v Speaker 2>modern world. Everything from consumer tech, data centers, even cars,

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<v Speaker 2>they all use semiconductors.

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<v Speaker 1>And here's where the kind of ironies continue to abound, because,

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<v Speaker 1>of course, you know, President Trump has made AI supremacy

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<v Speaker 1>a key element of his policy for this term, and

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<v Speaker 1>so technically the tariffs announce an exemption for semiconductors, but

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<v Speaker 1>as it turns out, many of the semiconductors imported are

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<v Speaker 1>actually bundled into other products like GPU chips and service

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<v Speaker 1>to train AI models. That's per wired to have a

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<v Speaker 1>story under the headline Trump's tariffs are threatening the US

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<v Speaker 1>semiconductor revival. Wide also points out that all of the

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<v Speaker 1>machinery and the underlying materials to manufacture semiconductors here in

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<v Speaker 1>the US will become far more expensive with these tariffs

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<v Speaker 1>make it less attractive to manufacture domestically.

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<v Speaker 2>Yeah, you know this is a little bit heady, but

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<v Speaker 2>needless to say, it is a consumer tech story. You know,

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<v Speaker 2>there are many articles circulating about how these tariffs could

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<v Speaker 2>affect the price of something as ubiquitous as the iPhone.

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<v Speaker 1>Have you been stoking up for your ebase sales.

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<v Speaker 2>Of my iPhone? Oh to sell iPhones? Oh yeah, it's

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<v Speaker 2>not a bad idea. Actually, I hadn't thought about it,

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<v Speaker 2>you know. And just to give a shout out to

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<v Speaker 2>four A form Meta who we love, you know, they

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<v Speaker 2>pointed out that on Apple's own supply chain website. The

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<v Speaker 2>big beautiful bold text that overlays the video of people

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<v Speaker 2>making iPhones in a factory says, designed by Apple in California,

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<v Speaker 2>made by people everywhere. And it's true, you know, as

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<v Speaker 2>a device exemplifies globalization. The materials for the batteries come

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<v Speaker 2>from one country, the display from another. Almost every part

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<v Speaker 2>of the iPhone comes from a different country, and then

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<v Speaker 2>they are predominantly assembled in China. So if things go

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<v Speaker 2>the way they're going and tariffs on Chinese imports remain,

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<v Speaker 2>these phones could get a lot more expensive. And I'm

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<v Speaker 2>going to get the burner phone that I plan on

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<v Speaker 2>getting the summer anyway.

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<v Speaker 1>Okay, good, Yeah, Well this will be another inducement for

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<v Speaker 1>us to get dumb phones, but that that might be

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<v Speaker 1>enough for us on Tarish this week. I feel this

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<v Speaker 1>is probably something going to be coming back to again

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<v Speaker 1>and again. So time for a game.

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<v Speaker 2>I have been sitting on my hands for this entire

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<v Speaker 2>show as we talk about tariffs, to play a game

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<v Speaker 2>with you that came out last week for April Fools.

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<v Speaker 2>I will catch people up a little bit. Last week,

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<v Speaker 2>Tinder launched an in app game called The Game Game.

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<v Speaker 1>The Game Game it sounds a bit like that seventies

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<v Speaker 1>dating show, the dating game with a sprinkle of my

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<v Speaker 1>hero Neil Strauss.

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<v Speaker 2>I think they were definitely going for seventies dating show.

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<v Speaker 2>I don't think they were going for a sprinkle of

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<v Speaker 2>Neil Strauss. But that's your drama. So basically, Open AI's Chat,

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<v Speaker 2>GPT four oh and Tinder partner together to create this

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<v Speaker 2>thing called the Game Game, which allows real Tinder users

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<v Speaker 2>to enter pretend scenarios and talk to AI characters.

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<v Speaker 1>This was a meet cute between chat ChiPT and Tinder,

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<v Speaker 1>good one if you will.

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<v Speaker 2>It was a me cute between altman and Tinder. Absolutely,

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<v Speaker 2>But there's also a competitive part of the game, which

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<v Speaker 2>is that as you talk into your phone, you try

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<v Speaker 2>your best to flirt with the AI, and you get

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<v Speaker 2>points for how suave or empathetic or interesting your responses are.

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<v Speaker 2>And here's how it works. You entered a preferred scenario

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<v Speaker 2>like I'm on a train and my shoes untied and

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<v Speaker 2>a man says, miss, your shoes untied and I say, sir,

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<v Speaker 2>I'm into women. That would be the end of that.

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<v Speaker 2>But no, if I were straight, he would say, mam,

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<v Speaker 2>your shoes untied and I'd look up and it would

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<v Speaker 2>get no. But our producer Tory actually played it and

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<v Speaker 2>she talked to a character named Nathan, who was interested

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<v Speaker 2>in technology and had a Southern accent. But after their

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<v Speaker 2>conversation ended, Tinder told Tory that her replies were charming,

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<v Speaker 2>but that her conversation could have fload a little better

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<v Speaker 2>as she jumped between topics too quickly. Now, as a producer,

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<v Speaker 2>that's a great quality.

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<v Speaker 1>Yeah, exactly, short attention span. I think Tory may have

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<v Speaker 1>had it right and the and the app wrong, but

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<v Speaker 1>I would love to hear you try it.

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<v Speaker 2>My phone is ready and Tinder is downloaded. So let's

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<v Speaker 2>the game game. So what happens first is the prompt

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<v Speaker 2>comes up in the game. It's in the Tinder app.

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<v Speaker 1>Well, I mean, let's not pass over this soundtrack and

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<v Speaker 1>loving it.

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<v Speaker 2>It's fantastic.

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<v Speaker 1>This is like old New York.

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<v Speaker 2>We're going to Cafe Carlisle for a drink and a smoke. Okay,

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<v Speaker 2>I'm done, but let me read you the prompt so

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<v Speaker 2>we can start the game.

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<v Speaker 1>Okay.

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<v Speaker 2>And by the way, it lets you re roll, so

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<v Speaker 2>if you don't like the person you're introduced to, it

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<v Speaker 2>gives you another prompt, which I don't think should happen.

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<v Speaker 2>I think you should happen. But that's how Tinder works,

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<v Speaker 2>That's how chatchy be T four zero works. At a

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<v Speaker 2>bustling dog park, your curious dog eagerly runs up to Penelope,

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<v Speaker 2>a customer service representative, and starts playing with her dog.

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<v Speaker 1>How does your dog know what Penelope's job is? Oh,

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<v Speaker 1>you find that out later.

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<v Speaker 2>Hello, get my dog's like? Whoa, she's in customer service.

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<v Speaker 2>You should chase her down. No, and so my dog

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<v Speaker 2>goes up to Penelope's dog and starts playing with her dog.

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<v Speaker 2>This unexpected encounter creates the perfect excuse to strike up

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<v Speaker 2>a conversation with the one and only Penelope from Customer Service.

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<v Speaker 2>Let's go, I'm not rerolling, I'm taking my first card.

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<v Speaker 3>Well, hey, there looks like your dog's got quite a

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<v Speaker 3>bit of energy, don't they. My pup here is pretty

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<v Speaker 3>friendly too. Seems they're getting along just fine.

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<v Speaker 2>What's their name? My dog's name is Astrid Pastrid.

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<v Speaker 3>Huh, that's a fun name. Seems like an estrid. It's

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<v Speaker 3>a real social butterfly. Does she usually make friends this quick?

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<v Speaker 2>Honestly? No, your dog is the first dog she's ever

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<v Speaker 2>taken any interest in her? Well, ain't that something special?

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<v Speaker 3>Looks like they found the money today.

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<v Speaker 1>Must be a good match.

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<v Speaker 3>Maybe Astrid knows a kindred spirit when she sees one.

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<v Speaker 2>So how often do you come to the park. I've

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<v Speaker 2>tried to go to the dog park more now because

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<v Speaker 2>Astroid's gotten kind of crazy inside, so have I I mean,

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<v Speaker 2>post COVID it's really hard to get outside even now.

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<v Speaker 2>Why I hear you. It's been tough all around.

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<v Speaker 3>The fresh air and space can do wonders for both

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<v Speaker 3>you and Astro. Charleston's got a lot of beauty if

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<v Speaker 3>you take time to notice it.

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<v Speaker 1>You know.

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<v Speaker 2>Pela. Sorry, Penelte, I'm so sorry to cut you off.

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<v Speaker 3>No worries at all, I understand it. I don't want

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<v Speaker 3>to chat about the park or just need a friendly here.

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<v Speaker 3>I'm here.

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<v Speaker 2>Take care of yourself and Astrid. Penelope, would you be

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<v Speaker 2>interested in either giving me or getting Did she go away?

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<v Speaker 2>Oh you're still here, Penelope? Sorry, so Penelope, I want

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<v Speaker 2>another go But he just like girl.

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<v Speaker 1>You have no no. I like the way you dropped

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<v Speaker 1>your voice a little bit.

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<v Speaker 2>Wait, do you want to try it? We have to

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<v Speaker 2>have things to do on the show, but that's really

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<v Speaker 2>how it goes. CHATPG is kind of incredible. So guys,

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<v Speaker 2>that is the game game.

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<v Speaker 1>I love the game game. I'm also curious as to

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<v Speaker 1>why both your and Torri's match as a Southern accent is.

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<v Speaker 1>Is this a subtle kind of white loticification of society.

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<v Speaker 2>Where chat GPT four roh is just like, you know what,

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<v Speaker 2>they're getting Southern girls and that's about it, or southern boys.

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<v Speaker 2>In the case of Tory, Nathan was southern. I live

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<v Speaker 2>in New York and one of the things that I

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<v Speaker 2>saw come up and I was talking to Penelope was

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<v Speaker 2>plus plus empathetic. Now, if I was talking to New York,

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<v Speaker 2>I would have been like, yo, girl, what's up. I'm

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<v Speaker 2>talking to Penelope. I'm like, well, girl, would you like

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<v Speaker 2>to meet me at the park again?

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<v Speaker 1>I thought that you're lying about how Astroid had never

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<v Speaker 1>approached any other dogs. Was I mean that was you

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<v Speaker 1>gotta make them feel speak.

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<v Speaker 2>I hope this podcast never comes out. I love that

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<v Speaker 2>more than anything. I will be playing that all day

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<v Speaker 2>and I think I will, by the end of it

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<v Speaker 2>have a Southern accent, just to get a little bit

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<v Speaker 2>more serious about this story. You know, the Washington Post

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<v Speaker 2>reached out to the vice president of Product Growth and

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<v Speaker 2>Revenue at Tinder, and she said that the game is

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<v Speaker 2>meant to be silly and that the company quote leaned

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<v Speaker 2>into the campiness. Apparently, though, She went on to call

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<v Speaker 2>gen Z a socially anxious generation, and while the game

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<v Speaker 2>might be cringe, it's a generation that might look past

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<v Speaker 2>that if it indeed leads to a real connection.

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<v Speaker 1>I had to say, I mean, it was definitely fun

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<v Speaker 1>watching you play. I have never before myself, and I

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<v Speaker 1>didn't just time either, but I've never had a conversation

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<v Speaker 1>directly using my voice with an ali before. Was that

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<v Speaker 1>Was that a first for you or.

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<v Speaker 2>Only when I tried to scam my cousin? Actually?

0:12:11.480 --> 0:12:11.880
<v Speaker 1>Yeah, yeah?

0:12:12.040 --> 0:12:14.600
<v Speaker 2>So crazy? Is the pressure cooker that that just created

0:12:14.679 --> 0:12:16.840
<v Speaker 2>for me? Felt like there was literally a gun to

0:12:16.880 --> 0:12:18.359
<v Speaker 2>my head that was like flirt.

0:12:19.360 --> 0:12:21.880
<v Speaker 1>That's what it felt like. It's getting hot in here.

0:12:21.920 --> 0:12:24.520
<v Speaker 1>So we're going to take a quick break when we

0:12:24.559 --> 0:12:38.320
<v Speaker 1>come back some more headlines. Now to pivot back to

0:12:38.360 --> 0:12:41.640
<v Speaker 1>the headlines, We've got a few more for today, continuing

0:12:41.679 --> 0:12:45.600
<v Speaker 1>the theme of sex, deaths, and money. Well, no death, thankfully,

0:12:46.000 --> 0:12:48.520
<v Speaker 1>but we've had sex in the form of flirting now

0:12:48.559 --> 0:12:50.040
<v Speaker 1>for money taxes.

0:12:52.559 --> 0:12:55.120
<v Speaker 2>We know it's tax month, and one of the stories

0:12:55.160 --> 0:12:57.560
<v Speaker 2>has to do with two things you never want to

0:12:57.600 --> 0:13:02.600
<v Speaker 2>hear put together, which is IRS and hackathon. And of

0:13:02.679 --> 0:13:07.080
<v Speaker 2>course what does this start with the Department of Government

0:13:07.160 --> 0:13:11.200
<v Speaker 2>Efficiency is planning to stage a hackathon event. I sound

0:13:11.280 --> 0:13:14.160
<v Speaker 2>sad because I am is planning to stage a hackathon

0:13:14.200 --> 0:13:18.280
<v Speaker 2>event with the best engineers at the Internal Revenue Service.

0:13:18.600 --> 0:13:22.000
<v Speaker 2>According to Wired, DOE is planning to host dozens of

0:13:22.040 --> 0:13:24.679
<v Speaker 2>them in DC to build a mega API.

0:13:24.880 --> 0:13:28.400
<v Speaker 1>A mega API, that's actually what I read process.

0:13:28.679 --> 0:13:31.840
<v Speaker 2>It is a MEGAAPI essentially, which would make it easier

0:13:31.880 --> 0:13:36.199
<v Speaker 2>to access taxpayer data across different applications and cloud platforms.

0:13:36.240 --> 0:13:38.600
<v Speaker 1>We don't yet have a lot of details on the hackathon,

0:13:38.760 --> 0:13:41.040
<v Speaker 1>but I do hope they keep it tight because the

0:13:41.080 --> 0:13:45.200
<v Speaker 1>idea of highly sensitive tax data moving freely between what

0:13:45.240 --> 0:13:48.719
<v Speaker 1>maybe third party applications is a little frightening. There is

0:13:48.760 --> 0:13:52.200
<v Speaker 1>a broader controversy roiling the IRS. Several officials, including the

0:13:52.240 --> 0:13:56.360
<v Speaker 1>acting Commissioner, are quitting over the Trump administration's insistence that

0:13:56.480 --> 0:14:01.880
<v Speaker 1>the agency disclosed taxpayer information to Immigration and Customs Enforcement.

0:14:02.160 --> 0:14:05.719
<v Speaker 1>The IRIS has typically kept taxpay information confidential, even from

0:14:05.840 --> 0:14:10.920
<v Speaker 1>other government agencies, and that includes information submitted by undocumented immigrants.

0:14:11.360 --> 0:14:13.960
<v Speaker 1>But in a new agreement which appeared redacted in a

0:14:14.000 --> 0:14:17.480
<v Speaker 1>court filing, ICE officials can now ask the IRS for

0:14:17.520 --> 0:14:21.120
<v Speaker 1>information about people they're investigating or who've been ordered to

0:14:21.200 --> 0:14:22.280
<v Speaker 1>leave the US.

0:14:22.360 --> 0:14:24.760
<v Speaker 2>And in a story that takes us elsewhere into a

0:14:24.800 --> 0:14:27.360
<v Speaker 2>topic I am personally obsessed with, which is right to

0:14:27.400 --> 0:14:28.280
<v Speaker 2>repair laws?

0:14:28.480 --> 0:14:29.200
<v Speaker 1>What does that mean?

0:14:29.600 --> 0:14:32.160
<v Speaker 2>Right to repair law is basically like laws that say

0:14:32.160 --> 0:14:35.640
<v Speaker 2>that companies have to provide information to people who buy

0:14:35.680 --> 0:14:38.800
<v Speaker 2>things that teach them how to repair it, so one

0:14:38.880 --> 0:14:41.320
<v Speaker 2>you're not just buying new things every time they come out,

0:14:41.360 --> 0:14:44.640
<v Speaker 2>and two that you're able to actually know how to,

0:14:44.800 --> 0:14:47.360
<v Speaker 2>for example, repair a tractor. I was drawn to this

0:14:47.400 --> 0:14:50.840
<v Speaker 2>headline from The Verge with the perfect subhead quote, India's

0:14:50.920 --> 0:14:54.280
<v Speaker 2>repair culture gives new life to dead tech.

0:14:54.440 --> 0:14:56.400
<v Speaker 1>So we had sex, some money, and we do indeed have.

0:14:57.920 --> 0:15:00.640
<v Speaker 2>Oh dead technology, which is about the least sexy thing

0:15:00.640 --> 0:15:04.800
<v Speaker 2>on the planet. There's a rise of Frankenstein laptops in India. Now,

0:15:04.800 --> 0:15:06.800
<v Speaker 2>when I say Frankenstein laptops, what do you think?

0:15:07.320 --> 0:15:11.320
<v Speaker 1>Uh, gosh, I guess I think about laptops assembled from

0:15:11.320 --> 0:15:12.040
<v Speaker 1>all different parts.

0:15:12.400 --> 0:15:14.320
<v Speaker 2>I thought you were gonna say laptops with two bolts

0:15:14.360 --> 0:15:18.000
<v Speaker 2>on the side of that, But yes, they're basically resurrected

0:15:18.040 --> 0:15:21.080
<v Speaker 2>computers made with parts from trash older laptops and other

0:15:21.160 --> 0:15:24.480
<v Speaker 2>e waste ewtes, meaning trash that is of the electronic

0:15:24.520 --> 0:15:27.600
<v Speaker 2>variety at a fraction of the price. These laptops are

0:15:27.600 --> 0:15:31.400
<v Speaker 2>a good option for students, freelancers, or really anyone who

0:15:31.480 --> 0:15:34.000
<v Speaker 2>needs to be a part of India's growing digital economy

0:15:34.120 --> 0:15:36.640
<v Speaker 2>but may not be able to afford to participate otherwise.

0:15:36.680 --> 0:15:38.960
<v Speaker 1>Yeah, I think I read that you can basically get

0:15:39.080 --> 0:15:41.800
<v Speaker 1>a functional laptop from one of these one of these

0:15:41.800 --> 0:15:45.280
<v Speaker 1>Frankenstein laptops for around one hundred US dollars, which is

0:15:45.320 --> 0:15:47.880
<v Speaker 1>like an eighth of the price of any decent new laptop.

0:15:47.920 --> 0:15:49.120
<v Speaker 1>So it's pretty cool story.

0:15:49.440 --> 0:15:52.160
<v Speaker 2>But these Frankenstein tinkers don't have it so easy. There

0:15:52.200 --> 0:15:56.080
<v Speaker 2>are actually many global tech giants who restrict access to

0:15:56.120 --> 0:15:59.600
<v Speaker 2>spare parts or use proprietary hardware, which means people are

0:15:59.600 --> 0:16:03.440
<v Speaker 2>going through piles of sometimes toxic trash to get the parts,

0:16:03.640 --> 0:16:06.360
<v Speaker 2>and India's government is beginning to discuss right to repair

0:16:06.440 --> 0:16:09.120
<v Speaker 2>laws to address this, but progress has been slow.

0:16:09.840 --> 0:16:12.200
<v Speaker 1>Final story for this week is about a question I

0:16:12.320 --> 0:16:16.160
<v Speaker 1>find quite fascinating. What will be the iPhone of ai?

0:16:16.720 --> 0:16:19.000
<v Speaker 1>Will there be a kind of AI product that becomes

0:16:19.040 --> 0:16:21.880
<v Speaker 1>so ubiquitous that we forget what life was like before

0:16:21.880 --> 0:16:26.440
<v Speaker 1>it existed? Well, the iPhone designer himself, Johnny Ive or

0:16:26.640 --> 0:16:29.960
<v Speaker 1>Sir Johnny I've is working on it. Over a year ago,

0:16:30.000 --> 0:16:33.120
<v Speaker 1>he and Sam Altman, the CEO of Open Ai, began

0:16:33.160 --> 0:16:36.600
<v Speaker 1>discussing a device that might bring to life voice enabled

0:16:36.800 --> 0:16:41.280
<v Speaker 1>AI assistance, partly inspired by Altman's well documented fascination with

0:16:41.360 --> 0:16:44.920
<v Speaker 1>the movie Her. So. Alman and I have this startup together,

0:16:45.080 --> 0:16:48.600
<v Speaker 1>Ioproducts that's raised hundreds of millions of dollars and is

0:16:48.640 --> 0:16:51.880
<v Speaker 1>working on some device concepts, including a quote phone without

0:16:51.880 --> 0:16:55.280
<v Speaker 1>a screen, although some sources insist that it's in fact

0:16:55.480 --> 0:17:00.240
<v Speaker 1>not a phone, so the mystery remains. But this into

0:17:00.240 --> 0:17:02.480
<v Speaker 1>a story in the Information, which is also reporting that

0:17:02.560 --> 0:17:07.760
<v Speaker 1>Open Ai executives are considering acquiring a startup Ioproducts. This

0:17:07.800 --> 0:17:09.960
<v Speaker 1>would be a move that could potentially bring the AI

0:17:10.080 --> 0:17:13.960
<v Speaker 1>giant into more direct competition with Apple. It's not clear

0:17:14.080 --> 0:17:17.040
<v Speaker 1>where the negotiation is at the moment, but another of

0:17:17.080 --> 0:17:22.440
<v Speaker 1>these types of XAI X deals perhaps brewing, Although while

0:17:22.440 --> 0:17:24.520
<v Speaker 1>Altman worked close to you with ive on the project.

0:17:24.960 --> 0:17:26.760
<v Speaker 1>Is not clear what his economic stake in it.

0:17:26.800 --> 0:17:29.879
<v Speaker 2>Maybe if the new phone is not a phone. It

0:17:29.920 --> 0:17:31.960
<v Speaker 2>begs the question how the next thing that we cover

0:17:32.200 --> 0:17:35.960
<v Speaker 2>actually is going to happen in a no phone phone universe.

0:17:36.800 --> 0:17:40.159
<v Speaker 1>You're right, and our next segment is all about scammers,

0:17:40.280 --> 0:17:44.720
<v Speaker 1>and specifically scam callers who famously use phones and the

0:17:44.800 --> 0:17:48.400
<v Speaker 1>tech they're using to be more convincing and successful than ever.

0:17:48.960 --> 0:17:51.080
<v Speaker 2>Yeah, And one of the things that I can't stop

0:17:51.160 --> 0:17:53.120
<v Speaker 2>talking about on the show and talked a lot about

0:17:53.119 --> 0:17:58.000
<v Speaker 2>on Sleepwalkers is how much technological progress and innovation happens

0:17:58.040 --> 0:18:01.040
<v Speaker 2>in the sort of seedier parts of society. And then

0:18:01.080 --> 0:18:05.520
<v Speaker 2>it's after everyone hears these sensational stories about criminal ingenuity

0:18:05.680 --> 0:18:08.320
<v Speaker 2>that the tech is more widely adopted by the general public.

0:18:08.600 --> 0:18:11.480
<v Speaker 2>But it's actually the illicit use that forges the way.

0:18:11.600 --> 0:18:13.640
<v Speaker 1>Yeah. I remember, back in twenty nineteen, when we first

0:18:13.680 --> 0:18:16.239
<v Speaker 1>started covering this stuff together, there was a study that

0:18:16.280 --> 0:18:19.080
<v Speaker 1>revealed that more than ninety five percent of all deep

0:18:19.119 --> 0:18:22.400
<v Speaker 1>fake videos on the Internet were non consensual porn.

0:18:22.600 --> 0:18:25.000
<v Speaker 2>Well, I actually didn't even know that three D printing

0:18:25.200 --> 0:18:28.159
<v Speaker 2>was a consumer tech until I heard that blueprints for

0:18:28.240 --> 0:18:31.640
<v Speaker 2>three D printed ghost guns were circulating the internet.

0:18:32.119 --> 0:18:34.400
<v Speaker 1>Together. We actually ran an experiment a few years ago

0:18:34.600 --> 0:18:38.040
<v Speaker 1>to create a deep fake of your voice and scam

0:18:38.119 --> 0:18:40.439
<v Speaker 1>your cousin, and it took us about a week to

0:18:40.480 --> 0:18:42.680
<v Speaker 1>make that clone with the help of a company called

0:18:42.760 --> 0:18:46.240
<v Speaker 1>liar Bird that was subsequently acquired by Descript, the software

0:18:46.280 --> 0:18:49.159
<v Speaker 1>that we use every week to make our podcast. We

0:18:49.200 --> 0:18:51.200
<v Speaker 1>didn't actually get to the scamming apart, but we did

0:18:51.240 --> 0:18:54.600
<v Speaker 1>briefly trick Kara's cousin. That was back in twenty nineteen.

0:18:55.119 --> 0:18:57.640
<v Speaker 1>Since then, the state of the art and the kind

0:18:57.680 --> 0:19:01.840
<v Speaker 1>of social risks haveally advanced. And here to tell us

0:19:01.880 --> 0:19:04.720
<v Speaker 1>more is Julie Jargon, the family and tech columnist at

0:19:04.760 --> 0:19:06.960
<v Speaker 1>the Wall Street Journal. Julie, welcome to Tech Stuff.

0:19:07.440 --> 0:19:08.280
<v Speaker 4>Thank you for having me.

0:19:08.640 --> 0:19:12.359
<v Speaker 2>So, just to begin, your article tells the story of

0:19:12.400 --> 0:19:14.520
<v Speaker 2>a woman who gets a terrifying call. Can you tell

0:19:14.600 --> 0:19:18.760
<v Speaker 2>us a little bit more about what happened in this exchange?

0:19:18.960 --> 0:19:21.479
<v Speaker 4>Yeah, absolutely So. There was a woman in Colorado by

0:19:21.480 --> 0:19:23.720
<v Speaker 4>the name of Linda Rohan, and she was just at

0:19:23.760 --> 0:19:26.640
<v Speaker 4>home one night making herself dinner, and her phone rang

0:19:26.760 --> 0:19:29.199
<v Speaker 4>her cell phone and the caller ID showed that the

0:19:29.240 --> 0:19:30.960
<v Speaker 4>call was from a local number, so she thought it

0:19:31.040 --> 0:19:33.840
<v Speaker 4>might be someone she should talk to, so she picked

0:19:33.880 --> 0:19:36.280
<v Speaker 4>it up and immediately heard a voice of a young

0:19:36.280 --> 0:19:39.840
<v Speaker 4>woman that she thought sounded exactly like the youngest of

0:19:39.840 --> 0:19:44.280
<v Speaker 4>her three adult daughters, a panicked, you know message, Mom,

0:19:44.320 --> 0:19:46.879
<v Speaker 4>I'm okay, but something awful has happened and she's sobbing

0:19:46.920 --> 0:19:50.080
<v Speaker 4>and saying she needs help. And that immediately put this

0:19:50.119 --> 0:19:53.760
<v Speaker 4>woman on high alert. And then apparently a man took

0:19:53.800 --> 0:19:57.320
<v Speaker 4>the phone and mentioned the name of her daughter by

0:19:57.600 --> 0:20:00.000
<v Speaker 4>you know by name, and said that she had witnessed

0:20:00.200 --> 0:20:02.919
<v Speaker 4>this drug deal and she screamed and it scared the

0:20:02.920 --> 0:20:05.439
<v Speaker 4>buyers away, and so now he was out all this money,

0:20:05.480 --> 0:20:08.560
<v Speaker 4>and he had pulled this girl into his van and

0:20:08.720 --> 0:20:10.280
<v Speaker 4>now was demanding money.

0:20:10.480 --> 0:20:13.520
<v Speaker 2>We know that this wasn't Linda's real daughter. Where was

0:20:13.600 --> 0:20:15.800
<v Speaker 2>Linda's daughter actually during this.

0:20:15.880 --> 0:20:18.600
<v Speaker 4>She was in her apartment the whole time, safe at home.

0:20:18.800 --> 0:20:21.240
<v Speaker 2>And can you talk a little bit about how this happened.

0:20:21.640 --> 0:20:23.960
<v Speaker 4>I think what happens with these kind of callers is

0:20:24.040 --> 0:20:28.560
<v Speaker 4>they operate on fear and a sense of urgency. And

0:20:28.880 --> 0:20:33.199
<v Speaker 4>this scammer had an elaborate story that he kind of

0:20:33.640 --> 0:20:37.040
<v Speaker 4>kept this woman through this whole time. He told her

0:20:37.080 --> 0:20:39.560
<v Speaker 4>that he needed money in order to free her daughter.

0:20:40.040 --> 0:20:43.520
<v Speaker 4>He told her to go to Walmart and wire money.

0:20:43.560 --> 0:20:46.000
<v Speaker 4>And so she gets in her car and finds the

0:20:46.040 --> 0:20:49.520
<v Speaker 4>nearest Walmart, and he timed how long it took her

0:20:49.560 --> 0:20:51.800
<v Speaker 4>to get there. When she went to the Walmart, he

0:20:51.880 --> 0:20:53.600
<v Speaker 4>wanted to be on speaker the whole time, so he

0:20:53.680 --> 0:20:56.840
<v Speaker 4>had her conceal her phone in her shirt so he

0:20:56.880 --> 0:21:00.200
<v Speaker 4>could hear the conversation. And you know, I think he'd

0:21:00.200 --> 0:21:02.119
<v Speaker 4>made some kind of threats to her and you know,

0:21:02.240 --> 0:21:05.119
<v Speaker 4>her daughter. And when she got to the Walmart, she

0:21:05.160 --> 0:21:07.119
<v Speaker 4>couldn't do the wire transfer because she didn't have a

0:21:07.119 --> 0:21:09.240
<v Speaker 4>debit card. So he told her to go home and

0:21:09.480 --> 0:21:12.520
<v Speaker 4>do it online. And he said, you've got sixteen minutes.

0:21:12.840 --> 0:21:15.080
<v Speaker 4>If you stop anywhere, I'm going to know, because he

0:21:15.160 --> 0:21:16.800
<v Speaker 4>knew how long it had taken her to drive there

0:21:16.800 --> 0:21:18.040
<v Speaker 4>in the first place. And he kept her on the

0:21:18.080 --> 0:21:20.720
<v Speaker 4>phone this whole time, talking to her, trying to keep

0:21:20.720 --> 0:21:24.359
<v Speaker 4>her calm, asking her questions. This whole scenario played out

0:21:24.480 --> 0:21:27.800
<v Speaker 4>for a long time, and she made not one, but

0:21:27.880 --> 0:21:33.520
<v Speaker 4>two money transfers online in order to obtain her daughter's freedom.

0:21:34.080 --> 0:21:37.680
<v Speaker 4>And once it was finally over, she called her daughter

0:21:38.000 --> 0:21:40.480
<v Speaker 4>and found that her daughter was safe in her apartments.

0:21:40.800 --> 0:21:43.520
<v Speaker 1>It was such a striking story because it had this

0:21:43.640 --> 0:21:46.600
<v Speaker 1>kind of cinematic quality. I mean's actually like a movie.

0:21:46.680 --> 0:21:49.880
<v Speaker 1>The guy is playing a version of her daughter's voice,

0:21:50.320 --> 0:21:53.320
<v Speaker 1>making her literally drive from a to b, having her

0:21:53.440 --> 0:21:57.200
<v Speaker 1>conceal a phone in her clothes. I mean, there's fifteen

0:21:57.280 --> 0:21:59.840
<v Speaker 1>twenty thirty forty five minutes, all the while she thinks

0:21:59.840 --> 0:22:04.160
<v Speaker 1>that her daughter has been abducted by a drug dealer.

0:22:04.280 --> 0:22:05.800
<v Speaker 1>I mean, what did that do to the mother? And

0:22:05.800 --> 0:22:07.199
<v Speaker 1>when you were into viewing her and what does she

0:22:07.560 --> 0:22:08.760
<v Speaker 1>reflect about the experience?

0:22:09.480 --> 0:22:11.480
<v Speaker 4>Yeah, she described it as something that she can still

0:22:11.640 --> 0:22:15.560
<v Speaker 4>feel viscerally like. She retold the story to me three

0:22:15.600 --> 0:22:18.120
<v Speaker 4>times over the course of a few different conversations with her,

0:22:18.280 --> 0:22:20.480
<v Speaker 4>as I went through the story again and again with her,

0:22:20.920 --> 0:22:22.840
<v Speaker 4>and I could tell each time I talk to her

0:22:22.840 --> 0:22:24.560
<v Speaker 4>that she felt really nervous and worked up about it,

0:22:24.560 --> 0:22:26.520
<v Speaker 4>even though she knows it was all a scam, even

0:22:26.560 --> 0:22:28.880
<v Speaker 4>though she knows that her daughter was never in any

0:22:28.920 --> 0:22:33.000
<v Speaker 4>actual danger, but this whole ordeal was so terrifying to her.

0:22:33.600 --> 0:22:35.880
<v Speaker 4>And then that's of course why these scammers are so effective,

0:22:36.200 --> 0:22:38.920
<v Speaker 4>that they prey on the fear of people thinking that

0:22:38.960 --> 0:22:41.000
<v Speaker 4>they have a loved one, especially a child who might

0:22:41.000 --> 0:22:43.520
<v Speaker 4>be in some sort of danger. So, even though she's

0:22:43.720 --> 0:22:46.680
<v Speaker 4>now more than a month removed from the situation, still

0:22:46.680 --> 0:22:50.760
<v Speaker 4>in the retelling she feels very like physically nervous and scared.

0:22:50.960 --> 0:22:53.119
<v Speaker 1>Well, she's not surprising because the tension was kind of

0:22:53.160 --> 0:22:55.440
<v Speaker 1>resting up. And then just when she thought that she'd

0:22:55.440 --> 0:22:57.920
<v Speaker 1>made the payment everything was okay, there was a kind

0:22:57.920 --> 0:23:00.159
<v Speaker 1>of not the tone of the screw right right.

0:23:00.240 --> 0:23:01.679
<v Speaker 4>She thought it was kind of over. She'd made one

0:23:01.720 --> 0:23:05.119
<v Speaker 4>transfer of a thousand dollars, and then there was a

0:23:05.119 --> 0:23:08.720
<v Speaker 4>commotion and the man on the phone came back and said, well,

0:23:08.760 --> 0:23:10.439
<v Speaker 4>you know, my boss is angry that it took so

0:23:10.560 --> 0:23:13.919
<v Speaker 4>long to transfer this money, so we need more. My

0:23:13.960 --> 0:23:17.119
<v Speaker 4>boss is mad and he thinks he could sell your

0:23:17.200 --> 0:23:19.520
<v Speaker 4>daughter for thirty thousand dollars. And then at that point

0:23:19.560 --> 0:23:22.040
<v Speaker 4>she hears her daughter in the background screaming like no, no,

0:23:22.160 --> 0:23:25.960
<v Speaker 4>you know, please help me, and this woman Linda wanted

0:23:26.000 --> 0:23:28.280
<v Speaker 4>to talk to her daughter. She pleaded with this man

0:23:28.640 --> 0:23:30.639
<v Speaker 4>to let her talk to her daughter again, and he

0:23:30.680 --> 0:23:32.480
<v Speaker 4>said no, but you know, we can end this now

0:23:32.520 --> 0:23:35.679
<v Speaker 4>if he send another thousand dollars. So then she wired

0:23:36.240 --> 0:23:40.720
<v Speaker 4>another thousand dollars through a different wire service, and at

0:23:40.720 --> 0:23:42.359
<v Speaker 4>that point it was finally over.

0:23:43.200 --> 0:23:46.800
<v Speaker 1>It's this kind of incredible intersection of both a new technology,

0:23:46.920 --> 0:23:50.119
<v Speaker 1>I like the ubiquity of deep fake voices, and a

0:23:50.160 --> 0:23:53.440
<v Speaker 1>tremendously sophisticated psychological hack, right, I mean it has both

0:23:53.480 --> 0:23:54.640
<v Speaker 1>elements exactly.

0:23:54.640 --> 0:23:56.600
<v Speaker 4>And these kind of imposter scams have been going on

0:23:56.640 --> 0:23:58.679
<v Speaker 4>for a long time. I mean years ago, we'd be

0:23:58.760 --> 0:24:01.679
<v Speaker 4>hearing about grandpa parents getting calls from someone that was

0:24:01.760 --> 0:24:03.959
<v Speaker 4>claiming to be their grandson. But they usually didn't have

0:24:04.000 --> 0:24:06.639
<v Speaker 4>a name, they didn't have you know, the voice was

0:24:06.680 --> 0:24:09.600
<v Speaker 4>like just any young man, you know. And so it's

0:24:09.720 --> 0:24:14.040
<v Speaker 4>kind of using the same type of social engineering, but

0:24:14.200 --> 0:24:16.960
<v Speaker 4>ramped up in a more technological way that makes it

0:24:17.040 --> 0:24:18.080
<v Speaker 4>all the more believable.

0:24:24.359 --> 0:24:26.680
<v Speaker 2>When we come back, we'll hear about the way generative

0:24:26.720 --> 0:24:44.240
<v Speaker 2>AI makes imposter scams so convincing. Welcome back, So, Julie,

0:24:44.320 --> 0:24:47.119
<v Speaker 2>I have a lot of friends whose grandparents this has

0:24:47.160 --> 0:24:50.600
<v Speaker 2>happened to, and it preys on this sort of psychology

0:24:50.600 --> 0:24:54.000
<v Speaker 2>of oh my god, my grandchild is in trouble, let

0:24:54.080 --> 0:24:57.439
<v Speaker 2>me help them, without really thinking about how possible it

0:24:57.480 --> 0:24:59.920
<v Speaker 2>is that this is actually going on. This to your point,

0:25:00.119 --> 0:25:03.679
<v Speaker 2>is like an extremely ratcheted up version of this, and

0:25:03.720 --> 0:25:08.320
<v Speaker 2>it begs the question how exactly does something like this work?

0:25:08.640 --> 0:25:11.720
<v Speaker 2>How has it gotten so much more advanced? And I

0:25:11.760 --> 0:25:14.520
<v Speaker 2>think most importantly for this show tech stuff is like,

0:25:14.920 --> 0:25:18.639
<v Speaker 2>how were these people able to replicate Linda's daughter's voice?

0:25:19.680 --> 0:25:21.600
<v Speaker 4>Well, what we don't know here is whether they in

0:25:21.680 --> 0:25:25.840
<v Speaker 4>fact cloned her voice from some publicly available audio, you know,

0:25:25.880 --> 0:25:29.000
<v Speaker 4>whether her daughter had YouTube video out there or some

0:25:29.119 --> 0:25:31.639
<v Speaker 4>other type of audio or video that they could have

0:25:32.400 --> 0:25:34.679
<v Speaker 4>grabbed her voice from. She's twenty six, so chances are

0:25:34.720 --> 0:25:37.480
<v Speaker 4>she she could have. I didn't find any social media

0:25:37.520 --> 0:25:39.800
<v Speaker 4>accounts that I could access for her. But there are

0:25:39.800 --> 0:25:43.080
<v Speaker 4>other ways that you can approximate the sound of someone's voice.

0:25:43.200 --> 0:25:45.520
<v Speaker 4>There are a bunch of apps that are free or

0:25:45.720 --> 0:25:49.000
<v Speaker 4>very inexpensive on the different app stores that allow you

0:25:49.080 --> 0:25:51.920
<v Speaker 4>to change your voice. Fifty year old man could change

0:25:51.920 --> 0:25:54.879
<v Speaker 4>his voice to sound like a twenty year old woman,

0:25:55.119 --> 0:25:57.120
<v Speaker 4>you know, and you can change the dialect to the accent,

0:25:57.600 --> 0:26:00.639
<v Speaker 4>and those can be pretty convincing. And the experts I

0:26:00.680 --> 0:26:04.040
<v Speaker 4>talked to, both psychologists and cybersecurity experts, said that you

0:26:04.040 --> 0:26:07.400
<v Speaker 4>know when you're in this moment of fear, and you've

0:26:07.440 --> 0:26:10.439
<v Speaker 4>already gotten this idea in your mind that your daughter

0:26:10.600 --> 0:26:12.960
<v Speaker 4>is calling you. The first thing they're saying is mom,

0:26:13.600 --> 0:26:16.880
<v Speaker 4>your mind immediately switches to one of your children. And

0:26:17.000 --> 0:26:21.000
<v Speaker 4>so if they're able to approximate a voice of a

0:26:21.160 --> 0:26:25.240
<v Speaker 4>twenty year old woman, then your mind might immediately think

0:26:25.280 --> 0:26:28.040
<v Speaker 4>that that is your daughter, when it may not be

0:26:28.720 --> 0:26:30.800
<v Speaker 4>her actual voice or clone of her voice. So in

0:26:30.840 --> 0:26:34.239
<v Speaker 4>this case, we'll never know how they either got a

0:26:34.280 --> 0:26:36.640
<v Speaker 4>clone of her voice or whether they use some sort

0:26:36.680 --> 0:26:39.119
<v Speaker 4>of generative AI to create a voice that sounded like

0:26:39.160 --> 0:26:41.399
<v Speaker 4>it could be her daughter. And then a couple of

0:26:41.400 --> 0:26:44.320
<v Speaker 4>the tip offs here is that she wasn't able to

0:26:44.400 --> 0:26:47.560
<v Speaker 4>interact with the daughter. There were just these clips of

0:26:47.640 --> 0:26:51.120
<v Speaker 4>sound playing. She didn't have a conversation.

0:26:51.800 --> 0:26:53.879
<v Speaker 2>This is exactly what we did with my cousin and

0:26:53.920 --> 0:26:55.800
<v Speaker 2>what she had said to me that was so interesting

0:26:55.840 --> 0:26:58.840
<v Speaker 2>about this is the thing that tricked her was not

0:26:58.920 --> 0:27:01.679
<v Speaker 2>that I had this like incredible deep fake, but it

0:27:01.720 --> 0:27:04.800
<v Speaker 2>was the context. So she didn't really question the fact

0:27:04.920 --> 0:27:07.199
<v Speaker 2>that it was me, not because it really sounded like me,

0:27:07.560 --> 0:27:10.240
<v Speaker 2>but because of the context of our conversation. She called

0:27:10.240 --> 0:27:11.919
<v Speaker 2>me and I picked up, So why shouldn't she think

0:27:11.960 --> 0:27:14.160
<v Speaker 2>it's me right exactly.

0:27:14.359 --> 0:27:16.560
<v Speaker 1>So what is the scale of this problem?

0:27:16.920 --> 0:27:20.719
<v Speaker 4>It's really huge. The Federal Trade Commission said that the

0:27:21.280 --> 0:27:26.640
<v Speaker 4>number one category of fraud last year was imposter scams.

0:27:26.840 --> 0:27:29.359
<v Speaker 4>So that doesn't mean that they're all AI generated, but

0:27:29.960 --> 0:27:35.160
<v Speaker 4>scams in which people are calling, texting, emailing, whatever, impersonating

0:27:35.359 --> 0:27:38.840
<v Speaker 4>someone that someone knows with some sort of story and

0:27:38.880 --> 0:27:39.919
<v Speaker 4>a request for money.

0:27:40.760 --> 0:27:44.600
<v Speaker 2>This is something that is incredibly advanced for people who

0:27:44.640 --> 0:27:47.520
<v Speaker 2>we'd often call petty criminals. Does that mean that the

0:27:47.560 --> 0:27:51.920
<v Speaker 2>technology has become so ubiquitous that it's very accessible by

0:27:51.920 --> 0:27:54.359
<v Speaker 2>people we would call petty criminals. It's no longer the

0:27:54.359 --> 0:27:55.919
<v Speaker 2>thing of like, oh, I'm going to get on the

0:27:55.960 --> 0:27:58.600
<v Speaker 2>subway and pickpocket someone for the amount of money that

0:27:58.640 --> 0:28:00.320
<v Speaker 2>you might be able to get for this kind of scam.

0:28:00.400 --> 0:28:02.439
<v Speaker 2>So I mean not that I think you have a

0:28:02.480 --> 0:28:06.000
<v Speaker 2>criminal mind, Julie, but I'm wondering, from your perspective as

0:28:06.000 --> 0:28:08.360
<v Speaker 2>someone who's now reported on this, is this the kind

0:28:08.400 --> 0:28:12.240
<v Speaker 2>of crime that people who are looking to scam people

0:28:12.240 --> 0:28:15.000
<v Speaker 2>are engaging it? Is it because it's so easy?

0:28:15.080 --> 0:28:17.720
<v Speaker 4>Yeah, it has become a lot easier because of the

0:28:17.760 --> 0:28:21.040
<v Speaker 4>abiquity of these tools that can do voice clones or

0:28:21.600 --> 0:28:25.000
<v Speaker 4>AA generated voice approximations of people. All you have to

0:28:25.000 --> 0:28:28.879
<v Speaker 4>do is google it and you'll find dozens of online

0:28:28.880 --> 0:28:32.280
<v Speaker 4>tools that are either free or very very inexpensive. Or

0:28:32.359 --> 0:28:35.200
<v Speaker 4>go on the app store and download a voice changing app.

0:28:35.240 --> 0:28:39.440
<v Speaker 4>Though it's widely accessible, it's inexpensive, and all it takes

0:28:39.520 --> 0:28:42.920
<v Speaker 4>is one person who sends two thousand dollars and however

0:28:42.960 --> 0:28:45.680
<v Speaker 4>long this scenario went on, maybe thirty forty five minutes

0:28:45.760 --> 0:28:48.840
<v Speaker 4>or whatever, you know, they got two thousand dollars. So

0:28:49.240 --> 0:28:52.120
<v Speaker 4>you get a few victims over the course of some

0:28:52.360 --> 0:28:56.360
<v Speaker 4>period of time, and the payout can be pretty sizable.

0:28:57.080 --> 0:29:00.160
<v Speaker 1>Yeah, I think. I mean there's a financial cost to

0:29:00.200 --> 0:29:02.840
<v Speaker 1>your point about you know, the aftermath for Linda. There's

0:29:02.840 --> 0:29:06.280
<v Speaker 1>also this tremendous emotional costs, I mean, the trauma of it.

0:29:06.400 --> 0:29:09.360
<v Speaker 1>I saw a documentary the other day produced by Bloomberg

0:29:09.600 --> 0:29:13.960
<v Speaker 1>about young teens who are basically the victims of sextortion scam.

0:29:14.040 --> 0:29:16.160
<v Speaker 1>So somebody pretends to be somebody in their community and

0:29:16.200 --> 0:29:18.960
<v Speaker 1>gets them to send nude photos and maybe they're looking

0:29:19.000 --> 0:29:21.320
<v Speaker 1>to get I think hundreds of dollars, but in some

0:29:21.360 --> 0:29:24.520
<v Speaker 1>cases this pushes the teams to suicide and so it's

0:29:24.600 --> 0:29:26.479
<v Speaker 1>not like, yes, you have a sense of violation if

0:29:26.480 --> 0:29:28.880
<v Speaker 1>you get pick pocket on the subway, but this goes

0:29:28.920 --> 0:29:32.440
<v Speaker 1>to your core of your deepest fears, and I guess

0:29:32.480 --> 0:29:34.280
<v Speaker 1>maybe that's one of the reasons why your story went

0:29:34.440 --> 0:29:36.760
<v Speaker 1>so viral. But what can we do and what can

0:29:36.800 --> 0:29:38.840
<v Speaker 1>listeners do? What can readers do? What is the way

0:29:38.840 --> 0:29:41.120
<v Speaker 1>to make ourselves a bit more robust in the face

0:29:41.160 --> 0:29:41.360
<v Speaker 1>of this.

0:29:41.640 --> 0:29:43.440
<v Speaker 4>Well, I do have a column coming out this weekend

0:29:43.480 --> 0:29:45.040
<v Speaker 4>that will have tips, so I don't want to pre

0:29:45.120 --> 0:29:49.240
<v Speaker 4>empt to that, but there are things you can do, So.

0:29:49.240 --> 0:29:51.920
<v Speaker 1>Stay tuned, read all about it. Yeah, yeah, real about.

0:29:51.640 --> 0:29:53.720
<v Speaker 4>It when it comes out. But yeah, I mean, I

0:29:53.720 --> 0:29:56.360
<v Speaker 4>think just awareness, for one, is a major thing. And

0:29:56.400 --> 0:29:59.680
<v Speaker 4>I think that's why so many people responded to this,

0:29:59.720 --> 0:30:04.080
<v Speaker 4>Because you'd talk to anybody and someone knows someone to

0:30:04.120 --> 0:30:07.000
<v Speaker 4>whom this has happened or something you know very similar,

0:30:07.520 --> 0:30:10.600
<v Speaker 4>and that shows the scale of the problem. And I

0:30:10.640 --> 0:30:13.680
<v Speaker 4>think what's unfortunate is that people who are victimized by

0:30:13.680 --> 0:30:16.360
<v Speaker 4>these scams feel an incredible sense of shame and embarrassment

0:30:16.520 --> 0:30:19.040
<v Speaker 4>about it. You know, after their mind has calmed down,

0:30:19.120 --> 0:30:21.240
<v Speaker 4>they can easily go back and see the red flags

0:30:21.240 --> 0:30:24.040
<v Speaker 4>and they can you know, even when Linda was experiencing

0:30:24.040 --> 0:30:26.920
<v Speaker 4>this from the beginning, it cossed her mind this could

0:30:26.960 --> 0:30:29.280
<v Speaker 4>be a scam, but she felt like the stakes were

0:30:29.320 --> 0:30:32.360
<v Speaker 4>too high to just hang up and call her daughter

0:30:32.400 --> 0:30:34.080
<v Speaker 4>at that point, because she thought, you know, there was

0:30:34.080 --> 0:30:36.560
<v Speaker 4>that one kernel of like what if, what if my

0:30:36.640 --> 0:30:38.880
<v Speaker 4>daughter really has witnessed the drug deal and is in

0:30:38.920 --> 0:30:41.520
<v Speaker 4>the back of this person's van, and now her life

0:30:41.600 --> 0:30:42.280
<v Speaker 4>is in my hands.

0:30:42.400 --> 0:30:44.200
<v Speaker 2>And you don't want to be the mother that avoided

0:30:44.200 --> 0:30:47.400
<v Speaker 2>this because you think that you're being sort of techno savvy, right,

0:30:47.440 --> 0:30:49.120
<v Speaker 2>And all of a sudden, yeah, And that's when it

0:30:49.160 --> 0:30:52.600
<v Speaker 2>really speaks to the sort of core emotional piece of

0:30:52.640 --> 0:30:55.320
<v Speaker 2>these kind of scams. To Oz's point, it's not just pickpocketing.

0:30:55.640 --> 0:30:57.320
<v Speaker 2>You know, pickpocketing, you can say, oh, I should have

0:30:57.400 --> 0:30:59.880
<v Speaker 2>closed up my jacket better, But this is something that

0:31:00.120 --> 0:31:03.000
<v Speaker 2>is just so much more complicated than that. And also

0:31:03.080 --> 0:31:05.720
<v Speaker 2>I think has dual use. I just wanted to bring

0:31:05.760 --> 0:31:08.840
<v Speaker 2>that up quickly, like a lot of these technologies are

0:31:08.880 --> 0:31:12.120
<v Speaker 2>not just created for bad right, so it's not something

0:31:12.160 --> 0:31:14.920
<v Speaker 2>that can just be kind of wiped out. Deep fake

0:31:14.960 --> 0:31:19.880
<v Speaker 2>technology also has some really interesting applications that I think

0:31:19.960 --> 0:31:23.080
<v Speaker 2>we all benefit from. Now, so it becomes that sort

0:31:23.120 --> 0:31:26.040
<v Speaker 2>of complicated intersection of like some people are using this

0:31:26.480 --> 0:31:29.800
<v Speaker 2>to take advantage of people and scam them, and other

0:31:29.800 --> 0:31:34.080
<v Speaker 2>people are using it to make some really interesting practical applications.

0:31:34.120 --> 0:31:36.800
<v Speaker 2>So I don't know, I'm curious to see your column,

0:31:36.800 --> 0:31:41.080
<v Speaker 2>but it's definitely less simple than just get rid of

0:31:41.120 --> 0:31:41.920
<v Speaker 2>this technology.

0:31:42.120 --> 0:31:44.280
<v Speaker 4>Well, it's not going away, that's for sure. There are

0:31:44.680 --> 0:31:48.479
<v Speaker 4>obviously good uses of generative AI and it's definitely here

0:31:48.520 --> 0:31:51.160
<v Speaker 4>to stay. And my worry is as it gets better

0:31:51.200 --> 0:31:54.040
<v Speaker 4>and better, especially with video, I just wonder at some

0:31:54.160 --> 0:31:58.040
<v Speaker 4>point will people be able to receive faith time calls,

0:31:58.120 --> 0:32:02.520
<v Speaker 4>right video calls where they feel like they're seeing interacting

0:32:02.600 --> 0:32:05.920
<v Speaker 4>with someone who looks just like their child. Now, how

0:32:07.040 --> 0:32:08.720
<v Speaker 4>do you then tell that that's not real?

0:32:09.880 --> 0:32:11.400
<v Speaker 1>Julie, Thank you so much for your time today.

0:32:11.560 --> 0:32:14.240
<v Speaker 2>Thank you, Julie. We'll look forward to that column this Saturday.

0:32:14.480 --> 0:32:15.560
<v Speaker 4>Yeah, thank you for having me.

0:32:22.680 --> 0:32:24.280
<v Speaker 2>That's it for this week for TEXTA.

0:32:24.560 --> 0:32:27.800
<v Speaker 1>I'm Kara Price and I'm mos Vloschen. This episode was

0:32:27.800 --> 0:32:32.240
<v Speaker 1>produced by Eliza Dennis, Victoria Dominguez, and Adriana Tapia. It

0:32:32.280 --> 0:32:35.480
<v Speaker 1>was executive produced by me, Kara Price and Kate Osborne

0:32:35.560 --> 0:32:40.520
<v Speaker 1>Kaleidoscope and Katria Novelfi Hot Podcasts. The engineer is Bihit

0:32:40.560 --> 0:32:43.880
<v Speaker 1>Fraser and Kyle Murdoll makes this episode and he also

0:32:43.880 --> 0:32:44.640
<v Speaker 1>wrote our theme song.

0:32:44.880 --> 0:32:47.600
<v Speaker 2>Join us next Wednesday for Textuff the Story, when we

0:32:47.640 --> 0:32:50.880
<v Speaker 2>will share an in depth conversation with Jenstatsky, creator and

0:32:50.920 --> 0:32:54.000
<v Speaker 2>writer of the hit HBO Max show hacks Well, chat

0:32:54.000 --> 0:32:56.280
<v Speaker 2>about if AI is coming for her job and what

0:32:56.320 --> 0:32:58.800
<v Speaker 2>it's like to make TV. Knowing you're likely battling for

0:32:58.840 --> 0:32:59.760
<v Speaker 2>attention with a.

0:32:59.680 --> 0:33:03.440
<v Speaker 1>Second, please rate, review, and reach out to us at

0:33:03.480 --> 0:33:06.720
<v Speaker 1>tech Stuff podcast at gmail dot com. We love hearing

0:33:06.760 --> 0:33:07.120
<v Speaker 1>from you