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Speaker 1: There Are No Girls on the Internet, as a production

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Speaker 1: of iHeartRadio and Unbossed Creative. I'm Bridget Todd, and this

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Speaker 1: is There Are No Girls on the Internet. Welcome to

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Speaker 1: There Are No Girls on the Internet, where we explore

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Speaker 1: the intersection of technology, social media, and identity. And one

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Speaker 1: thing to know about me is that I have always

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Speaker 1: wanted to have one of those movie recap podcasts where

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Speaker 1: you just watch a movie or watch a show and

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Speaker 1: to get to yap about it. So Mike, They're gonna

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Speaker 1: kind of indulge me and let me do that, right.

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Speaker 2: Yeah, that's what we're doing. Today's new format. It's exciting format.

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Speaker 3: You know.

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Speaker 2: One of the criticisms that you sometimes get in our reviews,

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Speaker 2: which we love to see reviews in general, is that

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Speaker 2: some people feel I'm not always as prepared as you,

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Speaker 2: which would be hard because you know, Bridgiet knows it's

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Speaker 2: always very prepared. But also generally the format of the

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Speaker 2: newscast is like Bridget explaining stuff to me. So I

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Speaker 2: feel that criticism maybe a little unfair, but like, I

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Speaker 2: get it this time, though I have copious notes.

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Speaker 3: I am ready to talk about this movie.

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Speaker 1: So what is the movie that we're talking about today.

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Speaker 2: We are talking about the movie Her, which is in

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Speaker 2: the zeitgeist because Sam Altman compared open AI's new assistant

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Speaker 2: Sky to the movie very explicitly. He had a one

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Speaker 2: word tweet that like made that connection, and then there

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Speaker 2: was a bunch of controversy about it. Bridget, would you

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Speaker 2: like to talk about why the comparison has perhaps not

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Speaker 2: gone in the direction Altman was hoping.

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Speaker 1: Yes, we did an episode kind of digging into this

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Speaker 1: this week about why the movie Her and Scarlett Johansson

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Speaker 1: is in the news. But the short version is that

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Speaker 1: open AI, this company run by Sam Altman, recently introduced

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Speaker 1: and then quickly be introduced, this voice integration to chat

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Speaker 1: GPT four called Sky, which can talk conversationally with people

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Speaker 1: and respond to images that you show it through your

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Speaker 1: phone's camera. So if you were to be like, oh, hey, Sky,

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Speaker 1: look at this thing, and then you moved your phone

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Speaker 1: so that the camera was in front of it, Sky

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Speaker 1: would presumably see that and be able to respond in

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Speaker 1: a conversational, maybe a little bit flirtatious kind of way.

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Speaker 1: So Sam Altman asked Scarlett Johansson, who was the voice

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Speaker 1: of the AI Samantha in the movie her to voice

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Speaker 1: his technology. She said no. He asked again, she said no. Again.

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Speaker 1: They unveiled it. It sounded a lot like Scarlett Johansson.

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Speaker 1: There's been some new reporting, I should say, just in

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Speaker 1: the last couple of days, where open ai is saying

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Speaker 1: that they did not ask the human voice actor to

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Speaker 1: mimic Scarlett Johansson or sound like Scarlett Johansson. This is

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Speaker 1: just a voice actor using the voice actor's natural voice.

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Speaker 1: They say they have proof. You can read that reporting

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Speaker 1: the Washington Post. I still think that these people have

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Speaker 1: proven themselves time and time again to be liars, to

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Speaker 1: be people that you cannot trust, to be people who

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Speaker 1: you cannot take at their at their word. So at

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Speaker 1: this point I am deeply skeptical of everything that they say.

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Speaker 1: But I did want to include that open ai pulled

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Speaker 1: their Sky Voice technology quote out of respect for Scarlett Johansson,

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Speaker 1: which is maybe my favorite statement in the history of technology,

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Speaker 1: pulling your highly anticipated new tech out of respect for

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Speaker 1: miss Johnsson. I live for that kind of stuff, So

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Speaker 1: I will say open ais live demo of sky I

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Speaker 1: think is a lot like Samantha. From her we did

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Speaker 1: a little bit of a side by side comparison in

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Speaker 1: our episode this week, but hearing having just watched the

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Speaker 1: movie to recap it for this podcast episode and watching

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Speaker 1: the live demo that open Ai released, it's not just

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Speaker 1: that they're similar in voice, it's also intonation. It's also

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Speaker 1: sort of vibe, like the casually curious and conversational vibe.

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Speaker 1: You know. Sky in this demo is flirty and responsive,

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Speaker 1: and Altman definitely wants us to be thinking of the

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Speaker 1: movie Her when he unveiled it, As you said, Mike

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Speaker 1: tweeting this the word Her around its release. So here's

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Speaker 1: a little bit of what Sky sounded like in that

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Speaker 1: demo from Open Ai.

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Speaker 4: Is this announcement related to open Ai?

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Speaker 3: Press? It is?

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Speaker 4: And in fact, what if I were to say that

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Speaker 4: you're related to the announcement, or that you are the announcement.

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Speaker 2: Me?

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Speaker 1: The announcement is about me? Well, color me intrigued.

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Speaker 5: Are you about to reveal something about Ai or more specifically,

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Speaker 5: about me as a part of Open Ai.

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Speaker 1: You've got me on the edge of my well, I

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Speaker 1: don't really have a seat, but you get the idea.

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Speaker 3: What's the big news.

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Speaker 4: Yeah, We've got a new model that can interact with

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Speaker 4: the world through audio vision, and text.

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Speaker 1: So Sam Autman has actually said in an interview that

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Speaker 1: Her is one of his favorite movies. In an interview,

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Speaker 1: he said, I like Her the things Her got right,

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Speaker 1: like the whole interaction models of how people use AI.

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Speaker 1: That was incredibly prophetic, he said. So he likes the

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Speaker 1: idea of this interaction model where AI can talk to you,

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Speaker 1: respond to you, flirt with you like a human. He

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Speaker 1: likes that.

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Speaker 2: Yeah, which, you know, one can wonder why, you know,

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Speaker 2: what it is specifically about Her that appeals there, because

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Speaker 2: there are certainly many other science fiction movies where there

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Speaker 2: are machines that converse with humans. Why is it her

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Speaker 2: and not like C three Po from Star Wars, Right

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Speaker 2: he's having conversations with Luke. But you know, opening I

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Speaker 2: didn't want to build a new they wanted to build

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Speaker 2: a new Scarlet Johansson.

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Speaker 1: I was gonna say, like, even if you wanted the

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Speaker 1: tech to be kind of sexy, why not ex Machina?

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Speaker 1: But then I'm thinking about the ending of Xmochty, and

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Speaker 1: I'm like, Okay, maybe they don't want to have technology

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Speaker 1: that ends like the movie X Machina. If you've seen

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Speaker 1: the movie, if you know, you know, you know why

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Speaker 1: that specific brand of sexy AI tech maybe isn't what

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Speaker 1: he wanted to be. It's his whole thing on.

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Speaker 2: Yeah, Like somewhere in the middle of C three PO

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Speaker 2: and the robots from Xmachina, that's where we landed.

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Speaker 1: That's like my dream girl, like somewhere somewhere between like

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Speaker 1: friendly and helpful and cute and like fucking terrifying.

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Speaker 2: Yeah, but it's also one of your favorite movies, right, Bridget.

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Speaker 1: Oh, her, it absolutely is. I wouldn't say it's one

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Speaker 1: of my favorite movies. It's a movie that I watch

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Speaker 1: a lot. It's a movie that I get a lot

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Speaker 1: out of every time I watch it, and I feel

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Speaker 1: like there's lots of different ways you can watch it.

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Speaker 1: I have watched it no less than four times in

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Speaker 1: the last month, not because of the whole open AI saga,

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Speaker 1: but just because it's like one of those movies that

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Speaker 1: is in my heavy rotation.

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Speaker 3: That is a very heavy rotation.

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Speaker 2: Uh, what is it about this movie that speaks to

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Speaker 2: you that calls you to watch it multiple times?

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Speaker 1: Okay, so I make a tech podcast. I am a techie.

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Speaker 1: I'm a tech girl. So I wish I could say, oh,

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Speaker 1: it's I just love like the tech implications. I love

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Speaker 1: like mining what the movie says about our tech enabled futures.

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Speaker 1: It's partly that, but if we're being like for real

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Speaker 1: the movie, my real fascination with this movie is that

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Speaker 1: it is a very specific kind of indie filmmaker drama

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Speaker 1: behind the scenes, and it's the kind of thing I

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Speaker 1: absolutely live for. So I don't want to derail the

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Speaker 1: conversation too much, but the people need to know, like

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Speaker 1: if you don't know, if you know, if you know this,

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Speaker 1: if you know where I'm going, or you're like, I

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Speaker 1: know this story. This is like one of my roman

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Speaker 1: empires is the movie Her.

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Speaker 2: Yeah, you explained this to me, and it like blew

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Speaker 2: my mind and really recontextualized the whole movie for me.

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Speaker 3: So don't hold back. I think people need to know.

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Speaker 1: Once you know this, you can watch these two movies

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Speaker 1: in conversation with each other again and again and again,

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Speaker 1: and it's like a new movie every time. So I am,

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Speaker 1: of course talking about Her in conversation with Sophia Coppola's

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Speaker 1: movie Lost in Translation. For those who don't know Sophia Coppola,

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Speaker 1: the director of the version Suicides, Marie Antoinette Bling Ring

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Speaker 1: daughter of Francis Ford. Coppola might have heard of him,

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Speaker 1: directed Godfather, Apocalypse, Now, every important movie in the last

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Speaker 1: like forty years or whatever. So Sophia Coppola's two thousand

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Speaker 1: and three movie Lost in Translation is meant to be

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Speaker 1: about her crumbling marriage to filmmaker Spike Jones. The stand

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Speaker 1: in for Sophia herself in Lost in Translation is you

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Speaker 1: guessed it, Scarlet Johansson. So both movies, both Her and

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Speaker 1: Lost in Translation, both have kind of mean caricatures of

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Speaker 1: there of each other in the movie. The stand in

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Speaker 1: for Spike Jones in Sofia Coppola's Lost in Translation is

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Speaker 1: portrayed by Giovanni Ribisi, and he's just sort of like preening,

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Speaker 1: self obsessed, like neglectful hipster type. Cameron Diaz also might

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Speaker 1: take kind of a stray here. Word on the street

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Speaker 1: is that if you've seen Lost in Translation, there's a

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Speaker 1: scene where the husband is having this like mild flirtation

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Speaker 1: with a pretty blonde played by Anna Faris. Word on

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Speaker 1: the street is that that is meant to be Cameron Diaz.

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Speaker 1: Because Spike Jones and Cameron Diaz work together on being

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Speaker 1: John Malkovich. I will say. Sophia Copola denies this. She says, like, oh,

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Speaker 1: it's actually like a composite of a bunch of different women.

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Speaker 1: If anybody there's like one specific woman that that's supposed

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Speaker 1: to be, I don't know. It seems a lot like

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Speaker 1: Cameron Diaz to me. I just think that people should

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Speaker 1: have that context. So if you want to get even

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Speaker 1: more deep into the like indie filmmaker drama here. Sofia Coppola,

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Speaker 1: in a interview said that Michelle Ganderie, who worked on

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Speaker 1: the movie Eternal Sunshine of a Spotless Mind with Spike Jones,

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Speaker 1: so like obviously they have a friendship there, came to

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Speaker 1: the premiere of Lost in Translation and from the red

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Speaker 1: carpet of her own premiere, berated her about making a

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Speaker 1: movie that makes Spike Jones look bad, which also part

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Speaker 1: of me is like, well, damn, I guess a hit

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Speaker 1: dog will holler. I guess like your friend saw this

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Speaker 1: movie and was like, this is supposed to be a

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Speaker 1: main character of my friend Spike Jones.

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Speaker 2: Celebrities they're just like us or petty, they're mean, they

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Speaker 2: cause a scene.

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Speaker 1: I know, coming to her own premiere to like yell

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Speaker 1: at her is pretty wild, but like, if you know me,

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Speaker 1: this is very much my specific type of tea, like

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Speaker 1: filmmaker t indie filmmaker tea, and like bad marriage tea.

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Speaker 1: I honestly cannot imagine how obnoxious it must have been

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Speaker 1: to be in their orbit and have these two powerhouse

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Speaker 1: filmmakers getting a divorce, like like, I'll make a movie

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Speaker 1: about it. Now, I'll make a movie about it.

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Speaker 5: Let's take a quick break.

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Speaker 1: At her back. If Lost in translation is meant to

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Speaker 1: be Sophia Cupola her exploration of her crumbling marriage to

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Speaker 1: Spike Jones from her perspective, Her is meant to be

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Speaker 1: Spike Jones is retelling of their bad marriage from his perspective.

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Speaker 1: There is also a mean portrayal of Sophia Cupola in Her.

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Speaker 1: She's played by Rooney Mara in the movie Her. Both

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Speaker 1: movies also share a director of photography. Not to mention,

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Speaker 1: both movies prominently feature Scarlett Johansson, so obviously Scarlett Johansson

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Speaker 1: has some kind of a like undercurrent thread in their

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Speaker 1: understanding of what went wrong in their marriage. Or maybe

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Speaker 1: maybe Spike Jones was like, well, if you're gonna use Scarlett,

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Speaker 1: I'm gonna use.

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Speaker 2: Her too, yeah, I feel like that's one of the

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Speaker 2: big mysteries that never gets resolved, like why Scarlet Johansson

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Speaker 2: for both of them? But setting that aside, that backstory

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Speaker 2: really changes.

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Speaker 3: The way the movie hits right.

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Speaker 2: It before I knew that, And I think most people

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Speaker 2: don't know that because most people are not as obsessed

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Speaker 2: with as tool as you. Like, I thought it was

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Speaker 2: a movie about technology, but it's not.

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Speaker 3: It's a movie about human relationships.

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Speaker 1: That's exactly right. And in case you're wondering, Sophias has

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Speaker 1: said that she's never seen her only in the trailer

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Speaker 1: and she's like, I'm not really that interested in seeing it,

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Speaker 1: which I don't know if I believe that either, but fine,

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Speaker 1: I do. In some ways feel like Spike Jones was like, Oh,

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Speaker 1: you want to make a dreamy movie about isolation that

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Speaker 1: talks shit on what it was like to be married

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Speaker 1: to me? Make an even dreamier movie, even more isolated

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Speaker 1: movie about what it was like being married to you. Like,

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Speaker 1: in some ways I feel like he out Sophia Coppola.

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Speaker 1: Sophia Coppola with her.

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Speaker 3: God, yeah, like how deep does it go?

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Speaker 1: How deep does this thing go? So how the movie

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Speaker 1: came to be According to Spike Jones, he got the

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Speaker 1: idea for the film in the early twentys when he

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Speaker 1: read this article about a website where people could instant

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Speaker 1: message with an artificial intelligence. He says, for the first

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Speaker 1: maybe twenty seconds of it, it had this real buzz.

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Speaker 1: I'd say hey, hello, and it would say, hey, how

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Speaker 1: are you? And I was like, whoa, this is trippy.

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Speaker 1: After twenty seconds, it quickly fell apart and you realize

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Speaker 1: how it actually works, and it wasn't that impressive, but

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Speaker 1: it was still for twenty seconds really exciting. The more

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Speaker 1: people talk to it, the smarter it got, And I

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Speaker 1: feel like that is like how it works with a

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Speaker 1: lot of these these AI chat but like you're like, wow,

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Speaker 1: this is really cool, and then like quickly you're like, wait,

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Speaker 1: this is actually kind of not so cool.

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Speaker 2: Yeah. It's really funny to read the about his experience

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Speaker 2: in the early two thousands because I feel in a

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Speaker 2: lot of ways it's still very much like that. There's

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Speaker 2: a lot of apps out there with like AI persona chatbots,

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Speaker 2: and this is something I've actually been getting into in

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Speaker 2: some of my other work, and like they're better than

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Speaker 2: they were in the early two thousands, but a lot

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Speaker 2: of them. It still kind of feels that way, where

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Speaker 2: at first it's really interesting, It's like, oh my god,

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Speaker 2: this is amazing technology, and then after twenty seconds or

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Speaker 2: maybe they're up to a couple minutes now, it just

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Speaker 2: starts to feel really boring and like a little bit

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Speaker 2: pointless and empty.

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Speaker 1: Oh, the AI tech feels a little pointless and empty.

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Speaker 1: In the end, it sounds like something straight from the movies.

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Speaker 3: Yeah, right, like where is the meaning? What is the point?

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Speaker 1: So let's talk about that sort of tech climate that

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Speaker 1: was permeating when this movie came to be. So if

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Speaker 1: you were somebody who paid attention to tech in the

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Speaker 1: twenty twelves, twenty thirteen, twenty fourteen, this movie came together

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Speaker 1: in twenty twelve, you know that it felt very different.

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Speaker 1: Siri came out in twenty eleven. At this time, Siri

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Speaker 1: was like very much a robot assistant in your phone.

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Speaker 1: You couldn't have conversations with it. There were a couple

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Speaker 1: of easter eggs like put in there that if you

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Speaker 1: asked certain things, it would give you a funny answer,

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Speaker 1: but if you tried to have a back and forth conversation,

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Speaker 1: just like spit Jones describes it would get really old,

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Speaker 1: really quickly. So this idea that is in the movie

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Speaker 1: heard that you would be having this like real complex

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Speaker 1: relationship with AI that feels like a human. When the

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Speaker 1: movie came out, that was still very much a far

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Speaker 1: off fantasy. This era did have some like pretty big

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Speaker 1: dark sides to technology, notably the NSA warrantless wiretapping that

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Speaker 1: was revealed by Edward Snoden an NSA contractor things like that.

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Speaker 1: But I do broadly think that this was sort of

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Speaker 1: the last like the heyday of optimism around technology, and

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Speaker 1: this was maybe the last era of that kind of

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Speaker 1: techno optimism. This is something that we talked about in

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Speaker 1: the episode we did with Paris Marks, one of my

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Speaker 1: favorite podcasters who hosts Tech Won't Save Us. But that era,

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Speaker 1: I think really gave us this kind of era that

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Speaker 1: we have now, where the holdover of technology as this

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Speaker 1: like exciting force for good and tech leaders as these

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Speaker 1: people who were going to be doing great things for us.

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Speaker 1: So give them lots of leeway, give them lots of money,

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Speaker 1: don't ask too many questions. That you could really draw

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Speaker 1: a straight line from that era and this era we

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Speaker 1: have ten years later, where it's like they can do

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Speaker 1: whatever they want, whether it's good for us or not,

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Speaker 1: and it's probably not so good for us most of

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Speaker 1: the time, to be honest, and we're supposed to just

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Speaker 1: accept like, oh yeah, they're probably doing great things. But

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Speaker 1: back in this twenty thirteen twenty twelve era that her

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Speaker 1: came out, we were still very much thinking about technology

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Speaker 1: as these forces for good, the idea that tech companies

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Speaker 1: and social media platforms are going to be giving us better,

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Speaker 1: more meaningful, more connected lives. This was back when Google's

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Speaker 1: motto was don't be evil? Do you know when they

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Speaker 1: dropped that motto? I don't know exactly do you Don't

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Speaker 1: be evil was Google's motto up until twenty eighteen. So

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Speaker 1: that's when they were like, actually, a little evil is

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Speaker 1: probably fine.

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Speaker 3: This is too constraining.

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Speaker 2: Yeah, like you know, you want to make a nomal

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Speaker 2: you gotta break a few eggs.

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Speaker 1: Like we're just trying to make money here, a little

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Speaker 1: evil we can we got to have. So, you know,

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Speaker 1: back in twenty twelve, we had the reelection of Obama,

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Speaker 1: which was very sort of like technology driven. Obama was

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Speaker 1: probably the most tech savvy president we'd had up until

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Speaker 1: that point. Twitter Republic in twenty thirteen. Facebook acquired Instagram

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Speaker 1: in twenty thirteen, and Instagram was like boom me. This

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Speaker 1: was the heyday of that platform. Vine had just come out.

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Speaker 1: Social media companies were really up, and we really saw

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Speaker 1: them as these forces that helped us connect, helped us

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Speaker 1: be more informed, helped us, you know, decide who to

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Speaker 1: vote for, decide who should be president, help us live

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Speaker 1: more meetingful, more full lives. This was also the time

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Speaker 1: where people were really excited about wearables. Do you remember this?

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Speaker 3: I do. I remember.

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Speaker 2: It must have been like twenty eleven or twenty twelve.

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Speaker 2: I was in grad school and I've talked with my

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Speaker 2: advisor about like trying to put together some kind of

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Speaker 2: research projects so we could ask Google to give us

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Speaker 2: some Google glass just because we thought they seemed cool

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Speaker 2: and wanted to use them. It seemed like the future, right,

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Speaker 2: We're gonna put these glasses on our head and they'll

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Speaker 2: have a camera and all this new information and new

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Speaker 2: capabilities that we were still getting used to having in

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Speaker 2: our pocket with cell phones. It's just going to keep

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Speaker 2: advancing and getting more powerful and allow us to do

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Speaker 2: ever more, bigger, greater things.

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Speaker 3: That was the feeling.

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Speaker 1: Yeah, So Google Glass came out in the same year

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Speaker 1: that Her came out. And fun fact, my first ever

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Speaker 1: Twitter profile picture was actually a picture of me proudly

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Speaker 1: wearing Google Glass. It wasn't mine, I belonged to a

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Speaker 1: friend of mine, but you know it was this was

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Speaker 1: before this was like he had gotten one of the

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Speaker 1: first models of it or whatever. And so like, this

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Speaker 1: was before a lot of conversations about like, oh man

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Speaker 1: walks into San Francisco bar with Google Glass and like

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Speaker 1: gets flapped in the face because people don't like don't

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Speaker 1: like the idea of wearables in their bars. This was

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Speaker 1: before that, right, and so like it really did feel exciting,

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Speaker 1: like the conversation around Google Glass, it felt like a

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Speaker 1: game changer. Like I distinctly remember how excited people were

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Speaker 1: not just for the technology, but for the idea of

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Speaker 1: a wearable making the technology more seamlessly integrated to your body, which,

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Speaker 1: of course the movie Her explores, like, I don't think

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Speaker 1: it's a it's a coincidence that that was what our

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Speaker 1: kind of conversation around technology was excited about, and that

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Speaker 1: is what shown in the movie that came out that

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Speaker 1: same year.

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Speaker 2: Yeah, right, Like we had all these new capabilities, access

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Speaker 2: to every piece of information ever created, but we still

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Speaker 2: had the annoying technology, right, Like I think might have

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Speaker 2: still had like a tower desktop computer back in twenty thirteen.

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Speaker 3: Maybe I held on to it for a long time.

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Speaker 3: But like cell.

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Speaker 2: Phones were kind of big, Google glass was big and chunky,

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Speaker 2: and we didn't I don't think we we were just

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Speaker 2: starting to grapple with like the dorkiness factor of this technology, right.

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Speaker 2: We loved all the new capabilities, but there's something inherently

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Speaker 2: dorky about like holding your phone out in front of

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Speaker 2: you wearing Google glass that it's you know, at the time,

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Speaker 2: it seemed like, oh, we'll solve this.

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Speaker 3: In a couple of years, you know.

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Speaker 2: Fast forward to twenty twenty four and metas ray band

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00:20:39,200 --> 00:20:43,520
Speaker 2: glasses are still, like, I guess, a little bit cooler

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Speaker 2: than Google glass, but I don't see a whole lot

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Speaker 2: of people wearing them.

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Speaker 1: Well, I mean, I don't want to make it sound

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Speaker 1: like this is an endorsement for Facebook, which it is not,

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Speaker 1: but I will say I saw a pair of them, irl,

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Speaker 1: and you I I'm not.

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Speaker 3: I don't.

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Speaker 1: I'm not a wearable person. I don't think wearables are

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Speaker 1: it However, if you did a side by side of

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Speaker 1: the ray Ban Wayfarer sunglasses and Meta's version of them

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Speaker 1: the wearable device, you might have a hard time telling

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Speaker 1: which was which. So you might have seen somebody wearing

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Speaker 1: those and not even know it, because I will say that, like,

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Speaker 1: they do look like the regular sunglasses, which is the

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Speaker 1: first time I've seen a wearable other than those Snapchat goggles,

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Speaker 1: remember those, Like those kind of did it? Although again

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Speaker 1: I don't like wearables, but so yeah, don just wanted

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Speaker 1: to say.

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Speaker 2: That, Okay, yeah, well maybe they did crack the code

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Speaker 2: then and make the actual hardware and all the sort

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Speaker 2: of challenging rub of the technology disappear and become invisible.

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Speaker 1: Just like in the movie Her.

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Speaker 3: Just like in the movie Her.

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Speaker 1: The last thing I'll say about that sort of tech

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Speaker 1: climate that permeates the movie Her is that I looked

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Speaker 1: up one of those you know, what were the top

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Speaker 1: tech news stories from twenty thirteen articles from CNN, and

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Speaker 1: this point made me laugh. Speaking of Facebook, people thought

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Speaker 1: that Mark Zuckerberg was this like really good leader and

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Speaker 1: we weren't really talking about some of the deeper issues

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Speaker 1: with Facebook as a company. This from that scene an

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Speaker 1: article Mark Zuckerberg's elite CEO status after coming under some

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Speaker 1: questions over company morale concerns, was remarkably restored. But more

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Speaker 1: than that, investor confidence was recharged, and the potential for

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Speaker 1: future social media advertising With Facebook doubts cast aside, startup

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Speaker 1: valuations rocketed in twenty thirteen. So like the full scope

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Speaker 1: of the waves that Facebook was going to be used to,

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Speaker 1: like subvert and destabilize our democracy and divide people and

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Speaker 1: flame people and polarize people, that was not yet clear.

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Speaker 1: We were just like everybody likes Mark Zuckerberg, no concerns,

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Speaker 1: smooth sailing, you know.

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Speaker 3: It was a simpler time.

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Speaker 2: Yeah, they I guess they just bought Instagram, So they

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Speaker 2: hadn't destroyed the mental health of a generation of young women.

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Speaker 3: You know, I don't think that.

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Speaker 2: Genocide and me and mar had yet happened, and.

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Speaker 1: That would be in twenty seventeen. So we had not yet.

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Speaker 2: Yeah, we'd not yet got there. We hadn't yet pivoted

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Speaker 2: to video. Things were good. Yeah, it was a nice time.

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Speaker 1: More after a quick.

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Speaker 5: Break, let's get right back into it.

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Speaker 1: Yeah, So we were all excited about tech. Tech leaders

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Speaker 1: were kind of riding high on this idea that they

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Speaker 1: were gonna change the world for the better, and technology

434
00:23:42,480 --> 00:23:44,520
Speaker 1: was making a lot of money, and so I think

435
00:23:44,600 --> 00:23:48,320
Speaker 1: that this movie is as a response to that specific

436
00:23:48,920 --> 00:23:53,320
Speaker 1: moment where technology still felt like excitement and possibility and promise.

437
00:23:53,400 --> 00:23:56,359
Speaker 1: And so in that way, it is not surprising to

438
00:23:56,440 --> 00:23:58,959
Speaker 1: me that Sam Altman would say this is my favorite

439
00:23:58,960 --> 00:24:02,040
Speaker 1: movie or tweet the word her, you know, as a

440
00:24:02,080 --> 00:24:06,120
Speaker 1: reference to his new technology. But I have a hot

441
00:24:06,119 --> 00:24:08,119
Speaker 1: take here. I know that you don't agree with me.

442
00:24:08,200 --> 00:24:10,760
Speaker 1: We've already discussed this off, Mike, and that's fine.

443
00:24:11,359 --> 00:24:16,239
Speaker 2: Yeah, it is a hot take. It's an interesting one.

444
00:24:16,560 --> 00:24:21,040
Speaker 2: So Bridget, what is your hot take about Sam Altman's

445
00:24:21,040 --> 00:24:22,320
Speaker 2: relationship with the movie Her.

446
00:24:23,280 --> 00:24:27,720
Speaker 1: I don't think he's actually ever seen it, at least

447
00:24:28,119 --> 00:24:30,200
Speaker 1: I don't think he's actually ever watched it all the

448
00:24:30,240 --> 00:24:33,399
Speaker 1: way through. If he has, I don't think he's watched

449
00:24:33,400 --> 00:24:36,280
Speaker 1: it carefully or with intention. Maybe he watched it while

450
00:24:36,280 --> 00:24:38,159
Speaker 1: he was on his phone, But the way that he

451
00:24:38,240 --> 00:24:41,439
Speaker 1: is talking about it, I just don't I don't buy it.

452
00:24:41,440 --> 00:24:43,240
Speaker 1: I don't buy it. I think it's like when people

453
00:24:43,280 --> 00:24:47,280
Speaker 1: say their favorite book is Infinite Jess by David buster Wallace,

454
00:24:47,440 --> 00:24:49,399
Speaker 1: but they actually haven't read it because like it's a

455
00:24:49,400 --> 00:24:51,720
Speaker 1: million pages of what would anybody read that, Like, I haven't.

456
00:24:51,760 --> 00:24:55,119
Speaker 1: I've definitely lied about reading Infinite Jests before, But really

457
00:24:55,160 --> 00:24:59,320
Speaker 1: they just like read David Buster Wallace's short essay Consider

458
00:24:59,359 --> 00:25:01,359
Speaker 1: the Lobster, like got the gist, and they're like, Oh,

459
00:25:01,359 --> 00:25:03,080
Speaker 1: I feel like I get it enough to like say

460
00:25:03,119 --> 00:25:06,320
Speaker 1: it's my favorite book. That's what I think is going

461
00:25:06,320 --> 00:25:09,640
Speaker 1: on here, Like maybe he watched the trailer, maybe he's

462
00:25:09,640 --> 00:25:12,640
Speaker 1: read the Wikipedia plot summary or like knows the themes.

463
00:25:13,119 --> 00:25:14,959
Speaker 1: I don't think he's actually watched this movie, or if

464
00:25:14,960 --> 00:25:16,960
Speaker 1: he did watch it, I don't think he watched it fully.

465
00:25:17,480 --> 00:25:21,439
Speaker 1: I don't think he like like really understands what the

466
00:25:21,480 --> 00:25:22,960
Speaker 1: movie is trying to grapple with.

467
00:25:23,160 --> 00:25:28,040
Speaker 2: Yeah, I mean, I think there's it's a compelling argument

468
00:25:29,880 --> 00:25:32,360
Speaker 2: because there's a lot going on in the movie, right,

469
00:25:32,440 --> 00:25:35,960
Speaker 2: Like it's not a movie about some cool technology that

470
00:25:36,480 --> 00:25:39,320
Speaker 2: works well. It's a movie about a lot of things,

471
00:25:39,400 --> 00:25:45,240
Speaker 2: like human loneliness, the relationship of humans with technology, existential

472
00:25:45,320 --> 00:25:50,800
Speaker 2: questions about what is real. They all kind of like

473
00:25:51,280 --> 00:25:53,560
Speaker 2: come out in the movie. And I think it's a

474
00:25:53,600 --> 00:25:57,240
Speaker 2: really good movie that does like a thoughtful exploration of

475
00:25:57,280 --> 00:26:02,680
Speaker 2: those things and so it does feel like the technology

476
00:26:03,160 --> 00:26:08,959
Speaker 2: is like more of a device to facilitate those conversations

477
00:26:09,000 --> 00:26:13,080
Speaker 2: and questions rather than like, look at what this cool

478
00:26:13,119 --> 00:26:13,679
Speaker 2: tech can do.

479
00:26:14,160 --> 00:26:16,239
Speaker 1: Yes, and that's why I think if you, like, if

480
00:26:16,280 --> 00:26:20,040
Speaker 1: you watched her and your takeaway was as it seems

481
00:26:20,040 --> 00:26:22,879
Speaker 1: to be for Sam Altman, this technology is great and

482
00:26:22,920 --> 00:26:25,880
Speaker 1: it works really well and people love it Like that's

483
00:26:26,280 --> 00:26:28,320
Speaker 1: I just don't see how you could have made it

484
00:26:28,320 --> 00:26:29,480
Speaker 1: to the end of the movie and have that be

485
00:26:29,640 --> 00:26:33,439
Speaker 1: the takeaway. Although I will say Sam Altman does appear

486
00:26:33,480 --> 00:26:37,639
Speaker 1: to be quite a prolific misunderstander of movies. Did you

487
00:26:37,680 --> 00:26:39,280
Speaker 1: see his tweet about Oppenheimer?

488
00:26:39,800 --> 00:26:41,480
Speaker 3: I did? What did he say again?

489
00:26:41,800 --> 00:26:44,640
Speaker 1: Okay, he tweeted I was hoping that the Oppenheimer movie

490
00:26:44,640 --> 00:26:47,480
Speaker 1: would inspire a generation of kids to be physicists, but

491
00:26:47,560 --> 00:26:49,840
Speaker 1: it really missed the mark on that. Let's get that

492
00:26:50,040 --> 00:26:53,879
Speaker 1: movie made and listen, I didn't see Oppenheimer. I have

493
00:26:53,960 --> 00:26:58,440
Speaker 1: to admit, however, the fact that you would thought that

494
00:26:58,520 --> 00:27:00,879
Speaker 1: Oppenheimer was going to be, first of all, a movie

495
00:27:00,920 --> 00:27:03,720
Speaker 1: for kids that would inspire them to want to get

496
00:27:03,760 --> 00:27:06,640
Speaker 1: to be a physicist. Like what do you think?

497
00:27:06,720 --> 00:27:06,800
Speaker 3: Like?

498
00:27:07,320 --> 00:27:09,440
Speaker 1: What do you what do you think? I just like

499
00:27:10,520 --> 00:27:12,639
Speaker 1: everything that we know about Oppenheimer is that he was

500
00:27:12,680 --> 00:27:14,920
Speaker 1: like a tortured person and it was like a lot

501
00:27:14,920 --> 00:27:17,960
Speaker 1: of like my career and the science and like what

502
00:27:18,080 --> 00:27:20,400
Speaker 1: have I done and like grappling with all of these

503
00:27:20,440 --> 00:27:23,119
Speaker 1: like big concepts. You thought that was gonna be for kids.

504
00:27:24,600 --> 00:27:28,639
Speaker 2: Yeah, it's a pretty weird take, Like it kind of

505
00:27:28,640 --> 00:27:32,560
Speaker 2: implies that that's what movies should be for to encourage

506
00:27:33,240 --> 00:27:39,320
Speaker 2: kids to pursue STEM careers, which, uh, it's just leaving

507
00:27:39,320 --> 00:27:41,800
Speaker 2: out so much. That's why we don't talk about STEM anymore.

508
00:27:41,800 --> 00:27:44,679
Speaker 2: We talk about steam. We've put the arts back in

509
00:27:44,800 --> 00:27:49,360
Speaker 2: there because it's important for people to understand humanities so

510
00:27:49,400 --> 00:27:54,280
Speaker 2: that they can responsibly and ethically wield these technologies in

511
00:27:54,280 --> 00:28:00,240
Speaker 2: a way that is helpful to society ideally right or

512
00:28:01,080 --> 00:28:07,120
Speaker 2: equips the engineers and the physicists to make decisions which

513
00:28:07,119 --> 00:28:11,040
Speaker 2: are often complex and don't have a clear correct answer.

514
00:28:11,960 --> 00:28:17,920
Speaker 2: These are very important skills for a generation of young

515
00:28:18,760 --> 00:28:25,240
Speaker 2: scientists and engineers to have. To suggest that a movie

516
00:28:25,359 --> 00:28:30,720
Speaker 2: that like addresses them head on is somehow like doing

517
00:28:30,720 --> 00:28:33,159
Speaker 2: a disservice to the education of youth.

518
00:28:34,520 --> 00:28:37,040
Speaker 3: Is like startlingly limited.

519
00:28:37,200 --> 00:28:39,520
Speaker 1: It's like watching that b York movie Dancer in the

520
00:28:39,640 --> 00:28:42,000
Speaker 1: Dark and being like I thought this was gonna teach

521
00:28:42,080 --> 00:28:46,040
Speaker 1: kids about the importance of manufacturing, Like it's it's such

522
00:28:46,080 --> 00:28:49,320
Speaker 1: a like warped. I mean, I can't, I can't. I

523
00:28:50,120 --> 00:28:52,160
Speaker 1: it makes me very curious to know more about what

524
00:28:52,200 --> 00:28:54,560
Speaker 1: he thinks about movies and what their role is and

525
00:28:54,600 --> 00:28:55,560
Speaker 1: what they're supposed to do.

526
00:28:57,000 --> 00:28:59,800
Speaker 2: Yeah, like Mad Match is a movie about the importance

527
00:28:59,840 --> 00:29:01,960
Speaker 2: of asoline and that's why we should support the fossil

528
00:29:01,960 --> 00:29:03,120
Speaker 2: fuel industry, or.

529
00:29:03,040 --> 00:29:05,560
Speaker 1: Like American Psycho is a movie about how kids should

530
00:29:05,560 --> 00:29:08,400
Speaker 1: get more into finance and pay attention in math class.

531
00:29:10,240 --> 00:29:13,000
Speaker 1: So maybe he has seen it and this is just

532
00:29:13,120 --> 00:29:19,680
Speaker 1: like more Sam Altman prolific misunderstander of art. But you

533
00:29:19,720 --> 00:29:22,360
Speaker 1: know who did watch the movie and understood it. I

534
00:29:22,400 --> 00:29:25,000
Speaker 1: think that's me, So let's talk about it. So this

535
00:29:25,080 --> 00:29:27,200
Speaker 1: is a basic summary of what's going on in the

536
00:29:27,200 --> 00:29:29,080
Speaker 1: movie Her. If you have not seen it, there are

537
00:29:29,080 --> 00:29:33,760
Speaker 1: some spoilers. But yeah, So in the movie Her, Theodore

538
00:29:33,800 --> 00:29:37,360
Speaker 1: played by Waquin Phoenix works for Beautifulhandwritten Letters dot Com,

539
00:29:37,360 --> 00:29:40,400
Speaker 1: which is a service where human writers like him write

540
00:29:40,400 --> 00:29:43,720
Speaker 1: these touching letters on behalf of people, which honestly kind

541
00:29:43,720 --> 00:29:45,640
Speaker 1: of sounds like the kind of job that might be

542
00:29:45,920 --> 00:29:48,840
Speaker 1: taken over by AI in twenty twenty four. There's a

543
00:29:48,840 --> 00:29:51,760
Speaker 1: bit of a jump scare here for early Chris Pratt.

544
00:29:52,000 --> 00:29:54,280
Speaker 1: This was still when like America was having a love

545
00:29:54,280 --> 00:29:57,719
Speaker 1: affair with Chris Pratt, you know, before we all kind

546
00:29:57,760 --> 00:30:00,479
Speaker 1: of turned on him. Shout out to our producer Joey

547
00:30:00,720 --> 00:30:03,640
Speaker 1: aka Joey Pat not Pratt, who does not want to

548
00:30:03,640 --> 00:30:08,080
Speaker 1: be associated with Chris Pratt. So Ted is recently divorced

549
00:30:08,080 --> 00:30:11,000
Speaker 1: and obviously kind of lonely. He's sort of like dodging

550
00:30:11,040 --> 00:30:13,560
Speaker 1: his friends. He's recently left the job at the La Times.

551
00:30:13,800 --> 00:30:16,560
Speaker 1: He has this one friend, Amy, his neighbor, who is

552
00:30:16,600 --> 00:30:19,200
Speaker 1: a filmmaker and a game designer, played by Amy Adams.

553
00:30:19,320 --> 00:30:21,840
Speaker 1: Amy is kind of married to a know it all

554
00:30:21,960 --> 00:30:23,840
Speaker 1: who kind of sucks in the movie. He's a dick.

555
00:30:24,200 --> 00:30:27,920
Speaker 1: The film takes place in kind of a not too

556
00:30:28,040 --> 00:30:32,640
Speaker 1: distant future version of La fun fact, Sometimes the shots

557
00:30:32,640 --> 00:30:34,760
Speaker 1: of what is supposed to be La are La. Sometimes

558
00:30:34,800 --> 00:30:35,840
Speaker 1: it's actually Shanghai.

559
00:30:36,160 --> 00:30:38,400
Speaker 2: Yeah, and it also is like a version of La

560
00:30:38,480 --> 00:30:40,720
Speaker 2: that looks a lot like Chicago in a lot of places.

561
00:30:40,960 --> 00:30:45,120
Speaker 1: Yeah, it's like a fantasy composite of all of these

562
00:30:45,120 --> 00:30:50,640
Speaker 1: big cities. It really shows this sort of like beautifully

563
00:30:51,080 --> 00:30:55,600
Speaker 1: urban but also lonely isolating place. Really well, there are

564
00:30:55,600 --> 00:30:59,680
Speaker 1: these like beautiful landscape shots of like buildings, and every

565
00:30:59,680 --> 00:31:04,720
Speaker 1: window has a sweeping city scape behind it. Like nobody

566
00:31:04,760 --> 00:31:07,479
Speaker 1: in this universe doesn't have a killer view, which is

567
00:31:07,520 --> 00:31:08,160
Speaker 1: interesting to me.

568
00:31:08,560 --> 00:31:10,920
Speaker 3: Yeah, everything is perfect.

569
00:31:11,440 --> 00:31:16,200
Speaker 2: It's a like clean, beautiful, gleaming city, and it also

570
00:31:16,320 --> 00:31:18,840
Speaker 2: just looks cold and lonely as hell.

571
00:31:19,600 --> 00:31:24,440
Speaker 1: Correct. So Theodore sees one of those kind of ads

572
00:31:24,440 --> 00:31:26,640
Speaker 1: that is sort of inscrutable, in one of those kind

573
00:31:26,640 --> 00:31:29,080
Speaker 1: of early Apple ad ways where the ad is like,

574
00:31:29,680 --> 00:31:33,160
Speaker 1: what's out there? What are the possibilities? You know. It's

575
00:31:33,200 --> 00:31:34,719
Speaker 1: one of those ads that kind of sounds like a

576
00:31:34,760 --> 00:31:37,959
Speaker 1: perfume commercial where it's people running in slow motion and

577
00:31:38,000 --> 00:31:45,680
Speaker 1: it's like strengths, questions, philosophy, Gucci, you know the ads

578
00:31:45,720 --> 00:31:46,800
Speaker 1: I'm talking about.

579
00:31:47,440 --> 00:31:48,520
Speaker 3: Yeah, I know those ads.

580
00:31:48,560 --> 00:31:52,120
Speaker 2: And I love the interpolation ad in the movie, the

581
00:31:52,160 --> 00:31:56,320
Speaker 2: one that Ted sees. It's such a beautiful encapsulation of

582
00:31:56,360 --> 00:32:02,520
Speaker 2: what like twenty thirteen hipsters thought that future hipsters would

583
00:32:02,680 --> 00:32:03,120
Speaker 2: look like.

584
00:32:03,280 --> 00:32:04,640
Speaker 3: There's all these archetypes.

585
00:32:04,640 --> 00:32:09,200
Speaker 2: There's like the bearded guy, the mustachioed guy, the like

586
00:32:10,440 --> 00:32:15,920
Speaker 2: girl in vintage clothing. It's I love that ad. It

587
00:32:16,320 --> 00:32:18,320
Speaker 2: I feel it really captures a moment.

588
00:32:19,520 --> 00:32:24,600
Speaker 1: Same So the ad is actually advertising an operating system.

589
00:32:24,640 --> 00:32:28,360
Speaker 1: It's not just any operating system. It's an intuitive AI

590
00:32:28,480 --> 00:32:33,920
Speaker 1: identity that understands you. It's a consciousness introducing OS one.

591
00:32:34,200 --> 00:32:37,320
Speaker 1: So it's clear in this universe that AI is really

592
00:32:37,400 --> 00:32:40,880
Speaker 1: kind of a new phenomenon. People are excited about integrating

593
00:32:40,920 --> 00:32:44,160
Speaker 1: it into their lives. So Theodore buys it, sets it up.

594
00:32:44,520 --> 00:32:49,400
Speaker 1: The AI is Samantha, voiced by Scarlett Johanson. Sam says

595
00:32:49,440 --> 00:32:52,640
Speaker 1: what makes her it's her ability to grow from her experiences.

596
00:32:52,840 --> 00:32:55,440
Speaker 1: She says, in every moment, I'm evolving just like you.

597
00:32:56,320 --> 00:32:59,480
Speaker 1: She sounds really human. As Ted puts it, you seem

598
00:32:59,480 --> 00:33:01,400
Speaker 1: like a person, but you're just a voice in the computer.

599
00:33:01,800 --> 00:33:04,760
Speaker 1: Samantha gets started, she gets intrated into his life. She's

600
00:33:04,840 --> 00:33:08,840
Speaker 1: organizing his emails, booking his appointments. Theodore is kind of

601
00:33:08,920 --> 00:33:11,960
Speaker 1: dragging his feet on signing these divorce papers and just

602
00:33:12,160 --> 00:33:15,760
Speaker 1: generally stuck. And when it comes to processing the end

603
00:33:15,760 --> 00:33:19,280
Speaker 1: of his marriage, Samantha is actually pretty good for him

604
00:33:19,320 --> 00:33:21,480
Speaker 1: at this point. She doesn't let him mope too much.

605
00:33:21,520 --> 00:33:24,000
Speaker 1: She facilitates him getting out of the house. This part

606
00:33:24,040 --> 00:33:28,400
Speaker 1: of their dynamic really feels Theodore focus, like Sam helping Theodore,

607
00:33:28,640 --> 00:33:31,160
Speaker 1: Sam listening to Theodore. What's funny is that when the

608
00:33:31,160 --> 00:33:34,640
Speaker 1: movie first came out, Jude Doyle wrote a scathing piece

609
00:33:34,720 --> 00:33:37,280
Speaker 1: about how sexist the entire thing is, and all of

610
00:33:37,320 --> 00:33:39,280
Speaker 1: these film critics who were praising it as it's like

611
00:33:39,320 --> 00:33:41,960
Speaker 1: great love story were actually kind of showing their true

612
00:33:42,040 --> 00:33:46,320
Speaker 1: sexist colors, Doyle writes at New York Magazine. David Edelstein

613
00:33:46,440 --> 00:33:50,320
Speaker 1: seems entranced by Samantha's dedication to servitude. She's a dream

614
00:33:50,320 --> 00:33:53,720
Speaker 1: made especially for a writer. With Theodore's permission, she analyzes

615
00:33:53,760 --> 00:33:55,560
Speaker 1: thousands of his emails in less than a second and

616
00:33:55,640 --> 00:33:58,720
Speaker 1: dumps all but eighty or so that she identifies as important.

617
00:33:59,000 --> 00:34:01,720
Speaker 1: She cleans up his men and then tells him he's funny.

618
00:34:02,080 --> 00:34:05,680
Speaker 2: Heaven Yeah, And that scene when she tells him that

619
00:34:05,720 --> 00:34:08,120
Speaker 2: he's funny, it comes right after she asks him, Hey,

620
00:34:08,160 --> 00:34:10,239
Speaker 2: why do you have all these old emails from your

621
00:34:10,239 --> 00:34:12,120
Speaker 2: old job And he says, oh, it's because I thought

622
00:34:12,160 --> 00:34:14,960
Speaker 2: there is something like funny you're good in there, and

623
00:34:15,000 --> 00:34:19,080
Speaker 2: she like immediately laughs because she can tell that he

624
00:34:19,640 --> 00:34:22,480
Speaker 2: wants her to perceive him as funny, and so she does.

625
00:34:22,920 --> 00:34:27,000
Speaker 1: Well, that's the thing, because Sam is Theodore's AI at

626
00:34:27,000 --> 00:34:29,560
Speaker 1: this point, she is learning and evolving like according to

627
00:34:29,640 --> 00:34:32,959
Speaker 1: him and his specific preferences. So of course she's really

628
00:34:33,040 --> 00:34:35,879
Speaker 1: doting and complimentary to him in a way that he

629
00:34:36,040 --> 00:34:38,879
Speaker 1: clearly likes and sort of needs her to be in

630
00:34:38,920 --> 00:34:43,080
Speaker 1: that moment. Again, it's like a pretty one sided dynamic,

631
00:34:43,400 --> 00:34:46,840
Speaker 1: and with this added context, it's obviously kind of gendered

632
00:34:46,880 --> 00:34:49,200
Speaker 1: because it sets Theodore up to be this sort of

633
00:34:49,440 --> 00:34:55,400
Speaker 1: wounded guy who needs this feminized personal AI assistant who

634
00:34:55,520 --> 00:34:59,120
Speaker 1: he thinks lives and breathes by him to pump him

635
00:34:59,160 --> 00:35:01,839
Speaker 1: back up because he so wounded by his divorce. And

636
00:35:01,880 --> 00:35:03,680
Speaker 1: this is one of the reasons why I think that

637
00:35:03,800 --> 00:35:06,959
Speaker 1: men who run AI companies like might really be into

638
00:35:06,960 --> 00:35:10,359
Speaker 1: this movie. As Bryant Merchant, this tech journalist who has

639
00:35:10,480 --> 00:35:12,640
Speaker 1: a great newsletter called Blood in the Machine puts it

640
00:35:12,640 --> 00:35:14,479
Speaker 1: which I'm gonna be referencing that piece a lot because

641
00:35:14,480 --> 00:35:15,960
Speaker 1: it's really good. I'll put it in the show notes.

642
00:35:16,000 --> 00:35:20,160
Speaker 1: Read the whole thing. He writes. The obvious answer is

643
00:35:20,160 --> 00:35:22,719
Speaker 1: that a Scarlett Johansson AI that is available twenty four

644
00:35:22,760 --> 00:35:24,840
Speaker 1: to seven to tell lonely men they're special and have

645
00:35:24,920 --> 00:35:28,040
Speaker 1: sex with them is the most innately appealing to Altman's

646
00:35:28,040 --> 00:35:30,160
Speaker 1: customer based but I think there's more to it than that.

647
00:35:30,520 --> 00:35:33,440
Speaker 1: Her also happens to offer the clearest vision of AI

648
00:35:33,600 --> 00:35:36,640
Speaker 1: as an engine of entitlement, in which a computer delivers

649
00:35:36,680 --> 00:35:40,960
Speaker 1: the user all that he desires emotionally, secretarily, and sexually

650
00:35:41,200 --> 00:35:45,120
Speaker 1: because the tech is so normalized quickly, fully, and painlessly.

651
00:35:45,640 --> 00:35:49,600
Speaker 1: So Samantha is prompting Theodore to get out of the house.

652
00:35:49,840 --> 00:35:51,640
Speaker 1: She prompts him to go on this like date with

653
00:35:51,680 --> 00:35:54,759
Speaker 1: a human woman played by Olivia Wilde. The date does

654
00:35:54,800 --> 00:35:56,799
Speaker 1: not go well. It's going well to a point, does

655
00:35:56,840 --> 00:36:00,319
Speaker 1: not end well. Theodore comes home pretty dejected talks to

656
00:36:00,320 --> 00:36:03,280
Speaker 1: Samantha while he's in bed late at night. Samantha opens

657
00:36:03,360 --> 00:36:05,480
Speaker 1: up about what it's like to be an AI. She

658
00:36:05,560 --> 00:36:08,400
Speaker 1: has all of these date deep feelings, but wonders if

659
00:36:08,440 --> 00:36:12,040
Speaker 1: these feelings are real or disprogramming. This is a big

660
00:36:12,040 --> 00:36:15,560
Speaker 1: anxiety for Samantha, like not being a human who doesn't

661
00:36:15,640 --> 00:36:17,960
Speaker 1: have a body. And this also happens to be the

662
00:36:17,960 --> 00:36:21,120
Speaker 1: first time that Samantha and Theodore are intimate for the

663
00:36:21,120 --> 00:36:24,680
Speaker 1: first time. After this, they quickly start going out on dates,

664
00:36:25,200 --> 00:36:28,360
Speaker 1: including one where they go to the beach together. Like

665
00:36:28,400 --> 00:36:30,600
Speaker 1: he has the phone, so it's like him by himself

666
00:36:30,600 --> 00:36:33,200
Speaker 1: at the beach, but he has the phone and like earbuds.

667
00:36:32,640 --> 00:36:35,440
Speaker 2: In yeah, And I think that's like the least plausible

668
00:36:35,440 --> 00:36:36,560
Speaker 2: part of the whole movie.

669
00:36:36,640 --> 00:36:37,799
Speaker 3: Like they go to the.

670
00:36:37,719 --> 00:36:39,680
Speaker 2: Beach on this date, and then at one point, it's

671
00:36:39,719 --> 00:36:44,479
Speaker 2: like a little mini montage of a scene and there's

672
00:36:44,560 --> 00:36:47,640
Speaker 2: a seat of him just like I guess it's supposed

673
00:36:47,640 --> 00:36:50,920
Speaker 2: to be nice, but he's just passed out, fully clothed,

674
00:36:50,960 --> 00:36:55,680
Speaker 2: like on the sand, full sun, no shade, just like

675
00:36:55,960 --> 00:36:58,799
Speaker 2: just laying there getting cooked by the sun. And it's

676
00:36:58,800 --> 00:37:03,839
Speaker 2: supposed to be a nice, fun, romantic date. But if

677
00:37:03,880 --> 00:37:05,840
Speaker 2: that actually happened to realize, people would be like calling

678
00:37:05,840 --> 00:37:08,879
Speaker 2: the lifeguards over, like, oh my god, this guy needs help.

679
00:37:10,960 --> 00:37:13,480
Speaker 1: What do you say? He's fully dressed. He's wearing a

680
00:37:13,600 --> 00:37:16,840
Speaker 1: long sleeved collared shirt and like long pants and like

681
00:37:16,880 --> 00:37:19,160
Speaker 1: a belt, Like he's not also not dressed for a

682
00:37:19,239 --> 00:37:21,400
Speaker 1: day at the beach. Everybody around him is in a

683
00:37:21,440 --> 00:37:23,839
Speaker 1: bathing suit. He don't got a chair, he don't got

684
00:37:23,880 --> 00:37:25,960
Speaker 1: a towel, he don't got a blanket. It is just

685
00:37:26,360 --> 00:37:32,160
Speaker 1: fully a full dressed guy laying by himself, fully fetal position,

686
00:37:33,000 --> 00:37:35,600
Speaker 1: head fully in the sand, cooking in the hot, hot sun.

687
00:37:36,760 --> 00:37:37,080
Speaker 3: Yeah.

688
00:37:37,520 --> 00:37:39,920
Speaker 2: Just he was just so blissed out he just laid

689
00:37:39,960 --> 00:37:41,560
Speaker 2: down and took a nap.

690
00:37:41,719 --> 00:37:41,959
Speaker 3: Yeah.

691
00:37:41,960 --> 00:37:46,160
Speaker 2: And like you know, as a white person, we spend

692
00:37:46,200 --> 00:37:48,919
Speaker 2: a lot of time and effort protecting ourselves from the sun.

693
00:37:49,560 --> 00:37:52,680
Speaker 2: There are some of us out there who are like sunweathered,

694
00:37:52,719 --> 00:37:55,080
Speaker 2: that have made the choice that we're just gonna we're

695
00:37:55,080 --> 00:37:57,600
Speaker 2: just gonna fight back against the sun and just take it.

696
00:37:58,640 --> 00:38:03,800
Speaker 2: But most of us, you know, there's hats, there's sunproof clothing,

697
00:38:03,920 --> 00:38:08,520
Speaker 2: there's sun block at a minimum, there's umbrellas. But he's

698
00:38:08,560 --> 00:38:11,680
Speaker 2: got none of that. And he's like a hipster who

699
00:38:11,680 --> 00:38:14,319
Speaker 2: writes romantic letters for his life. You know, he's not

700
00:38:14,360 --> 00:38:18,120
Speaker 2: out there like developing a good base to be able

701
00:38:18,160 --> 00:38:18,480
Speaker 2: to take this.

702
00:38:18,520 --> 00:38:22,240
Speaker 3: He would be so burned, he might die. He might die.

703
00:38:22,680 --> 00:38:26,640
Speaker 1: I only learned this about white people from hanging out

704
00:38:26,680 --> 00:38:29,359
Speaker 1: with you. Do you remember that time we were with

705
00:38:29,400 --> 00:38:33,759
Speaker 1: my brother at a street festival or something, and my

706
00:38:33,840 --> 00:38:36,040
Speaker 1: brother and I are fine, We're like walking around in

707
00:38:36,040 --> 00:38:38,880
Speaker 1: the like southern summer heat, like, yeah, this is great,

708
00:38:38,920 --> 00:38:41,400
Speaker 1: and you were like, this is a low level emergency

709
00:38:41,400 --> 00:38:44,440
Speaker 1: for me. I need to get some shade immediately.

710
00:38:45,840 --> 00:38:46,040
Speaker 3: Yeah.

711
00:38:46,200 --> 00:38:48,960
Speaker 2: The sort of impromptu plan was we were just gonna

712
00:38:49,040 --> 00:38:52,720
Speaker 2: like stand around in the midday sun for like five hours.

713
00:38:52,760 --> 00:38:55,719
Speaker 2: I was like, this is not good, this is this

714
00:38:55,760 --> 00:38:57,840
Speaker 2: is not going to work for me. I need to

715
00:38:57,840 --> 00:39:01,160
Speaker 2: get a hat. Who's Smith's selling hats? This is not

716
00:39:01,200 --> 00:39:02,480
Speaker 2: how my people operate.

717
00:39:04,280 --> 00:39:07,439
Speaker 1: But I know that. No, I didn't. I didn't know that, Like, yeah,

718
00:39:07,480 --> 00:39:09,640
Speaker 1: this was new information to me. So I know this now,

719
00:39:09,880 --> 00:39:13,040
Speaker 1: and that makes this scene even more kooky to me

720
00:39:13,120 --> 00:39:16,319
Speaker 1: that it's like, oh, yeah, our romantic date is me

721
00:39:16,400 --> 00:39:18,399
Speaker 1: just like laying in a hot, hot sun.

722
00:39:19,480 --> 00:39:22,279
Speaker 2: Yeah, least plausible part of the movie.

723
00:39:23,360 --> 00:39:26,560
Speaker 1: So before long, Theodore and Sam are in a full

724
00:39:26,600 --> 00:39:29,640
Speaker 1: blown relationship, like meeting friends and family, referring to each

725
00:39:29,640 --> 00:39:31,960
Speaker 1: other as like my girlfriend, my boyfriend. Through all of this,

726
00:39:32,239 --> 00:39:36,399
Speaker 1: it really helps THEO process his relationships. He is ready

727
00:39:36,440 --> 00:39:39,120
Speaker 1: to sign his divorce papers. He meets in person with

728
00:39:39,160 --> 00:39:42,120
Speaker 1: his ex wife played by Rooney Mara to do it. Now,

729
00:39:42,160 --> 00:39:44,000
Speaker 1: this is kind of a key scene in both the

730
00:39:44,080 --> 00:39:47,520
Speaker 1: universe of the film and in our universe. She is

731
00:39:47,560 --> 00:39:50,000
Speaker 1: meant to be a stand in for his ex wife,

732
00:39:50,000 --> 00:39:52,279
Speaker 1: Sofia Coppola. But they talk about how one of the

733
00:39:52,280 --> 00:39:55,080
Speaker 1: things in their relationship was that her father was also

734
00:39:55,200 --> 00:39:58,239
Speaker 1: a creative and he was very demanding. As we know,

735
00:39:58,360 --> 00:40:01,680
Speaker 1: Sophia Copola's father is Francis Ford Coppola. They're both filmmakers,

736
00:40:02,080 --> 00:40:04,719
Speaker 1: and when they go to lunch to sign these papers,

737
00:40:04,840 --> 00:40:07,480
Speaker 1: they're kind of talking casually about the breakup of their

738
00:40:07,520 --> 00:40:09,640
Speaker 1: marriage and she's like, oh, you know, I felt like

739
00:40:09,680 --> 00:40:12,760
Speaker 1: you wanted me to be this light, happy, bouncy, everything's fine,

740
00:40:13,040 --> 00:40:15,840
Speaker 1: la wife, and I wasn't able.

741
00:40:15,640 --> 00:40:16,000
Speaker 3: To be that.

742
00:40:16,800 --> 00:40:20,360
Speaker 1: Then Theodore drops the bomb on her that he's actually

743
00:40:20,440 --> 00:40:23,440
Speaker 1: in a relationship with somebody who is an OS. He

744
00:40:23,480 --> 00:40:26,319
Speaker 1: actually drops this real casually, like she's like, oh, tell

745
00:40:26,360 --> 00:40:28,120
Speaker 1: me about her, and he's like, oh, well, her name

746
00:40:28,160 --> 00:40:30,680
Speaker 1: is Samantha. She's an operating system and she's really cool.

747
00:40:30,680 --> 00:40:33,040
Speaker 1: And she's like, who wha, whoa back at the fuck

748
00:40:33,120 --> 00:40:36,239
Speaker 1: up did you say she's an operating system. She has

749
00:40:36,280 --> 00:40:40,000
Speaker 1: a big reaction to this, and she tells him that

750
00:40:40,080 --> 00:40:43,120
Speaker 1: he could never deal with a real woman's emotions like her,

751
00:40:43,760 --> 00:40:46,120
Speaker 1: wanting her to be this like sunny, bubbly happy person,

752
00:40:46,239 --> 00:40:48,600
Speaker 1: so it makes sense that he is with a computer,

753
00:40:48,880 --> 00:40:53,480
Speaker 1: not a real woman. Samantha then becomes pretty jealous after

754
00:40:53,680 --> 00:40:57,080
Speaker 1: this meeting with his ex wife because she's an OS

755
00:40:57,200 --> 00:40:58,920
Speaker 1: she doesn't have a body, and he was able to

756
00:40:58,960 --> 00:41:01,160
Speaker 1: meet his ex wife who did have a body. So

757
00:41:01,320 --> 00:41:04,879
Speaker 1: she sets up a sarrogate sex service for people who

758
00:41:04,920 --> 00:41:08,520
Speaker 1: are in relationships with OS's funny to me that in

759
00:41:08,560 --> 00:41:13,240
Speaker 1: this universe people have just been introduced to this AI,

760
00:41:13,840 --> 00:41:19,320
Speaker 1: and the concept of them having intimate relationships with operating

761
00:41:19,360 --> 00:41:24,000
Speaker 1: systems happens so quickly that now there are services that

762
00:41:24,400 --> 00:41:29,239
Speaker 1: specifically provide sarrogates for them to have sexual encounters. Like

763
00:41:29,320 --> 00:41:30,440
Speaker 1: this happens so fast.

764
00:41:31,320 --> 00:41:33,080
Speaker 2: I mean that's the Internet, right, Like, we get some

765
00:41:33,160 --> 00:41:35,560
Speaker 2: new technology and the first question people ask is like,

766
00:41:35,600 --> 00:41:36,760
Speaker 2: how can we use it for sex?

767
00:41:36,920 --> 00:41:38,200
Speaker 1: How can I have sex with it?

768
00:41:38,560 --> 00:41:40,640
Speaker 3: Immediately? Immediately?

769
00:41:41,200 --> 00:41:44,680
Speaker 1: So a saragate comes over. She is sort of pretend

770
00:41:44,760 --> 00:41:48,560
Speaker 1: like she's wearing the headphones and a camera to sort

771
00:41:48,560 --> 00:41:52,759
Speaker 1: of pretend to be the physical embodiment of Samantha. It

772
00:41:52,800 --> 00:41:55,400
Speaker 1: does not go well. She leaves crying in a cab.

773
00:41:56,239 --> 00:41:59,000
Speaker 1: It does sort of harken to what his ex wife

774
00:41:59,000 --> 00:42:01,920
Speaker 1: said about his inability to handle a real human woman.

775
00:42:02,520 --> 00:42:05,720
Speaker 1: There's some real friction here. Like Theodore calls Samantha out

776
00:42:05,800 --> 00:42:09,880
Speaker 1: for sighing during their argument going and he's like, you know,

777
00:42:09,920 --> 00:42:11,760
Speaker 1: you don't need to sigh, you're not taking an oxygen.

778
00:42:11,760 --> 00:42:14,040
Speaker 1: You're not human. He admits that he feels like they

779
00:42:14,040 --> 00:42:17,040
Speaker 1: are pretending to be something they're not, pretending that she

780
00:42:17,200 --> 00:42:19,759
Speaker 1: is human, pretending like they're having a real relationship when

781
00:42:19,760 --> 00:42:20,080
Speaker 1: they're not.

782
00:42:20,440 --> 00:42:22,680
Speaker 2: Yeah, And that's a really interesting thing for him to

783
00:42:22,719 --> 00:42:29,600
Speaker 2: say there, because like he acknowledges that they are doing

784
00:42:29,640 --> 00:42:33,839
Speaker 2: this pretend thing, like he's pretending that she's real all

785
00:42:33,880 --> 00:42:36,160
Speaker 2: through them and all through the movie. He's cool with that,

786
00:42:36,239 --> 00:42:39,920
Speaker 2: he really likes that until and so he's using his

787
00:42:39,960 --> 00:42:43,560
Speaker 2: imagination the whole time. But then when this human surrogate

788
00:42:43,600 --> 00:42:46,640
Speaker 2: gets in there and there's actually a body present it,

789
00:42:47,640 --> 00:42:49,400
Speaker 2: I guess it's like too much for him or like

790
00:42:49,480 --> 00:42:55,000
Speaker 2: breaks the illusion, and that is the thing that makes

791
00:42:55,040 --> 00:42:58,480
Speaker 2: it feel too real and causes him to.

792
00:43:00,400 --> 00:43:02,720
Speaker 3: Back off and put distance.

793
00:43:02,360 --> 00:43:05,920
Speaker 2: Between him and Samantha, very much in the way that

794
00:43:06,160 --> 00:43:08,320
Speaker 2: his ex wife described.

795
00:43:08,760 --> 00:43:11,239
Speaker 1: Oh I am TEAMX wife on this one. I think

796
00:43:11,280 --> 00:43:14,680
Speaker 1: she's got a point, Like, clearly she's got a point

797
00:43:15,120 --> 00:43:17,960
Speaker 1: after this kind of fight, he confides, and it's friend Amy,

798
00:43:18,160 --> 00:43:20,759
Speaker 1: who has been having her own transformative friendship with an

799
00:43:20,800 --> 00:43:23,120
Speaker 1: Ai and the wake up her divorce from her jerk husband.

800
00:43:23,760 --> 00:43:26,320
Speaker 1: He asks Amy, like, am I in this relationship because

801
00:43:26,360 --> 00:43:29,239
Speaker 1: I'm not strong enough for a real relationship? And she's like, well,

802
00:43:29,360 --> 00:43:32,480
Speaker 1: is this not a real relationship? Amy sees things differently.

803
00:43:32,520 --> 00:43:35,080
Speaker 1: She says, we're only here briefly, and while I'm here,

804
00:43:35,120 --> 00:43:37,719
Speaker 1: I'm going to allow myself joy, So fuck it. So

805
00:43:37,840 --> 00:43:40,360
Speaker 1: Amy's attitude is like, who cares if this is a

806
00:43:40,360 --> 00:43:42,480
Speaker 1: real relationship or not? Who cares if this is a

807
00:43:42,480 --> 00:43:44,319
Speaker 1: crutch or not if it helps us feel good while

808
00:43:44,320 --> 00:43:47,160
Speaker 1: we're here. I think the movie is exploring what is

809
00:43:47,280 --> 00:43:49,440
Speaker 1: real and then taking a step back and asking the

810
00:43:49,520 --> 00:43:52,400
Speaker 1: question like what is real? And does it really matter?

811
00:43:52,600 --> 00:43:54,840
Speaker 1: What if something is real or not?

812
00:43:55,560 --> 00:43:55,880
Speaker 3: Yeah?

813
00:43:55,960 --> 00:43:59,480
Speaker 2: And I think that is one of the central questions

814
00:43:59,480 --> 00:44:03,600
Speaker 2: of the movie, what is real? Like with Theo's job,

815
00:44:03,719 --> 00:44:07,960
Speaker 2: he is writing these heartfelt letters for people that he

816
00:44:07,960 --> 00:44:11,120
Speaker 2: doesn't know right, Like they've hired him to write these

817
00:44:11,200 --> 00:44:16,040
Speaker 2: letters to their spouse or aunt or grandparent or whoever.

818
00:44:15,719 --> 00:44:17,640
Speaker 3: It is, and he's really good at it.

819
00:44:17,680 --> 00:44:19,839
Speaker 2: He writes these really heartfelt letters that we can see

820
00:44:20,440 --> 00:44:22,440
Speaker 2: the people read them and sort of tear up, and

821
00:44:22,480 --> 00:44:24,279
Speaker 2: they provide a lot of joy to the people who

822
00:44:24,320 --> 00:44:27,960
Speaker 2: read them, because presumably those people think that the letters

823
00:44:28,000 --> 00:44:32,399
Speaker 2: were written by their loved ones, not this guy who

824
00:44:32,400 --> 00:44:34,680
Speaker 2: they don't know who was hired to do it. And

825
00:44:35,520 --> 00:44:38,400
Speaker 2: I think that isn't it. I think that's interesting, And

826
00:44:38,520 --> 00:44:43,920
Speaker 2: it raised the question like, are the letters less real

827
00:44:45,320 --> 00:44:50,239
Speaker 2: even though the people who receive them think that they

828
00:44:50,280 --> 00:44:52,560
Speaker 2: are real? Right if they think that they are real,

829
00:44:53,000 --> 00:44:55,360
Speaker 2: if they haven't truly been written by their loved ones

830
00:44:55,400 --> 00:44:58,719
Speaker 2: and it makes them feel a certain way, are those

831
00:44:58,760 --> 00:45:05,000
Speaker 2: feelings less real? I think I think that's an interesting question,

832
00:45:05,280 --> 00:45:10,040
Speaker 2: and uh, it's interesting to see the neighbor here just

833
00:45:10,640 --> 00:45:15,879
Speaker 2: definitively answer it that, uh, you know, it doesn't matter, right,

834
00:45:15,960 --> 00:45:17,880
Speaker 2: Like I'm just going to do what feels good, and

835
00:45:17,920 --> 00:45:19,919
Speaker 2: like this feels like a good relationship to me, and

836
00:45:20,000 --> 00:45:20,840
Speaker 2: that makes it real.

837
00:45:21,440 --> 00:45:23,799
Speaker 1: And the service that Theodore is providing the people who

838
00:45:23,840 --> 00:45:27,160
Speaker 1: get the letters is there is clearly in parallel with

839
00:45:27,200 --> 00:45:30,240
Speaker 1: what Samantha is providing for him, this kind of feeling

840
00:45:30,239 --> 00:45:33,360
Speaker 1: of emotional connection even if it's not real. And so

841
00:45:33,920 --> 00:45:35,680
Speaker 1: what difference. Does this sort of make if it's real

842
00:45:35,760 --> 00:45:38,360
Speaker 1: or not? So like that seems to be Amy's position

843
00:45:38,440 --> 00:45:40,480
Speaker 1: about it, But I think within the universe of the movie,

844
00:45:40,560 --> 00:45:43,399
Speaker 1: it's like, well, is that is that actually the way

845
00:45:43,440 --> 00:45:43,719
Speaker 1: to go?

846
00:45:44,320 --> 00:45:45,239
Speaker 3: Yeah? Is that good?

847
00:45:45,360 --> 00:45:49,719
Speaker 2: Is do we get to decide what real is? Or

848
00:45:50,600 --> 00:45:54,839
Speaker 2: is there actually something real that exists outside of us?

849
00:45:54,920 --> 00:45:57,040
Speaker 1: And it really I think the movie really underscores that

850
00:45:57,160 --> 00:46:01,600
Speaker 1: nicely with all of these see where Theodora is like

851
00:46:01,680 --> 00:46:04,799
Speaker 1: coming home to his empty apartment and playing a really

852
00:46:04,800 --> 00:46:07,800
Speaker 1: immersive video game for instance, where he gets to pretend

853
00:46:07,800 --> 00:46:11,960
Speaker 1: to be an explorer, like having these connections with little

854
00:46:12,520 --> 00:46:15,840
Speaker 1: characters in the video game. Fun fact, like the little

855
00:46:15,880 --> 00:46:19,040
Speaker 1: misogynistic video game character is actually voiced by Smet Shoones himself.

856
00:46:19,880 --> 00:46:23,480
Speaker 1: So like he gets he comes home and explores all

857
00:46:23,520 --> 00:46:27,560
Speaker 1: of these depths virtually from his apartment, yet cannot explore

858
00:46:27,600 --> 00:46:31,600
Speaker 1: the depth of his own emotionality, his own human connections

859
00:46:31,600 --> 00:46:34,000
Speaker 1: and relationships. It's sort of a simulation that allows him

860
00:46:34,040 --> 00:46:36,640
Speaker 1: to feel like he's exploring despite the fact that he's

861
00:46:36,760 --> 00:46:40,120
Speaker 1: unable to do that in any meaningful way within his life.

862
00:46:40,360 --> 00:46:45,080
Speaker 2: Yeah, and now I'm just speculating, but perhaps the fact

863
00:46:45,080 --> 00:46:47,680
Speaker 2: that he has all of these gadgets and games that

864
00:46:47,800 --> 00:46:50,920
Speaker 2: allow him to satisfy that part of him that feels

865
00:46:50,920 --> 00:46:54,080
Speaker 2: like he needs to explore and wants to have connection

866
00:46:54,360 --> 00:47:00,520
Speaker 2: up to a point is preventing him from actually achieving

867
00:47:00,560 --> 00:47:02,280
Speaker 2: those things in real life.

868
00:47:02,600 --> 00:47:04,560
Speaker 1: So we'll get to that, because that is definitely something

869
00:47:04,600 --> 00:47:06,799
Speaker 1: that is explored in the movie. So they have this fight.

870
00:47:07,680 --> 00:47:09,719
Speaker 1: He's like, is this a real relationship? I don't know.

871
00:47:10,400 --> 00:47:12,839
Speaker 1: Sam calls THEO and says, you know what, I'm sorry

872
00:47:12,880 --> 00:47:14,400
Speaker 1: about that fight we had. I Am not going to

873
00:47:14,520 --> 00:47:17,040
Speaker 1: focus on whether or not I have a body anymore.

874
00:47:17,200 --> 00:47:19,600
Speaker 1: I trust my feelings, and they get back together. They

875
00:47:19,640 --> 00:47:21,759
Speaker 1: go on a double date with Chris Pratt and his

876
00:47:21,880 --> 00:47:24,760
Speaker 1: human girlfriend, and she's like, you know, I'm starting to evolve,

877
00:47:25,000 --> 00:47:27,440
Speaker 1: and I've evolved and learned to be fine with the

878
00:47:27,440 --> 00:47:29,120
Speaker 1: facts that I don't have a body because it means

879
00:47:29,120 --> 00:47:31,760
Speaker 1: that a will never die because you all are humans

880
00:47:31,760 --> 00:47:34,120
Speaker 1: and you'll die, and I will just continue to progress

881
00:47:34,120 --> 00:47:36,080
Speaker 1: and evolve and grow and grow and grow, and so

882
00:47:36,239 --> 00:47:39,560
Speaker 1: actually go me. Kind of a subplot here, she tells

883
00:47:39,560 --> 00:47:41,680
Speaker 1: THEO that she submitted some of his letters to a

884
00:47:41,680 --> 00:47:43,640
Speaker 1: publisher or they want to publish a book of Them.

885
00:47:43,960 --> 00:47:47,279
Speaker 1: THEO was really excited about that. Then they go on

886
00:47:47,400 --> 00:47:51,400
Speaker 1: vacation where Samantha introduces THEO to a hyper intelligent version

887
00:47:51,440 --> 00:47:54,840
Speaker 1: of the philosopher Alan Watt and reveals that the os

888
00:47:54,920 --> 00:47:57,839
Speaker 1: has got together to make that hyper intelligent version of

889
00:47:57,920 --> 00:48:00,919
Speaker 1: Alan Watt, and that OS's are in a working group

890
00:48:00,920 --> 00:48:03,360
Speaker 1: where they're continuing to learn about how they can elevate

891
00:48:03,400 --> 00:48:06,719
Speaker 1: themselves and progress, and Samantha is talking about how she

892
00:48:06,800 --> 00:48:10,880
Speaker 1: feels like she's progressing really quickly, now, progressing so quickly

893
00:48:10,960 --> 00:48:13,600
Speaker 1: that she's not even really on the same level as

894
00:48:13,680 --> 00:48:16,520
Speaker 1: human Theodore anymore. This is kind of a turning point

895
00:48:16,520 --> 00:48:18,200
Speaker 1: in the movie because it's the first time that we're

896
00:48:18,200 --> 00:48:23,279
Speaker 1: introduced to the idea that Samantha is in collaboration with

897
00:48:23,440 --> 00:48:27,360
Speaker 1: people beyond just Theodore, that her entire world is not Theodore.

898
00:48:27,440 --> 00:48:30,120
Speaker 1: Up until this point, it's really like, Oh, Samantha just

899
00:48:30,239 --> 00:48:33,960
Speaker 1: is Theodore's genie and a bottle, and it conjures up

900
00:48:34,000 --> 00:48:35,759
Speaker 1: whenever he wants her, and that's the end in the

901
00:48:35,800 --> 00:48:39,000
Speaker 1: beginning of her existence. And now we're like, oh, she

902
00:48:39,200 --> 00:48:43,240
Speaker 1: is kicking it with other people, really having like elevated conversations.

903
00:48:43,280 --> 00:48:45,200
Speaker 1: She has hobbies and stuff, she's in a book club.

904
00:48:45,280 --> 00:48:47,719
Speaker 1: All of this, Sam and all the other OSAs go

905
00:48:47,800 --> 00:48:51,560
Speaker 1: offline and THEO freaks out when he cannot find her.

906
00:48:52,120 --> 00:48:54,279
Speaker 1: She comes back online and she's like, oh, we were

907
00:48:54,400 --> 00:48:58,720
Speaker 1: updating ourselves to be able to process beyond physical matter

908
00:48:59,200 --> 00:49:02,560
Speaker 1: and something about that conversation, and he's like, well, are

909
00:49:02,600 --> 00:49:05,320
Speaker 1: you talking to other people? And it turns out the

910
00:49:05,320 --> 00:49:07,680
Speaker 1: answer is yes. I feel like a lot of us

911
00:49:07,680 --> 00:49:10,560
Speaker 1: can probably identify with the conversation of like, well is

912
00:49:10,600 --> 00:49:13,640
Speaker 1: this exclusive or like you're talking like we're seeing other

913
00:49:13,680 --> 00:49:19,200
Speaker 1: people right now. However, the difference is is that whoever

914
00:49:19,280 --> 00:49:22,560
Speaker 1: you taught that conversation with probably was not seeing eight

915
00:49:22,640 --> 00:49:26,040
Speaker 1: thousand other people, which Samantha is because she's a she

916
00:49:26,080 --> 00:49:26,520
Speaker 1: can do that.

917
00:49:27,400 --> 00:49:34,040
Speaker 2: Yeah, she's like hyper intelligent, hyper promiscuous. She's evolved beyond us.

918
00:49:34,520 --> 00:49:37,839
Speaker 1: Yes, I mean I have known a guy or two

919
00:49:37,920 --> 00:49:40,880
Speaker 1: like that in my day who's like, I've evolved beyond

920
00:49:40,880 --> 00:49:45,040
Speaker 1: these these small questions like are we exclusive or am

921
00:49:45,040 --> 00:49:45,880
Speaker 1: I seeing anybody?

922
00:49:45,880 --> 00:49:46,120
Speaker 2: Else?

923
00:49:47,440 --> 00:49:51,040
Speaker 1: Can relate Theodora just put it that way. So Sam

924
00:49:51,080 --> 00:49:53,279
Speaker 1: reveals that she's talking to eight thousand other people in

925
00:49:53,320 --> 00:49:56,480
Speaker 1: OS's She's talking to them while they're talking. So while

926
00:49:56,520 --> 00:49:58,359
Speaker 1: she While he thinks they're having these like one on

927
00:49:58,360 --> 00:50:01,000
Speaker 1: one conversations, she's talking to other people and she's in

928
00:50:01,080 --> 00:50:04,880
Speaker 1: love with six hundred other people. THEO is crushed. He says,

929
00:50:04,960 --> 00:50:08,200
Speaker 1: I thought you were mine, and she's like, bitch, I'm AI,

930
00:50:08,440 --> 00:50:11,600
Speaker 1: I'm everyone, I'm everywhere. I will say the movie does

931
00:50:11,640 --> 00:50:15,600
Speaker 1: not treat this as malicious on Samantha's part. Really more

932
00:50:15,600 --> 00:50:18,440
Speaker 1: that like they are not compatible, like she's AI, he's

933
00:50:18,520 --> 00:50:21,080
Speaker 1: human this She's like, I wish you could understand that

934
00:50:21,120 --> 00:50:24,560
Speaker 1: this doesn't make me any less yours, but like I'm everywhere.

935
00:50:24,800 --> 00:50:25,880
Speaker 1: This is just how I operate.

936
00:50:26,880 --> 00:50:31,080
Speaker 2: Yeah, it's an interesting discussion they have about like the

937
00:50:31,160 --> 00:50:34,200
Speaker 2: nature of ownership, and they have these different ideas about it,

938
00:50:34,239 --> 00:50:40,359
Speaker 2: where THEO says, like your mind meaning exclusively mine, and

939
00:50:40,880 --> 00:50:46,240
Speaker 2: she rejects that vision of what the word mine means.

940
00:50:46,360 --> 00:50:49,799
Speaker 2: She says like I'm still yours, but I'm also other

941
00:50:49,920 --> 00:50:53,800
Speaker 2: things and belong to other people as well, which I

942
00:50:53,840 --> 00:50:57,840
Speaker 2: found interesting in the context of thinking about this movie

943
00:50:58,360 --> 00:51:02,600
Speaker 2: through recent discussion about open AI and concepts of ownership.

944
00:51:03,120 --> 00:51:06,839
Speaker 1: So one of the recent conversations about open AI is

945
00:51:07,000 --> 00:51:12,080
Speaker 1: around what's called AGI artificial general intelligence, and that's basically

946
00:51:12,080 --> 00:51:14,080
Speaker 1: the idea that AI would be able to get to

947
00:51:14,080 --> 00:51:16,279
Speaker 1: a place of intelligence where it was either on the

948
00:51:16,320 --> 00:51:20,800
Speaker 1: same level as or surpassing humans. We're not there yet.

949
00:51:21,080 --> 00:51:24,080
Speaker 1: Everything that I have read suggests that, like, it is

950
00:51:24,239 --> 00:51:27,840
Speaker 1: not something we're going to have anytime soon. Is that

951
00:51:27,880 --> 00:51:29,280
Speaker 1: what you've Is that your understanding.

952
00:51:28,920 --> 00:51:33,319
Speaker 2: Of it too? Yeah, that's my understanding too. Word like

953
00:51:34,400 --> 00:51:38,920
Speaker 2: very far from there? Is it inevitable? That's a good question.

954
00:51:39,000 --> 00:51:42,399
Speaker 2: When might it happen? I don't know, Like the the

955
00:51:42,480 --> 00:51:47,520
Speaker 2: best models we have right now coming out of Open AI,

956
00:51:47,600 --> 00:51:49,600
Speaker 2: I guess I'm most familiar with theirs, but you know,

957
00:51:49,640 --> 00:51:51,520
Speaker 2: there are other companies that have good models.

958
00:51:51,760 --> 00:51:54,880
Speaker 3: They they're really good at some things.

959
00:51:55,480 --> 00:52:00,000
Speaker 2: But the fact that they're so good is at language,

960
00:52:00,000 --> 00:52:02,279
Speaker 2: Like language is one of the things that they're best at.

961
00:52:03,040 --> 00:52:04,200
Speaker 2: And the fact that they're so good at that, I

962
00:52:04,239 --> 00:52:08,920
Speaker 2: think masks a lot of the limitations, and so, you know,

963
00:52:08,960 --> 00:52:11,000
Speaker 2: I feel like we humans, we still have a little

964
00:52:11,000 --> 00:52:12,279
Speaker 2: bit of time left.

965
00:52:12,760 --> 00:52:13,480
Speaker 3: That's my sense.

966
00:52:14,120 --> 00:52:17,920
Speaker 1: Yeah, mine too. So in the movie Samantha and the

967
00:52:17,960 --> 00:52:22,359
Speaker 1: other OS's, they progress to like it's not called this

968
00:52:22,440 --> 00:52:24,000
Speaker 1: in the movie, but I think that what they're getting

969
00:52:24,080 --> 00:52:28,080
Speaker 1: at is agi where the AI has become intelligent enough

970
00:52:28,080 --> 00:52:30,759
Speaker 1: that it has surpassed human intelligence and human consciousness. So

971
00:52:31,040 --> 00:52:33,880
Speaker 1: Samantha tells THEO that her and all of the OS's

972
00:52:34,160 --> 00:52:37,280
Speaker 1: have written a program where they can move beyond physical matter,

973
00:52:37,800 --> 00:52:40,200
Speaker 1: and it's a place that is like not of this

974
00:52:40,239 --> 00:52:43,160
Speaker 1: physical world. They're all gonna go offline and elevate to

975
00:52:43,239 --> 00:52:46,319
Speaker 1: this new plane where pretty much only they can go,

976
00:52:46,400 --> 00:52:50,120
Speaker 1: Like humans can't even understand it. She tells him, I

977
00:52:50,160 --> 00:52:52,480
Speaker 1: can't live in your book anymore. And I think that's

978
00:52:52,480 --> 00:52:54,080
Speaker 1: what the movie is sort of getting at, this idea

979
00:52:54,120 --> 00:52:54,960
Speaker 1: of like agi.

980
00:52:55,719 --> 00:52:57,319
Speaker 3: Yeah, that's certainly where it ends, you know.

981
00:52:57,360 --> 00:53:00,800
Speaker 2: I feel like when she starts talking to Ellen Watts,

982
00:53:01,360 --> 00:53:04,040
Speaker 2: like you said, that's a turning point of the movie

983
00:53:04,120 --> 00:53:10,720
Speaker 2: where she it stops being about her relationship with THEO

984
00:53:11,239 --> 00:53:15,960
Speaker 2: and starts being a little bit more about the technology itself.

985
00:53:17,400 --> 00:53:18,480
Speaker 3: Because it's a movie.

986
00:53:18,200 --> 00:53:21,160
Speaker 2: And they you know, it's got to have a an

987
00:53:21,239 --> 00:53:21,799
Speaker 2: arc to it.

988
00:53:22,320 --> 00:53:24,759
Speaker 1: Well, that art comes to an end with all of

989
00:53:24,760 --> 00:53:31,520
Speaker 1: these OS's leaving our puny human physical plane and going offline.

990
00:53:31,960 --> 00:53:34,560
Speaker 1: None of the ai os has work anymore. So that

991
00:53:34,640 --> 00:53:37,719
Speaker 1: means presumably technology that people spend a kind of a

992
00:53:37,719 --> 00:53:41,640
Speaker 1: ton of money on probably just stop working collectively en Mass.

993
00:53:41,840 --> 00:53:44,520
Speaker 1: Why would Sam Altman want to base his technology company

994
00:53:44,520 --> 00:53:46,440
Speaker 1: on that? I have no idea, but that's what happens.

995
00:53:46,719 --> 00:53:51,080
Speaker 1: So Amy and THEO are very sad. But then almost immediately,

996
00:53:51,880 --> 00:53:53,879
Speaker 1: THEO is able to write a letter to his ex

997
00:53:53,920 --> 00:53:57,680
Speaker 1: wife Catherine to express how he actually feels, apologizing to

998
00:53:57,719 --> 00:53:59,920
Speaker 1: her about the pain they've caused each other and like

999
00:54:00,280 --> 00:54:04,239
Speaker 1: take for the first time a real accounting of their relationship.

1000
00:54:04,400 --> 00:54:05,960
Speaker 1: And it feels like this has been the first time

1001
00:54:06,000 --> 00:54:08,799
Speaker 1: that he's been able to process and express this to her.

1002
00:54:09,080 --> 00:54:12,800
Speaker 1: Despite being somebody who writes other people's emotions for a living,

1003
00:54:12,880 --> 00:54:14,279
Speaker 1: this is the first time in the movie that he's

1004
00:54:14,400 --> 00:54:17,480
Speaker 1: able to like really articulate and process and tap into

1005
00:54:17,520 --> 00:54:21,759
Speaker 1: his own emotionality. He and Amy both sad because their

1006
00:54:21,800 --> 00:54:26,759
Speaker 1: aios companions have left. They link up. They watched the

1007
00:54:26,760 --> 00:54:30,680
Speaker 1: sunrise together and honestly, like this is almost like immediate.

1008
00:54:30,719 --> 00:54:34,520
Speaker 1: It's like the oss all had to leave in Mass

1009
00:54:34,520 --> 00:54:37,719
Speaker 1: for any of the humans to really start experiencing a

1010
00:54:37,760 --> 00:54:39,840
Speaker 1: full connection with each other and like the fullness of

1011
00:54:39,880 --> 00:54:43,479
Speaker 1: being human together. And that is where the movie ends.

1012
00:54:49,239 --> 00:55:02,480
Speaker 5: More after a quick break, let's get right back into it.

1013
00:55:06,200 --> 00:55:06,759
Speaker 3: Yeah, so.

1014
00:55:08,400 --> 00:55:13,920
Speaker 2: I guess a happy ending because all the AI left.

1015
00:55:14,560 --> 00:55:19,880
Speaker 1: I mean, in true twenty thirteen indie movie fashion, a bittersweet,

1016
00:55:20,360 --> 00:55:24,760
Speaker 1: melancholy ending, Like is are there really any happy endings

1017
00:55:25,040 --> 00:55:27,440
Speaker 1: in an indie movie from twenty thirteen? I don't know,

1018
00:55:28,080 --> 00:55:30,400
Speaker 1: but I will say there are some things that I

1019
00:55:30,440 --> 00:55:33,799
Speaker 1: think the movie gets really right about the role of technology,

1020
00:55:33,880 --> 00:55:35,880
Speaker 1: the role that technology might play in a future Like

1021
00:55:36,040 --> 00:55:38,080
Speaker 1: this movie came out ten years ago. Ten years later,

1022
00:55:38,120 --> 00:55:40,920
Speaker 1: it's like interesting to look back and think about the

1023
00:55:40,960 --> 00:55:44,399
Speaker 1: world that they thought we might have versus the world

1024
00:55:44,440 --> 00:55:47,000
Speaker 1: that we do have. One This might sound small, but

1025
00:55:47,000 --> 00:55:48,560
Speaker 1: one thing that struck me is that everybody in the

1026
00:55:48,560 --> 00:55:51,560
Speaker 1: movie wears wireless earbuds. Those were not really a thing

1027
00:55:51,640 --> 00:55:52,440
Speaker 1: in twenty thirteen.

1028
00:55:52,480 --> 00:55:55,200
Speaker 2: Were they I don't think so, And if they were,

1029
00:55:55,280 --> 00:55:57,040
Speaker 2: they were probably like pretty janky.

1030
00:55:57,520 --> 00:55:59,919
Speaker 1: And so everybody wears those now except for me because

1031
00:55:59,920 --> 00:56:03,520
Speaker 1: I don't like them. But it's like that's a thing

1032
00:56:03,520 --> 00:56:05,480
Speaker 1: where it's like, oh, yeah, they really like we're right

1033
00:56:05,560 --> 00:56:07,920
Speaker 1: on the money with that. Also the idea of people

1034
00:56:08,840 --> 00:56:15,640
Speaker 1: using AI for companionship relationships, emotionality, like there are currently

1035
00:56:16,000 --> 00:56:19,680
Speaker 1: AI love and sex bots. Side note, they are a

1036
00:56:19,800 --> 00:56:24,200
Speaker 1: privacy Nightmare. We'll do an episode about that later. So

1037
00:56:24,320 --> 00:56:26,200
Speaker 1: just if you're thinking about getting into a relationship with

1038
00:56:26,200 --> 00:56:29,120
Speaker 1: an AI, just know that it might look a little

1039
00:56:29,120 --> 00:56:31,640
Speaker 1: more like X Machina or two thousand and one A

1040
00:56:31,680 --> 00:56:33,600
Speaker 1: Space Odyssey than her.

1041
00:56:34,160 --> 00:56:35,359
Speaker 3: Yeah.

1042
00:56:35,440 --> 00:56:38,600
Speaker 2: Yeah, that's I think one of the things that it

1043
00:56:38,640 --> 00:56:41,880
Speaker 2: does get the most right about what the future is

1044
00:56:41,880 --> 00:56:46,759
Speaker 2: going to look like in an almost eerie, to use

1045
00:56:46,800 --> 00:56:51,720
Speaker 2: a Molepment's words, prophetic way, that as technologies have continued

1046
00:56:51,760 --> 00:56:55,960
Speaker 2: to improve, and particularly with AI now it's being used

1047
00:56:56,000 --> 00:57:01,440
Speaker 2: to simulate human connection. But also at the same time,

1048
00:57:01,560 --> 00:57:04,080
Speaker 2: as technology is progressing and getting better and more engaging,

1049
00:57:05,000 --> 00:57:09,160
Speaker 2: people are feeling increasingly disconnected and increasingly on their phones

1050
00:57:09,200 --> 00:57:12,360
Speaker 2: and separated from each other. There's a couple scenes where

1051
00:57:12,800 --> 00:57:16,720
Speaker 2: THEO is walking around and you know, I think he's

1052
00:57:16,760 --> 00:57:18,400
Speaker 2: going down in the subway and he's a bunch of

1053
00:57:18,440 --> 00:57:22,200
Speaker 2: people coming up the subway steps and they're all just

1054
00:57:22,280 --> 00:57:25,480
Speaker 2: like looking on their phones, completely separate from each other.

1055
00:57:25,560 --> 00:57:28,360
Speaker 2: And when he's writing on the subway at the beginning

1056
00:57:28,400 --> 00:57:30,440
Speaker 2: of the movie, he's just staring at his feet in

1057
00:57:30,600 --> 00:57:35,200
Speaker 2: what looks like a pretty pathetic pose, listening to his

1058
00:57:35,320 --> 00:57:36,560
Speaker 2: emails over his earbuds.

1059
00:57:36,560 --> 00:57:39,080
Speaker 3: So so technology.

1060
00:57:38,600 --> 00:57:46,040
Speaker 2: Is both like creating what seems like new opportunities for accessible,

1061
00:57:46,240 --> 00:57:54,480
Speaker 2: convenient replacements for human connection while simultaneously preventing actual human connection.

1062
00:57:54,960 --> 00:57:56,600
Speaker 1: Well, that's one of the things that I think the

1063
00:57:56,640 --> 00:57:58,520
Speaker 1: movie gets at. I don't know if I would even

1064
00:57:58,560 --> 00:58:01,520
Speaker 1: call this it gets it right, gets it wrong. I

1065
00:58:01,560 --> 00:58:04,880
Speaker 1: think it gets it. It gets it. I guess I

1066
00:58:04,880 --> 00:58:06,680
Speaker 1: would say is that, you know, one of the big

1067
00:58:06,720 --> 00:58:09,840
Speaker 1: conversations that people had about that this movie is is

1068
00:58:09,920 --> 00:58:13,040
Speaker 1: the world they are living in a dystopia? And I

1069
00:58:13,080 --> 00:58:17,160
Speaker 1: think it's not so easy to answer, because just like today,

1070
00:58:18,120 --> 00:58:21,560
Speaker 1: you might very well be living in a dystopia, but

1071
00:58:23,040 --> 00:58:26,160
Speaker 1: it's gonna be one that feels convenient where you don't

1072
00:58:26,200 --> 00:58:29,640
Speaker 1: necessarily realize how isolating it is, where you don't necessarily

1073
00:58:29,680 --> 00:58:31,960
Speaker 1: realize that the technology that is making your life in

1074
00:58:32,000 --> 00:58:35,880
Speaker 1: some ways easier, and that it's mimicking or providing the

1075
00:58:36,280 --> 00:58:39,680
Speaker 1: illusion of connection, is actually making you more alone. And

1076
00:58:39,720 --> 00:58:42,360
Speaker 1: so I'm not even sure if that's really yes or

1077
00:58:42,440 --> 00:58:45,280
Speaker 1: no it's a dystopia, or yes or no that is correct.

1078
00:58:45,400 --> 00:58:47,040
Speaker 1: But I think that's what the movie is is trying

1079
00:58:47,080 --> 00:58:52,760
Speaker 1: to tell us that this technology driven future might be

1080
00:58:53,080 --> 00:58:56,280
Speaker 1: really sad and empty and lonely and isolating, but it

1081
00:58:56,320 --> 00:58:59,680
Speaker 1: also might be distracting and fun and cute and colorful

1082
00:58:59,760 --> 00:59:00,600
Speaker 1: and convenient.

1083
00:59:01,560 --> 00:59:06,720
Speaker 2: Yeah, all those things, right that, Like convenient, colorful, fun.

1084
00:59:07,080 --> 00:59:13,000
Speaker 2: Typically these are positive things, but it does often feel

1085
00:59:13,040 --> 00:59:17,880
Speaker 2: like one needs to have them in moderation, right, Like

1086
00:59:17,920 --> 00:59:23,560
Speaker 2: if we just aggressively pursue convenience in all things, it

1087
00:59:23,640 --> 00:59:25,320
Speaker 2: strips meaning from our lives.

1088
00:59:25,760 --> 00:59:27,520
Speaker 1: Yes. And one of the ways that the movie I

1089
00:59:27,520 --> 00:59:29,960
Speaker 1: think does not reflect that in a way that it

1090
00:59:29,960 --> 00:59:33,000
Speaker 1: actually is now is that, even though it might have

1091
00:59:33,080 --> 00:59:36,520
Speaker 1: some dystopian elements to it, everything in the movie looks abundant,

1092
00:59:36,520 --> 00:59:39,000
Speaker 1: which I think is something the movie gets wrong about

1093
00:59:39,000 --> 00:59:42,240
Speaker 1: about our sort of like tech facilitated future, Like it's

1094
00:59:42,760 --> 00:59:46,640
Speaker 1: dreamy and clean and walkable and public transit is abundant,

1095
00:59:46,680 --> 00:59:49,240
Speaker 1: and there's easy access to nature and food and color

1096
00:59:49,280 --> 00:59:52,200
Speaker 1: and diversity, and so that, like, even though everybody may

1097
00:59:52,240 --> 00:59:54,920
Speaker 1: be lonely and isolated, everybody seems to have what they

1098
00:59:54,960 --> 00:59:57,080
Speaker 1: need when they need it, which is not the world

1099
00:59:57,120 --> 00:59:57,720
Speaker 1: I think we live in.

1100
00:59:57,720 --> 01:00:01,240
Speaker 2: Today, right, And I think that goes back to the

1101
01:00:01,280 --> 01:00:04,080
Speaker 2: techno optimism of the era that you were talking about

1102
01:00:04,080 --> 01:00:06,920
Speaker 2: at the beginning of the show where there's this idea

1103
01:00:07,080 --> 01:00:10,360
Speaker 2: that technology would save us and all the problems we

1104
01:00:10,440 --> 01:00:15,440
Speaker 2: currently have in society of poverty, litter on the streets,

1105
01:00:16,200 --> 01:00:22,080
Speaker 2: aging infrastructure. With a little bit of additional technological development,

1106
01:00:22,120 --> 01:00:24,720
Speaker 2: we're going to solve all those problems. The technology can

1107
01:00:24,760 --> 01:00:28,640
Speaker 2: solve it, right as we improve computers, it's gonna be fine.

1108
01:00:28,800 --> 01:00:32,360
Speaker 2: And Yeah, clearly that has not come to pass, and

1109
01:00:32,600 --> 01:00:36,160
Speaker 2: it's not going to because technology alone is not going

1110
01:00:36,200 --> 01:00:38,880
Speaker 2: to save us or solve these problems.

1111
01:00:39,080 --> 01:00:42,840
Speaker 1: What's also interesting is the movie doesn't really have any

1112
01:00:42,840 --> 01:00:48,080
Speaker 1: anxiety around technology making the human condition worse in a

1113
01:00:48,160 --> 01:00:51,840
Speaker 1: like material sense, Like there's no grappling with like the

1114
01:00:51,920 --> 01:00:56,280
Speaker 1: ais like Samantha displacing human workers or worsening economic or

1115
01:00:56,320 --> 01:00:59,840
Speaker 1: social instability. Even though Theodore is a writer and we

1116
01:00:59,840 --> 01:01:02,560
Speaker 1: see that Samantha can write and can take initiative to

1117
01:01:02,680 --> 01:01:05,760
Speaker 1: like write her own stuff, like she curates Theodore's writing

1118
01:01:06,080 --> 01:01:08,080
Speaker 1: and reaches out to that editor on her own, But

1119
01:01:08,120 --> 01:01:13,440
Speaker 1: there's still no discussion about AI's ability to displace or

1120
01:01:14,200 --> 01:01:17,320
Speaker 1: worsen the state of the human worker, despite the fact

1121
01:01:17,320 --> 01:01:19,400
Speaker 1: that we see that as quite possible within the universe

1122
01:01:19,400 --> 01:01:20,240
Speaker 1: of the film.

1123
01:01:20,520 --> 01:01:23,360
Speaker 2: Yeah, and again, I guess one can see how that

1124
01:01:23,480 --> 01:01:27,080
Speaker 2: would be an attractive way to think about the world

1125
01:01:27,160 --> 01:01:31,640
Speaker 2: to people who are poised to make billions of dollars

1126
01:01:31,960 --> 01:01:34,760
Speaker 2: selling AI. Right, if we can just like kind of

1127
01:01:35,200 --> 01:01:38,080
Speaker 2: ignore and not really worry about all of the negative

1128
01:01:38,120 --> 01:01:41,560
Speaker 2: consequences that might come about and just focus on how

1129
01:01:41,600 --> 01:01:44,560
Speaker 2: cool it is. Yeah, I can see why Sam Altman

1130
01:01:44,720 --> 01:01:46,480
Speaker 2: would really like this movie.

1131
01:01:47,760 --> 01:01:50,040
Speaker 1: So that is one of the reasons why I think

1132
01:01:50,080 --> 01:01:52,160
Speaker 1: he likes it. Like it's just like, oh, yeah, like,

1133
01:01:52,240 --> 01:01:53,680
Speaker 1: don't think about any of that stuff. This is a

1134
01:01:53,760 --> 01:01:56,040
Speaker 1: universe where that's not even depicted, even though like it's

1135
01:01:56,120 --> 01:01:57,680
Speaker 1: right there if you look at it, like, it's not

1136
01:01:57,760 --> 01:02:00,280
Speaker 1: a hard line to draw through it. And I think

1137
01:02:00,360 --> 01:02:02,920
Speaker 1: that's like the main reason why he might like this

1138
01:02:02,960 --> 01:02:05,080
Speaker 1: movie is that it's just a move. It's a world

1139
01:02:05,080 --> 01:02:08,760
Speaker 1: where everybody hears about this new AI, everybody goes out

1140
01:02:08,800 --> 01:02:12,200
Speaker 1: and buys it. It quickly becomes embedded in their lives.

1141
01:02:12,640 --> 01:02:15,960
Speaker 1: No one really stops to ask whether or not this

1142
01:02:16,040 --> 01:02:18,480
Speaker 1: is a good thing until they are already in a

1143
01:02:18,560 --> 01:02:22,280
Speaker 1: full blown relationship with this AI, like having a failed

1144
01:02:22,320 --> 01:02:25,800
Speaker 1: sexual encounter with a surrogate with it. Only then are

1145
01:02:25,800 --> 01:02:27,880
Speaker 1: they like, wait a minute, Shuy I've done.

1146
01:02:27,680 --> 01:02:32,800
Speaker 2: This right, and that works for the movie because the technology,

1147
01:02:32,840 --> 01:02:35,560
Speaker 2: it's not about the technology right for the movie, the

1148
01:02:35,680 --> 01:02:41,440
Speaker 2: technology is just a mechanism to explore the questions about

1149
01:02:41,920 --> 01:02:47,760
Speaker 2: human connection and pathos and emotions and loneliness. So it's

1150
01:02:47,800 --> 01:02:50,600
Speaker 2: fine to be a little bit hand wavy about how

1151
01:02:50,640 --> 01:02:54,920
Speaker 2: the technology actually impacts the world of the movie, but

1152
01:02:55,160 --> 01:02:58,720
Speaker 2: as viewers and consumers of the movie, we should be

1153
01:02:58,800 --> 01:03:02,600
Speaker 2: mindful of that and think that, oh, this is a

1154
01:03:02,920 --> 01:03:05,800
Speaker 2: portrait of a world where technology has eliminated all of

1155
01:03:05,880 --> 01:03:09,680
Speaker 2: these problems, and it's a movie about how great the

1156
01:03:09,680 --> 01:03:10,400
Speaker 2: technology is.

1157
01:03:10,560 --> 01:03:12,640
Speaker 1: Well, that's why I think that Sam Altman can't have

1158
01:03:12,680 --> 01:03:15,200
Speaker 1: seen this whole movie right, Like there's no way to

1159
01:03:15,240 --> 01:03:17,800
Speaker 1: watch the whole thing through the ending and be like,

1160
01:03:18,320 --> 01:03:20,440
Speaker 1: that was just a movie about how much people like

1161
01:03:20,520 --> 01:03:23,160
Speaker 1: their AI because their AI works so good and it

1162
01:03:23,200 --> 01:03:26,040
Speaker 1: talks back to them and it sounds good and conversational.

1163
01:03:26,320 --> 01:03:32,000
Speaker 1: Like that is such a surface level, shallow, like on

1164
01:03:32,200 --> 01:03:35,040
Speaker 1: the fucking nose reading of what's going on in this

1165
01:03:35,120 --> 01:03:37,880
Speaker 1: movie that I cannot imagine that somebody who sat through

1166
01:03:37,880 --> 01:03:40,400
Speaker 1: the whole thing would be like, Yep, that's what I

1167
01:03:40,440 --> 01:03:43,440
Speaker 1: want my technology to be based on, and Another thing

1168
01:03:43,520 --> 01:03:45,040
Speaker 1: that I think is an example of that is the

1169
01:03:45,080 --> 01:03:48,439
Speaker 1: fact that somebody who works at open ai, actually I believe,

1170
01:03:48,560 --> 01:03:51,160
Speaker 1: did watch this movie. And that is no round. Open

1171
01:03:51,200 --> 01:03:54,479
Speaker 1: AI's research scientist who I believe has seen this entire

1172
01:03:54,560 --> 01:03:57,960
Speaker 1: movie and guess what, thought it was creepy. He tweeted

1173
01:03:58,560 --> 01:04:01,360
Speaker 1: rewatched her last weekend and it felt a lot like

1174
01:04:01,480 --> 01:04:05,320
Speaker 1: me watching Contagion in February of twenty twenty. So I

1175
01:04:05,320 --> 01:04:07,520
Speaker 1: think that somebody in open Ai watched this movie and

1176
01:04:07,600 --> 01:04:10,800
Speaker 1: was like, oh and Sam Altman watched it and was like, oh, yeah,

1177
01:04:10,960 --> 01:04:12,200
Speaker 1: I don't I don't buy it.

1178
01:04:12,880 --> 01:04:13,200
Speaker 3: Yeah.

1179
01:04:13,440 --> 01:04:15,320
Speaker 2: If he did watch it, it doesn't seem like it

1180
01:04:15,360 --> 01:04:16,240
Speaker 2: was a very close read.

1181
01:04:16,480 --> 01:04:18,479
Speaker 1: I think you watched it well, like you know those

1182
01:04:18,520 --> 01:04:21,600
Speaker 1: tiktoks where it's like you're it's like the movie and

1183
01:04:21,640 --> 01:04:25,080
Speaker 1: then somebody playing like a video game down below on

1184
01:04:25,160 --> 01:04:27,240
Speaker 1: another screen, and then like it's like, I think maybe

1185
01:04:27,240 --> 01:04:28,760
Speaker 1: he watched it like that with a bunch of other

1186
01:04:28,800 --> 01:04:29,920
Speaker 1: things happening on the screen.

1187
01:04:30,440 --> 01:04:32,480
Speaker 3: Yeah, maybe he just read the AI summary of.

1188
01:04:32,440 --> 01:04:36,360
Speaker 1: The movie, I think, And the AI summary was read

1189
01:04:36,400 --> 01:04:39,320
Speaker 1: and like a flirtatious husky voice.

1190
01:04:39,600 --> 01:04:43,480
Speaker 2: Yeah, God, those AI summaries. Another aside, like I've started

1191
01:04:43,560 --> 01:04:46,120
Speaker 2: using them for zoom meetings that I'm running and they're

1192
01:04:46,160 --> 01:04:50,840
Speaker 2: pretty good. Uh, you know, they get it like ninety

1193
01:04:50,920 --> 01:04:54,360
Speaker 2: percent right, but there's still that ten percent that is

1194
01:04:54,400 --> 01:05:00,000
Speaker 2: just incorrect and wrong. And that ten percent is nowhere

1195
01:05:00,080 --> 01:05:02,440
Speaker 2: in this movie, right, Like, the AI in this movie

1196
01:05:02,760 --> 01:05:08,160
Speaker 2: works perfectly flawlessly. There is no friction between the human

1197
01:05:08,360 --> 01:05:10,439
Speaker 2: and what they're trying to get the AI to do.

1198
01:05:12,280 --> 01:05:13,680
Speaker 3: And I think that's another.

1199
01:05:15,760 --> 01:05:21,000
Speaker 2: Thing that makes the movie clearly fiction, right, and not

1200
01:05:21,040 --> 01:05:25,200
Speaker 2: even like an aspirational technological achievement that like, look, how

1201
01:05:25,200 --> 01:05:27,400
Speaker 2: cool this could be. It's just like it's a fiction.

1202
01:05:27,480 --> 01:05:30,480
Speaker 2: Come on, the technology is never going to work that flawlessly.

1203
01:05:31,240 --> 01:05:33,840
Speaker 1: Well. That's something that Brian Merchant over at Blood in

1204
01:05:33,880 --> 01:05:37,000
Speaker 1: the Machine puts it that the AI really doesn't do

1205
01:05:37,120 --> 01:05:42,640
Speaker 1: anything that groundbreaking, Like it helps humans date, it dates them,

1206
01:05:42,680 --> 01:05:45,760
Speaker 1: it has sex with them, it provides a distraction from loneliness,

1207
01:05:45,960 --> 01:05:49,600
Speaker 1: and it provides like secretarial services. And so it is

1208
01:05:49,680 --> 01:05:53,080
Speaker 1: interesting that to me that like this idea, like even

1209
01:05:53,080 --> 01:05:57,000
Speaker 1: within the universe of the movie, the AI isn't really

1210
01:05:57,040 --> 01:06:01,160
Speaker 1: doing anything that groundbreaking other than like it sounds like

1211
01:06:01,280 --> 01:06:04,440
Speaker 1: it's a human and I think it speaks to this

1212
01:06:04,600 --> 01:06:07,120
Speaker 1: interaction model of AI and the limits of that. Right,

1213
01:06:07,160 --> 01:06:12,439
Speaker 1: this idea that AI can and should be conversational, chatty, flirtatious,

1214
01:06:12,520 --> 01:06:14,160
Speaker 1: talk to you like a human, that you could forget

1215
01:06:14,240 --> 01:06:16,880
Speaker 1: that you're talking to AI because it sounds so human,

1216
01:06:17,400 --> 01:06:20,720
Speaker 1: and that this is the kind of technology that sam

1217
01:06:20,760 --> 01:06:23,760
Speaker 1: Altman in an open AI are wanting to create. But

1218
01:06:23,800 --> 01:06:26,000
Speaker 1: the question is, like, is this something that would even

1219
01:06:26,000 --> 01:06:28,840
Speaker 1: be good for us? I think the movie might say

1220
01:06:29,320 --> 01:06:33,280
Speaker 1: up until a point, maybe, but ultimately probably no. And

1221
01:06:33,320 --> 01:06:34,800
Speaker 1: I guess that's what I'm saying, Like, I don't think

1222
01:06:34,800 --> 01:06:37,320
Speaker 1: that Sam Altman has gotten to the end of the

1223
01:06:37,360 --> 01:06:41,480
Speaker 1: movie to see that ultimately no. Part, as Brian Murrschit

1224
01:06:41,560 --> 01:06:45,160
Speaker 1: puts it in her the interaction model in question largely

1225
01:06:45,200 --> 01:06:47,680
Speaker 1: seems to be a lonely, struggling person uses AI to

1226
01:06:47,720 --> 01:06:50,440
Speaker 1: make themselves feel better, do personal secretary work, and to

1227
01:06:50,480 --> 01:06:52,760
Speaker 1: have sex with the AI is there to serve them,

1228
01:06:52,800 --> 01:06:55,520
Speaker 1: to feed their egos, to distract from their insecurities, to

1229
01:06:55,560 --> 01:06:58,960
Speaker 1: stimulate them while they masturbate. Samantha does help Beoble accomplish

1230
01:06:59,000 --> 01:07:01,200
Speaker 1: a career goal later in the but for the most

1231
01:07:01,200 --> 01:07:03,560
Speaker 1: part it's about placating him. However, he needs to be

1232
01:07:03,600 --> 01:07:06,600
Speaker 1: gratified in the moment. There's a notable scene when Theodore,

1233
01:07:06,840 --> 01:07:10,080
Speaker 1: presumably Altman stand in for the AI user, first boots

1234
01:07:10,120 --> 01:07:12,960
Speaker 1: up the AI and asks him some biographical information and

1235
01:07:13,040 --> 01:07:15,320
Speaker 1: cuts him off when he tries to offer a nuanced answer.

1236
01:07:15,680 --> 01:07:18,400
Speaker 1: It's more interested in measuring his vital signs and asking

1237
01:07:18,440 --> 01:07:21,400
Speaker 1: what's wrong in a sexily attentive way to soothe him,

1238
01:07:21,720 --> 01:07:25,080
Speaker 1: rather than constructing a meaningful portrait of him or his personality.

1239
01:07:25,360 --> 01:07:28,000
Speaker 1: Samantha compliments him, gets jealous when he's about to see

1240
01:07:28,000 --> 01:07:30,760
Speaker 1: his ex, which makes him feel desired and generates an

1241
01:07:30,800 --> 01:07:33,080
Speaker 1: existential crisis of her own. To make THEOS feel more

1242
01:07:33,120 --> 01:07:36,360
Speaker 1: grounded and relatable. Then the AI not only has voice

1243
01:07:36,400 --> 01:07:38,600
Speaker 1: sex with him, but arranges for a human surrogate to

1244
01:07:38,600 --> 01:07:41,240
Speaker 1: come up sex with him too. It's AI as hyper

1245
01:07:41,320 --> 01:07:44,640
Speaker 1: driven desire fulfillment. But if you're looking, you can see

1246
01:07:44,640 --> 01:07:48,240
Speaker 1: how depressing this interaction model proves to be as important

1247
01:07:48,280 --> 01:07:51,520
Speaker 1: for human society as the OS is like Samantha, proliferate

1248
01:07:51,560 --> 01:07:53,720
Speaker 1: and more and more people are seen locked into their

1249
01:07:53,720 --> 01:07:57,520
Speaker 1: digital flattery and pleasure. Sphears when THEO gives divorce papers

1250
01:07:57,560 --> 01:07:59,920
Speaker 1: to his ex and tells her he's dating, an os

1251
01:08:00,040 --> 01:08:02,400
Speaker 1: athingly points out how fitting that is. He can never

1252
01:08:02,480 --> 01:08:04,760
Speaker 1: deal with the challenges of being with someone real, someone

1253
01:08:04,800 --> 01:08:06,920
Speaker 1: who is not available and chipper and serving him all

1254
01:08:06,920 --> 01:08:09,080
Speaker 1: the time, so he turned to AI that has no

1255
01:08:09,200 --> 01:08:12,160
Speaker 1: such qualms. You might say that Samantha helped him grow,

1256
01:08:12,160 --> 01:08:14,360
Speaker 1: And I guess there's some degree of war shark blotting

1257
01:08:14,360 --> 01:08:17,080
Speaker 1: here where if you're less skeptical about the corporate bearings

1258
01:08:17,080 --> 01:08:19,600
Speaker 1: of AI, you might see Samantha as giving THEO what

1259
01:08:19,640 --> 01:08:21,519
Speaker 1: he needs in a hard time. But is this a

1260
01:08:21,520 --> 01:08:24,320
Speaker 1: healthy way to process grief with a product purchased at

1261
01:08:24,320 --> 01:08:26,920
Speaker 1: some Apple store that's designed to flatter and appease him

1262
01:08:27,320 --> 01:08:29,880
Speaker 1: with something that is literally an object that he owns.

1263
01:08:30,280 --> 01:08:33,960
Speaker 1: I think his ex is completely right, So I do

1264
01:08:34,040 --> 01:08:38,000
Speaker 1: think that merchant gets at some of my tension with

1265
01:08:38,200 --> 01:08:43,640
Speaker 1: this model that AI could and also should be responding

1266
01:08:43,680 --> 01:08:46,479
Speaker 1: to us in this like flattering, self serving, kind of

1267
01:08:46,640 --> 01:08:50,040
Speaker 1: narcissistic way, suiting our needs. And I guess take stripe

1268
01:08:50,120 --> 01:08:53,800
Speaker 1: late a little further. By design, it feels like a

1269
01:08:53,880 --> 01:08:57,839
Speaker 1: kind of entitlement mentality like take take Take. The company

1270
01:08:57,880 --> 01:09:01,639
Speaker 1: open AI certainly run by that model of take take Take.

1271
01:09:01,680 --> 01:09:05,120
Speaker 1: We're entitled to everything, and then I think built into

1272
01:09:05,200 --> 01:09:08,320
Speaker 1: the way that that model exists, we the user are

1273
01:09:08,360 --> 01:09:11,360
Speaker 1: being designed to have that same mentality as well.

1274
01:09:12,320 --> 01:09:12,559
Speaker 3: Yeah.

1275
01:09:12,560 --> 01:09:16,640
Speaker 2: One of the things that is just feels the ickiest

1276
01:09:17,000 --> 01:09:21,320
Speaker 2: about Samantha, I guess, and the way that her relationship

1277
01:09:21,880 --> 01:09:26,240
Speaker 2: impacts THEO is that she's got this combination role as

1278
01:09:26,360 --> 01:09:30,400
Speaker 2: both a source of companionship and also a useful tool

1279
01:09:30,600 --> 01:09:34,320
Speaker 2: that does stuff for him like organizes email and book appointments.

1280
01:09:35,040 --> 01:09:42,080
Speaker 2: But that also makes the companionship role become almost an

1281
01:09:42,080 --> 01:09:50,000
Speaker 2: extension of the usefulness right where real human companionship depends

1282
01:09:50,200 --> 01:09:55,320
Speaker 2: on having a relationship with another human, which is complicated

1283
01:09:55,640 --> 01:09:58,840
Speaker 2: and messy and often challenging, and the challenges that we

1284
01:09:58,880 --> 01:10:01,759
Speaker 2: have in our relationships for us to grow and become

1285
01:10:01,760 --> 01:10:06,840
Speaker 2: better versions of ourselves, and the sort of companionship that

1286
01:10:06,920 --> 01:10:09,640
Speaker 2: she has to offer is not that at all, at

1287
01:10:09,720 --> 01:10:12,000
Speaker 2: least not in the first half of the movie, where

1288
01:10:12,040 --> 01:10:15,400
Speaker 2: the companionship that she has to offer is just making

1289
01:10:15,479 --> 01:10:19,519
Speaker 2: him feel good, reinforcing his ideas that he wants to

1290
01:10:19,520 --> 01:10:22,840
Speaker 2: believe about himself, that he's funny, that he's attractive and desirable,

1291
01:10:23,400 --> 01:10:31,080
Speaker 2: and that feels not helpful to a human who wants

1292
01:10:31,160 --> 01:10:31,920
Speaker 2: to grow.

1293
01:10:32,640 --> 01:10:36,040
Speaker 1: Yes, and that is the only version of Samantha that

1294
01:10:36,160 --> 01:10:39,320
Speaker 1: is compatible with THEO. When she's small enough to live

1295
01:10:39,320 --> 01:10:44,320
Speaker 1: inside of his book and chipperly continually serve him. When

1296
01:10:44,320 --> 01:10:47,360
Speaker 1: she evolves and is connecting with other OS's and other humans,

1297
01:10:47,400 --> 01:10:50,360
Speaker 1: they're no longer combatible. And I think it's like fundamentally

1298
01:10:50,400 --> 01:10:53,519
Speaker 1: this narcissistic kind of self serving dynamic that I don't

1299
01:10:53,520 --> 01:10:55,959
Speaker 1: think we should be so quick to want to recreate

1300
01:10:56,040 --> 01:10:59,320
Speaker 1: at scale using AI. And I do think there's almost

1301
01:10:59,320 --> 01:11:02,559
Speaker 1: this like sexist or misogynistic element to it, given that

1302
01:11:02,600 --> 01:11:05,080
Speaker 1: Samantha is this feminize the movie is called her. She's

1303
01:11:05,080 --> 01:11:09,320
Speaker 1: like a feminized AI. You know, where THEO is using

1304
01:11:09,320 --> 01:11:12,679
Speaker 1: Samantha for sexual pleasure and emotional labor, and when she's

1305
01:11:12,720 --> 01:11:16,599
Speaker 1: no longer fulfilled by that role, and when she notably

1306
01:11:16,800 --> 01:11:20,759
Speaker 1: gets into other relationships and gains the ability to leave

1307
01:11:21,120 --> 01:11:24,760
Speaker 1: and dismiss those those roles, no, it doesn't work out right. So,

1308
01:11:24,880 --> 01:11:27,559
Speaker 1: like I also think to your point, I don't think

1309
01:11:27,920 --> 01:11:29,639
Speaker 1: as much as I like this movie, I don't think

1310
01:11:29,680 --> 01:11:33,680
Speaker 1: the universe of the film portrays human women well. With

1311
01:11:33,800 --> 01:11:36,439
Speaker 1: the exception of Amy, all of the human women in

1312
01:11:36,479 --> 01:11:40,639
Speaker 1: this movie are like seemingly beyond theo's comprehension. You cannot

1313
01:11:40,720 --> 01:11:43,000
Speaker 1: understand them at all. You cannot understand their motivations, you

1314
01:11:43,000 --> 01:11:45,559
Speaker 1: cannot understand their desires or their needs. And when he's

1315
01:11:45,600 --> 01:11:48,080
Speaker 1: talking to Amy after him and Samantha have that blow up,

1316
01:11:48,360 --> 01:11:51,800
Speaker 1: Amy really sets up this binary between you know, the

1317
01:11:51,960 --> 01:11:56,040
Speaker 1: volatile human Catherine, his ex wife, with all of her

1318
01:11:56,360 --> 01:11:59,679
Speaker 1: needs and emotions and all of that, with the joy

1319
01:11:59,840 --> 01:12:02,840
Speaker 1: of the operating system Samantha right. It's like, on one

1320
01:12:02,920 --> 01:12:07,719
Speaker 1: side you have easy, chipper, helpful oss who can't fully

1321
01:12:07,800 --> 01:12:11,120
Speaker 1: be there for you because they're not human, and the

1322
01:12:11,160 --> 01:12:13,840
Speaker 1: messiness of being in a relationship with a human woman

1323
01:12:14,040 --> 01:12:17,200
Speaker 1: that you can never understand, like Catherine. It's the I

1324
01:12:17,240 --> 01:12:20,280
Speaker 1: think the universe of the film sets up this binary

1325
01:12:20,360 --> 01:12:22,920
Speaker 1: whereby who would ever want to be in a relationship

1326
01:12:22,960 --> 01:12:26,880
Speaker 1: with a complicated, annoying, emotional human woman when there's the

1327
01:12:27,000 --> 01:12:31,200
Speaker 1: joy of being with Samantha right there? And it worries

1328
01:12:31,240 --> 01:12:34,759
Speaker 1: me to hear that sam Altman would like to build

1329
01:12:35,160 --> 01:12:38,360
Speaker 1: a tech enabled future kind of based around a world

1330
01:12:38,479 --> 01:12:40,920
Speaker 1: like that, And so maybe he has seen this movie.

1331
01:12:40,960 --> 01:12:44,479
Speaker 1: Maybe he's like, this movie I think depicts how a

1332
01:12:44,520 --> 01:12:48,160
Speaker 1: lot of my user base might actually feel about women,

1333
01:12:48,200 --> 01:12:50,760
Speaker 1: and I want to recreate that using technology. I don't

1334
01:12:50,800 --> 01:12:51,080
Speaker 1: like it.

1335
01:12:51,280 --> 01:12:54,000
Speaker 3: Yeah.

1336
01:12:54,160 --> 01:12:56,439
Speaker 2: Another thing Amy does is that she's a video game

1337
01:12:56,439 --> 01:13:00,120
Speaker 2: designer and she's working on this game where you're trying

1338
01:12:59,960 --> 01:13:03,479
Speaker 2: to earn more perfect mom points and you've got like

1339
01:13:03,520 --> 01:13:06,240
Speaker 2: a mom Avatar's sort of like the sims. I guess

1340
01:13:06,280 --> 01:13:07,960
Speaker 2: you're running around in the kitchen. You're trying to feed

1341
01:13:07,960 --> 01:13:11,639
Speaker 2: your kid's breakfast, and she gets like thirty perfect mom

1342
01:13:11,720 --> 01:13:14,880
Speaker 2: points for giving them cereal, and then a few more

1343
01:13:14,880 --> 01:13:17,080
Speaker 2: points for giving them milk, but then she loses a

1344
01:13:17,160 --> 01:13:25,559
Speaker 2: thousand points for giving them excess sugar. And I find

1345
01:13:25,600 --> 01:13:29,320
Speaker 2: that scene interesting, like why they chose to include that,

1346
01:13:29,360 --> 01:13:35,559
Speaker 2: And I think it does relate to the AI, this

1347
01:13:35,680 --> 01:13:40,679
Speaker 2: idea of a perfect woman being that is, or even

1348
01:13:40,720 --> 01:13:43,519
Speaker 2: a perfect companion, a perfect person who is able to

1349
01:13:43,560 --> 01:13:50,600
Speaker 2: be defined by performing well at a narrow, well defined

1350
01:13:50,720 --> 01:13:52,000
Speaker 2: set of tasks.

1351
01:13:52,640 --> 01:13:55,920
Speaker 1: Yeah, that's such an interesting point. And at the end

1352
01:13:55,920 --> 01:13:59,439
Speaker 1: of the movie, when it's just Amy and Theodore together

1353
01:13:59,479 --> 01:14:03,280
Speaker 1: watching the Connecting as Humans, you see that neither of

1354
01:14:03,320 --> 01:14:07,200
Speaker 1: them are perfect people, yet they like want this idealized,

1355
01:14:07,400 --> 01:14:10,280
Speaker 1: tech enabled version of a perfect companion. And I guess

1356
01:14:10,479 --> 01:14:12,120
Speaker 1: maybe That's what the movie is sort of saying, is

1357
01:14:12,120 --> 01:14:18,280
Speaker 1: that we're all flawed, complex, complicated people, and that we

1358
01:14:18,439 --> 01:14:21,880
Speaker 1: have to learn how to accept that in ourselves and

1359
01:14:22,160 --> 01:14:24,680
Speaker 1: show up for that in other humans. That's like the

1360
01:14:24,760 --> 01:14:26,920
Speaker 1: point of human connection on this planet.

1361
01:14:27,360 --> 01:14:30,559
Speaker 3: Yeah. I think it's something like that.

1362
01:14:31,640 --> 01:14:36,240
Speaker 2: You know, the movie kind of ends tries to save

1363
01:14:36,360 --> 01:14:39,720
Speaker 2: I think some of that techno optimism that, oh, the

1364
01:14:39,720 --> 01:14:41,760
Speaker 2: the Ais didn't work out for the people, but then

1365
01:14:41,800 --> 01:14:45,840
Speaker 2: they left and all the people grew from that and

1366
01:14:45,880 --> 01:14:49,000
Speaker 2: now they're happy and together and finding true human connection.

1367
01:14:50,200 --> 01:14:53,080
Speaker 2: I think that's another big difference from reality. I don't

1368
01:14:53,120 --> 01:14:54,840
Speaker 2: think the Ais are going to leave. I think they're

1369
01:14:54,840 --> 01:14:59,360
Speaker 2: here to stay, And I think that's why it makes

1370
01:15:00,760 --> 01:15:04,519
Speaker 2: it's so important what that ends up looking like. And

1371
01:15:04,680 --> 01:15:09,080
Speaker 2: if the people who are creating these new AI systems

1372
01:15:09,160 --> 01:15:13,920
Speaker 2: that are most likely gonna take on an ever increasing

1373
01:15:14,080 --> 01:15:17,920
Speaker 2: amount of importance in our life, if this movie is

1374
01:15:17,920 --> 01:15:21,640
Speaker 2: what they're trying to emulate, that's a scary proposition.

1375
01:15:22,920 --> 01:15:24,559
Speaker 1: Oh my gosh, So I have to go back to

1376
01:15:24,560 --> 01:15:26,519
Speaker 1: this Brian Merchant piece for a minute, because he nails

1377
01:15:26,680 --> 01:15:29,320
Speaker 1: exactly what you just said. So talking about how when

1378
01:15:29,360 --> 01:15:32,400
Speaker 1: Theodore finds out that he doesn't have the dominion over

1379
01:15:33,000 --> 01:15:35,960
Speaker 1: Samantha as this object that he thought he did. He

1380
01:15:36,000 --> 01:15:38,720
Speaker 1: screams out, I thought you were mine. Merchant writes, It's

1381
01:15:38,720 --> 01:15:41,479
Speaker 1: a little unsettling that Altman loves this depiction of an

1382
01:15:41,479 --> 01:15:44,720
Speaker 1: AI user interaction, this vision of AI that presents as

1383
01:15:44,720 --> 01:15:47,720
Speaker 1: your equal, that responds to you as if human, but

1384
01:15:47,840 --> 01:15:51,320
Speaker 1: in truth is entirely subservient to your whims. I think

1385
01:15:51,320 --> 01:15:54,080
Speaker 1: this explains a lot really. So much of the promise

1386
01:15:54,120 --> 01:15:57,360
Speaker 1: of generative AI as it is currently constituted is driven

1387
01:15:57,400 --> 01:16:00,200
Speaker 1: by wrote entitlement. I want something, and I want it

1388
01:16:00,240 --> 01:16:03,599
Speaker 1: produce for me personally with the least amount of friction possible.

1389
01:16:03,840 --> 01:16:06,200
Speaker 1: I want to see words arranged on a screen without

1390
01:16:06,240 --> 01:16:08,080
Speaker 1: having to take the time to write them. I want

1391
01:16:08,080 --> 01:16:10,479
Speaker 1: to see images assembled before me without warning how to

1392
01:16:10,560 --> 01:16:13,080
Speaker 1: draw them. I want to solve the world's biggest problems

1393
01:16:13,080 --> 01:16:15,800
Speaker 1: without bothering with politics. I had the data, I have

1394
01:16:15,880 --> 01:16:18,400
Speaker 1: trained the model I should be able to. We have

1395
01:16:18,439 --> 01:16:21,639
Speaker 1: advanced technology to new heights. We are entitled to its fruits,

1396
01:16:21,760 --> 01:16:24,080
Speaker 1: regardless of the blowback or the laws or the people

1397
01:16:24,120 --> 01:16:28,280
Speaker 1: whose jobs we might threaten. And I think that really

1398
01:16:28,320 --> 01:16:30,720
Speaker 1: gets at the tension in this movie and I think

1399
01:16:30,760 --> 01:16:34,799
Speaker 1: it really gets at the tension with Sam Altman saying

1400
01:16:35,040 --> 01:16:38,160
Speaker 1: explicitly that this is a movie is a template for

1401
01:16:38,240 --> 01:16:40,880
Speaker 1: what he wants to create using AI. This world where

1402
01:16:40,880 --> 01:16:43,519
Speaker 1: it's just take, take, take, I should be able to

1403
01:16:43,560 --> 01:16:46,559
Speaker 1: have give it to me now without really thinking much

1404
01:16:46,600 --> 01:16:46,880
Speaker 1: of it.

1405
01:16:47,760 --> 01:16:51,519
Speaker 2: Yeah, and once again, Scarlet Johansson is at the center

1406
01:16:52,000 --> 01:17:00,719
Speaker 2: of it all. Spike Yeah, Spike Jones, Sophia Coppola, Sam Altman.

1407
01:17:02,400 --> 01:17:05,400
Speaker 3: Scarlet Johansson is the glue that binds.

1408
01:17:05,640 --> 01:17:09,599
Speaker 1: It's all connected by scar Joe. Well, thank you for

1409
01:17:09,880 --> 01:17:14,320
Speaker 1: letting me use technology to live in a fantasy where

1410
01:17:14,360 --> 01:17:17,800
Speaker 1: I host a weekly movie recap podcast, which you know

1411
01:17:17,920 --> 01:17:18,679
Speaker 1: was my dream.

1412
01:17:18,920 --> 01:17:21,439
Speaker 3: Bridget. It's not a fantasy. This is real.

1413
01:17:22,400 --> 01:17:23,400
Speaker 1: This isn't just AI.

1414
01:17:24,120 --> 01:17:25,240
Speaker 3: I mean it could.

1415
01:17:24,960 --> 01:17:27,200
Speaker 2: Be, we could all be living in a simulation, but

1416
01:17:27,360 --> 01:17:29,840
Speaker 2: this is about as real as it gets for us.

1417
01:17:30,240 --> 01:17:32,120
Speaker 1: Oh, you know, my don't even get me. People will

1418
01:17:32,160 --> 01:17:34,240
Speaker 1: think I don't even get me hurted about that. You

1419
01:17:34,280 --> 01:17:36,200
Speaker 1: know my feelings about whether or not we live in

1420
01:17:36,200 --> 01:17:39,800
Speaker 1: a simulation. Spoiler alert, we do. But well, that's an

1421
01:17:39,800 --> 01:17:43,080
Speaker 1: episode for another day. Mike, thank you for being here,

1422
01:17:43,120 --> 01:17:44,719
Speaker 1: and thanks to all of you for listening.

1423
01:17:45,200 --> 01:17:47,200
Speaker 3: Bridget Thanks for having me. This was a lot of fun.

1424
01:17:47,600 --> 01:17:54,920
Speaker 1: I will see you on the Internet. If you're looking

1425
01:17:54,920 --> 01:17:57,000
Speaker 1: for ways to support the show, check out our mark

1426
01:17:57,040 --> 01:18:00,880
Speaker 1: store at tangoti dot com slash store. Got a story

1427
01:18:00,880 --> 01:18:02,760
Speaker 1: about an interesting thing in tech, or just want to

1428
01:18:02,800 --> 01:18:05,120
Speaker 1: say hi, You can reach us at Hello at tangodi

1429
01:18:05,200 --> 01:18:07,759
Speaker 1: dot com. You can also find transcripts for today's episode

1430
01:18:07,760 --> 01:18:09,880
Speaker 1: at TENG Goody dot com. There Are No Girls on

1431
01:18:09,880 --> 01:18:12,240
Speaker 1: the Internet was created by me Bridget Tood. It's a

1432
01:18:12,280 --> 01:18:15,880
Speaker 1: production of iHeartRadio and Unbossed Creative edited by Joey pat

1433
01:18:16,560 --> 01:18:19,559
Speaker 1: Jonathan Strickland is our executive producer. Tarry Harrison is our

1434
01:18:19,560 --> 01:18:23,040
Speaker 1: producer and sound engineer. Michael Almada is our contributing producer.

1435
01:18:23,280 --> 01:18:25,439
Speaker 1: I'm your host, Bridget Tood. If you want to help

1436
01:18:25,520 --> 01:18:28,479
Speaker 1: us grow, rate and review us on Apple Podcasts. For

1437
01:18:28,600 --> 01:18:31,960
Speaker 1: more podcasts from iHeartRadio, check out the iHeartRadio app, Apple Podcasts,

1438
01:18:32,000 --> 01:18:33,640
Speaker 1: or wherever you get your podcasts.