Speaker 1: Hello the Internet, and welcome to season three, twenty two,
Speaker 1: episode two of Dirt Daily's Guys. It's a production of iHeartRadio.
Speaker 1: It's a podcast where we take a deep dive into
Speaker 1: America's shared consciousness. And it is Tuesday, January twenty third,
Speaker 1: twenty twenty four.
Speaker 2: Yeah you know what that two three two one two
Speaker 2: three two three, Well guess what? It's National National Handwriting Day,
Speaker 2: shout out to everybody who's still nice with the pen
Speaker 2: and pencil or quill, and also National Pie Day. But yeah, handwriting.
Speaker 2: I realize they're not teaching cursive anymore out here in
Speaker 2: the US.
Speaker 1: So I yeah, I haven't written cursive since like sixth
Speaker 1: seventh grade. I think, do you have a pen and paper?
Speaker 1: Handwriting Day is discriminatory against me as a left handed person.
Speaker 2: Wait do you do you have a pen and paper
Speaker 2: in front of you right now?
Speaker 1: No?
Speaker 2: Oh, I was gonna say, would you write your name
Speaker 2: right now? In cursive?
Speaker 1: I mean that one I can probably do right right
Speaker 1: my signature, but like, yeah, pizzeria pizzeria would be a
Speaker 1: real Billy Madison style problem. Yeah yeah, those z's are
Speaker 1: you fucking kicking?
Speaker 3: Yeah?
Speaker 1: Those are those? Don't don't look like any letter I
Speaker 1: ever seen anyways. By the way, I was just being
Speaker 1: a type of person I hate. Who's like really calling
Speaker 1: you out for calling it twenty twenty three?
Speaker 2: Oh shit, did I say?
Speaker 1: It's like, oh yeah, yeah, you said one, two three,
Speaker 1: two three, And that's fine for I think we have
Speaker 1: a grace period until June. Personally, after the pandemic, it's
Speaker 1: it's it's weird time has time has gone in a
Speaker 1: weird direction. And I think it's fine if somebody writes
Speaker 1: the year like as twenty twenty two, that's a fun
Speaker 1: thing to like laugh with them about. Yeah, but twenty
Speaker 1: twenty three. Give them a fucking break. Yeah, Like you're
Speaker 1: being like the person at the sleepover who's like, you
Speaker 1: mean this morning because it just hit midnight? Yeah, and
Speaker 1: twelve correcting people.
Speaker 2: You mean yesterday. Yeah. I feel like with that, I'm
Speaker 2: finally experiencing that form of time dilation our parents experience
Speaker 2: when they say the other day and it could mean
Speaker 2: three weeks to thirteen years ago. Oh yeah, yeah, yeah,
Speaker 2: so yeah, yeah, the other day, it's twenty twenty three.
Speaker 1: With movies that like came out I think recently, and
Speaker 1: it turns out it's over a decade ago. That really
Speaker 1: fucks me up, and it happens to me all the time. Anyways.
Speaker 1: My name is Jack O'Brien aka the rich don't give
Speaker 1: a fuck about us, The rich don't give a fuck
Speaker 1: about us. The rich don't give a fuck about us.
Speaker 1: Eat them on the halfshell, Lambeau power. That is courtesy
Speaker 1: of Malacaroni on the Discord, who I was just fucking
Speaker 1: around when I said, you can't write songs about me
Speaker 1: because of my pants anymore? Man, You can. You can
Speaker 1: totally write songs about it. That's that's fine. I'm the
Speaker 1: one who's choosing to sing men.
Speaker 2: Yeah, yeah, but through clenched teeth wiping away tears every Yeah.
Speaker 1: But it's a it's something that my therapist has said
Speaker 1: I need to work through musically, So you're doing the work.
Speaker 1: I'm thrilled to be joined as always by my co
Speaker 1: host mister Miles Great.
Speaker 2: Miles Gray aka how about a deal to make you fail? Okay,
Speaker 2: we know you failed, depressed shut how about a quick
Speaker 2: holiday shout out to Andrew bubb on the Discord because
Speaker 2: we were talking about Blue Monday, the most depressed day
Speaker 2: ever in history. But we don't really get that so
Speaker 2: much in the US, and just how it's really just
Speaker 2: a scheme to sell people vacations or McDonald's.
Speaker 1: Oh I missed that one. Well, which day is blue Monday?
Speaker 1: Is it today?
Speaker 2: It was last Monday? It was, yes, yes, exactly.
Speaker 1: Oh, but they gave us a day off so that
Speaker 1: we wouldn't like be so said.
Speaker 2: Well, just like a thing that was started in the
Speaker 2: UK with sky Travel, where they were basically had a
Speaker 2: guy be like I have out like mathematically calculated the
Speaker 2: most depressed day as like a function of time that
Speaker 2: is a lapsed since Christmas, sadness and motivation, and it
Speaker 2: was all just bullshit and you know, yeah, but hey,
Speaker 2: that's a great way to sell I respect it.
Speaker 1: It's Touch Todays, Yeah, Miles, Yeah, we are thrilled to
Speaker 1: be joined in our third seat, yes by an expert guest,
Speaker 1: a returning champion guests on our most popular episode of
Speaker 1: twenty twenty three.
Speaker 2: Oh.
Speaker 1: She's a research associate at the Leverholmes Center for the
Speaker 1: Future of Intelligence. I don't think I pronounced that word
Speaker 1: right few, where she researches AI from the perspective of
Speaker 1: gender studies, critical race theory, and Asian Diasporas Studies, also
Speaker 1: a research fellow at the AI Now Institute, the co
Speaker 1: editor of the new book The Good Robot, Why Technology
Speaker 1: Needs Feminism, and a co host of The Good Robot podcast.
Speaker 1: Please welcome back to the show, the Brilliant doctor Kerrie mcinnarn.
Speaker 4: Oh, thanks for having me back.
Speaker 2: Oh hey, thank you so much for accepting our invitation.
Speaker 2: So good to have you back.
Speaker 1: And what time is it where you are right now?
Speaker 3: It is about ten to eight pm and I am
Speaker 3: an early bird, so this is near my bedtime. But
Speaker 3: that just shows how keen I am to get to
Speaker 3: come back on and talk to you. But that I know,
Speaker 3: usually after sort of nine pm. Well my friends know,
Speaker 3: they like there's just going to be no response, no
Speaker 3: trying to plan anything.
Speaker 4: Yeah, it's a special occasion.
Speaker 1: Yeah, you're such an impressive guest that we actually opened
Speaker 1: our call with you by asking you, like why you
Speaker 1: came back. We were like, so, like you're you're like
Speaker 1: like us or something like you're cool, You're so we're
Speaker 1: like idiots, Right, why are you back? And yeah, we're
Speaker 1: thrilled to have you, regardless of the questionable decision by
Speaker 1: you to come hang out with us. This late in
Speaker 1: the evening.
Speaker 2: I'm learned. Yes, yeah, because so much has happened. I
Speaker 2: feel like everything, there's always something happening with A and
Speaker 2: we're like, once we hit we got to ask doctor
Speaker 2: carry like what about this? What about this? And then
Speaker 2: now we've got the perfect opportunity to ask you a
Speaker 2: bunch of questions and also let you rain your knowledge
Speaker 2: down upon us and the listeners, because yeah, last time
Speaker 2: was really really good talking to you and gave us
Speaker 2: so much perspective because we were definitely like we like
Speaker 2: AI end of world right, Like it's like so powerful.
Speaker 2: Oh no, no, just okay, okay, just these language models
Speaker 2: are doing a lot of the lifting right now.
Speaker 1: We've seen T two. We get it. It's wild how
Speaker 1: much that movie has a whole Like it's still raised
Speaker 1: in so many articles. Like yeah, journalists are like as
Speaker 1: in the movie Terminator too, like they're still they're like,
Speaker 1: that's the one I remember. So that's what we're going
Speaker 1: with for this model of understanding. But we're gonna so
Speaker 1: we're gonna get into all sorts of AI questions. Your
Speaker 1: new book talks about the question of is there good
Speaker 1: technology is that possible? Which is a real question for
Speaker 1: me at this point, because I've been been so long
Speaker 1: at sea in this hyper capitalist paradigm. So I'm curious,
Speaker 1: very interested to hear your answer to that, unless it's
Speaker 1: just like, nah, it's not possible. Yeah, super short book.
Speaker 1: But before we get into all of that, we do
Speaker 1: like to ask our guest, what is something from your
Speaker 1: search history that's revealing about who you are?
Speaker 3: Oh gosh, I don't really know if I like what
Speaker 3: this reveals about me, But you know, we need to
Speaker 3: get like really obsessed with something. And it's not even recent,
Speaker 3: it's not trending, like there's no reason why, but for
Speaker 3: all my search history for the last two days just
Speaker 3: really wild deep dives on the twenty nineteen film Cats,
Speaker 3: you know, the awful one, the Cgifer and you know,
Speaker 3: all the superstars kind of crawling around it all fours
Speaker 3: And I don't know why, but for some reason, like
Speaker 3: a specter just came back to want me, and I
Speaker 3: was like, today, I need to like listen to an
Speaker 3: hour and a half YouTube video on the making of
Speaker 3: the movie twenty nineteen and why it was a disaster.
Speaker 3: And so I'm not busy enough. I think it's I
Speaker 3: need more hobbies. And I need more productive uses of
Speaker 3: my time.
Speaker 4: But I am now an encyclopedia on terrible CGI slash
Speaker 4: why you shouldn't try and make very weird Broadway musicals
Speaker 4: into films.
Speaker 1: Yeah, I was immediately like trying to connect the dots.
Speaker 1: I was like, oh, well, I think I remember that
Speaker 1: they used AI technology to remove the cat assholes from
Speaker 1: like was that one of the things where it was
Speaker 1: about to come out and they did a test screening
Speaker 1: and everyone's like, they're pink cat assholes are in our
Speaker 1: face the entire movie? Or are we going to just
Speaker 1: do that? And they went back and digitally removed them.
Speaker 1: But now, were you into the movie when it came out?
Speaker 1: Were you anticipating it or you just kind of have it?
Speaker 3: So I love I'm a dancer, so like I love musicals,
Speaker 3: and like you know, I was one of the only
Speaker 3: people that was like an ironically ex that thought.
Speaker 4: Of the Cat's musicals.
Speaker 3: I realized that's like four people who like actually would
Speaker 3: have wanted to see this.
Speaker 4: And then the trailer came out and it was just
Speaker 4: so frightening.
Speaker 3: What it was a really good example of is like
Speaker 3: in like AI and robotics, either term the uncanny Valley.
Speaker 3: This might be something you've heard of, this idea of
Speaker 3: like the closest something looks like to a human or
Speaker 3: to like a living creature, but like being different enough
Speaker 3: that you can tell, like it's not quite human, like
Speaker 3: the creepy era it is. And so this original robotics
Speaker 3: experiment Matito Mari or the person who like writes this
Speaker 3: essay about this, used the example of like a mechanical
Speaker 3: hand that moves, and it's like, that's super creepy, like
Speaker 3: no one wants to see that. And all I could
Speaker 3: think of is this like essay from this Jepanese roboticist.
Speaker 3: When I saw those cat humans things moving, and I
Speaker 3: was like, it's going to be so bad, like no
Speaker 3: one wants to see this, whether or not the pink
Speaker 3: households are there or not, you know, and they just
Speaker 3: end up being all smooth doubt, which is also awful.
Speaker 4: So yes, it was a kind of terrifying disappointment.
Speaker 2: Because yeah, there's kind of a streisand effect. I feel
Speaker 2: like people are like, but where are the assholes? You
Speaker 2: know what I mean? And then people are like, well
Speaker 2: we actually like h I don't know, might have been
Speaker 2: better with them, have you speaking of cats and an interesting,
Speaker 2: uh sort of obsession with them. Have you listened to
Speaker 2: your fellow compatriots podcast Guy Montgomery and Tim Batt's podcast
Speaker 2: called My Week with Cats where they keep watching Cats
Speaker 2: over and over and talking about it.
Speaker 4: But it sounds exactly up my street.
Speaker 2: Yeah, yeah, yeah, yeah, we've had them on the show.
Speaker 2: Guy is one of our favorite guests and fellow Kiwi
Speaker 2: and yeah, like to such an absurd podcast just keep
Speaker 2: revisiting cats over and over.
Speaker 3: Yeah, I mean, have you listened to the iconic KIWI
Speaker 3: podcast who Shout on the Floor at my wedding with
Speaker 3: kind of viral? I still haven't listened to it yet,
Speaker 3: but that's also on my listening list.
Speaker 2: Yeah, that's one that I've heard many times, be like
Speaker 2: have you come on? And all the write ups about
Speaker 2: it too are like it's absolutely the most riveting thing
Speaker 2: that we've listened to this year, is what I feel
Speaker 2: like most people say about that.
Speaker 1: That's amazing. So are you how many viewings deep are
Speaker 1: you of twenty nineteen Cats or is it just like
Speaker 1: you watched it once and then it's all YouTube like explainers?
Speaker 3: Oh yeah, I watched it once. I don't know if
Speaker 3: I could do it again, to be honest, like I
Speaker 3: did it once on like a transatlantic flight and that
Speaker 3: was you know, myself trapped in the metal tube. Had
Speaker 3: this moment with cats when I was like, oh, it
Speaker 3: is as bad as everyone said, And then now it's
Speaker 3: just extremely scathing movie reviews on YouTube and in print.
Speaker 3: So I'm like single handedly keeping the movie YouTube review
Speaker 3: economy alive at this point.
Speaker 1: What is something you think is overrated?
Speaker 4: Hmmm?
Speaker 3: I mean I feel like pretty much anything TikTok tries
Speaker 3: to sell me, but particularly those like gigantic cups.
Speaker 4: Those Stanley cups. I don't know if you've seen this, yeah,
Speaker 4: but they've gone so viral.
Speaker 3: But they're like huge, and my dad used to take
Speaker 3: like a thermoust tumbler of that size out fishing for
Speaker 3: the day so that he would like have enough like
Speaker 3: tea or coffee to keep him going. But now I
Speaker 3: just see like normal people and then normal little walks
Speaker 3: like with a huge flask, and like, I don't get it.
Speaker 3: So if anyone can like sell me, like why why
Speaker 3: what is so attractive about these gigantic cups.
Speaker 4: Around them?
Speaker 1: I mean, that's what's important.
Speaker 2: Doctor.
Speaker 1: Yeah, I've ever heard of it.
Speaker 3: The medical doctors don't come to me on the plane
Speaker 3: anything useful.
Speaker 2: It's not the same screen. All right. I'm sorry I
Speaker 2: sent you so many medical questions earlier this week over email.
Speaker 2: Didn't realize that wasn't your area of expertise. I mean,
Speaker 2: it's like one of those weird It's just one of
Speaker 2: those consumer things that have taken over. It's like the
Speaker 2: era of like when I was a kid, like millennials
Speaker 2: and stuff, when everybody wanted like a slat bracelet or
Speaker 2: a Tamagatchi or a furbie like that or beanie babies.
Speaker 2: Like we're taking that into adulthood. And now it's like,
Speaker 2: do you have all this Stanley fucking quenchers? Yeah, which
Speaker 2: is like a wild thing. But then also it's wild
Speaker 2: when it's done for the SEO, because when you search
Speaker 2: Stanley Cup, which is the like trophy for the National
Speaker 2: Hockey League, it's mostly overtaken by these fucking Stanley insulated bugs.
Speaker 1: Yeah, I mean, it is wild though. Those are fifty
Speaker 1: dollars each of those things.
Speaker 2: Yeah, yeah, they're like at least forty five, right, Yeah,
Speaker 2: get you in the door.
Speaker 1: People are lining up the day before like to get
Speaker 1: an opportunity to pay forty five dollars for this thing that,
Speaker 1: as far as I could tell, is like has been
Speaker 1: available on the market for a long time, like the
Speaker 1: you know, just well insulated cups.
Speaker 2: That thermist like that you're talking about, Doctor Carrey. That's
Speaker 2: like the like O. G. Stanley like item that people
Speaker 2: have that was like sort of like that minty green
Speaker 2: very like every work in person, every work in stiff
Speaker 2: sort of insulated thermist kind of thing.
Speaker 1: We need a stan Lee stay on the show to
Speaker 1: just explain it to us, Like what is the what? What?
Speaker 1: What is so much better about the Stanley mug from
Speaker 1: like all the other insulated water carrying devices out there.
Speaker 2: Yeah, all right, look zeit gang. If you're a Stanley,
Speaker 2: stan hit us up. We were interested hearing from you.
Speaker 2: And also I feel like there's a high likelihood that
Speaker 2: you are also involved in some other like completionist collecting
Speaker 2: hobby in childhood. I'm just guessing, you know, like before
Speaker 2: I was like I had all the fucking Pokemon cars,
Speaker 2: or like I had all the Beanie babies, Like it
Speaker 2: just has that same energy of being like gotta get
Speaker 2: them all, gotta have them. If you're on that wave
Speaker 2: because I know some people just like them, but some
Speaker 2: people have like way too many.
Speaker 1: Yeah, I'm like over here laughing at my wife for
Speaker 1: like be her most value valued object right now is
Speaker 1: a Stanley tumbler. She got it like a week and
Speaker 1: a half ago. She like wrote her name and was like,
Speaker 1: I will reward if if found because like she's really
Speaker 1: into it. And I was like wow, like what is
Speaker 1: why are you so obsessed? Just like I got in
Speaker 1: like right before, like I got it before everything sold out,
Speaker 1: Like I really like this color way. And when she
Speaker 1: was like talking about the color, like the colorway of it,
Speaker 1: I was like, Oh, it's exactly how I am with shoes,
Speaker 1: Like I have absolutely no room to look down.
Speaker 2: We all have things.
Speaker 1: Yeah, shoes are more expensive. So yeah, Jordan's which were
Speaker 1: a thing that I was into when I was a kid.
Speaker 1: What is doctor McNerney? What is something you think is underrated?
Speaker 4: Oh?
Speaker 3: Well, I just finished watching with my husband season four
Speaker 3: of a show that I think is so underrated.
Speaker 4: It's called for All Mankind. It's on Apple. Have you
Speaker 4: seen it?
Speaker 2: I've heard of it, but I have not seen it.
Speaker 4: Yeah, okay, well now I can pitch it.
Speaker 3: I don't work for Apple for this show, just to
Speaker 3: be clear, although I should get commissioned now because I've
Speaker 3: pitched it so hard.
Speaker 4: But it's like an alternative history of the space rate.
Speaker 3: So the idea is like what happened if Russia got
Speaker 3: to the Moon first, and so space express and became
Speaker 3: this like major site of like investment and travel, And like,
Speaker 3: I'm like not one of those people who's super into space,
Speaker 3: Like I'm not someone who sneaks out a lot of
Speaker 3: space related sci fi.
Speaker 4: But this was riveting.
Speaker 3: It's so well acted, and every season it's a different decade,
Speaker 3: so it like starts in the nineteen sixties and the seventies, eighties,
Speaker 3: nineties and two thousands kind of mapping this alternate history
Speaker 3: of the world. And they've got lots of little like
Speaker 3: kind of like eat eggs, little plot twists and things
Speaker 3: like that. So in this like alternate history, for example,
Speaker 3: this is like not a big spoiler, say, like the
Speaker 3: John Lennon is shot, but he doesn't die, so he's
Speaker 3: kind of still alive and like featuring a little plot
Speaker 3: point or like I think Margaret Thatcher gets assassinated by
Speaker 3: the IRA, or like it's like a lot of these
Speaker 3: like little turning points in history, they go differently, So
Speaker 3: I would recommend checking that out is a really great watch.
Speaker 1: Okay, And this all happens because Russia gets to the moon.
Speaker 1: For like, as far as I can tell, the race
Speaker 1: to the Moon, the America got up there and there
Speaker 1: was like, ah, man, there ain't shit here. Turns out
Speaker 1: out there's a lot of dust. We discovered nothing. Is it?
Speaker 1: Just like the bragging rights kind of turns everything on
Speaker 1: its head.
Speaker 3: Yeah, I think that they kind of portray that, like,
Speaker 3: not only I mean a lot of it is the
Speaker 3: bragging rights and the international politics of like, oh, we've
Speaker 3: got to be competing to show that we're more like
Speaker 3: technologically advanced, but also it shows like, yeah, how the
Speaker 3: technological advances that came from continuing to invest in space
Speaker 3: as well as the discoveries they make out they're part
Speaker 3: a slightly different course in human history, from like new
Speaker 3: energy sources through to yeah, like new technologies for flight
Speaker 3: or for you know, cultivating life in different places. So
Speaker 3: it's just quite an interesting, like speculative future.
Speaker 1: Yeah, I see, I love a speculative future.
Speaker 2: I've I had Apple TV plus plus TV or whatever,
Speaker 2: and then I've I let the thing lapse, so then
Speaker 2: I'm like my I turn it on my like TV
Speaker 2: and they're like, oh, you don't got this anymore. But
Speaker 2: then I realized you basically get it for free if
Speaker 2: you buy like any Apple product anymore. And I recently
Speaker 2: like replaced my phone, so i'd be like, oh, yeah,
Speaker 2: I'll cash in my whatever three month period of freeness.
Speaker 2: I get to maybe check this one out because I
Speaker 2: just wasn't watching a lot of stuff on Apple TV.
Speaker 2: But it's also because we talk about this all the time.
Speaker 2: There's just too many things to watch now. So I need, like,
Speaker 2: if people like you, who's opinion I respect, to come
Speaker 2: on and be like you gotta check this out. And
Speaker 2: I'm like, see that. I need something like that rather
Speaker 2: than seeing some Twitter account being.
Speaker 1: Like this is the fucking dope as shit.
Speaker 2: Ever, I need more human recommendations.
Speaker 1: Yeah, human recommendation. Yeah. All right, Well we're going to
Speaker 1: talk about how AI stacks up to humans when we
Speaker 1: get back.
Speaker 2: We'll be right back.
Speaker 1: It's not really what we're going to talk about, but
Speaker 1: I wanted it to sound like I was good at
Speaker 1: my job, so I did like a transition.
Speaker 2: That that sounded like yeah, that sounded like a show
Speaker 2: that I would listen to and we're back, We're back,
Speaker 2: and all right. So I had something happened over the weekend.
Speaker 1: I just wanted to remember medic I just want you
Speaker 1: to look at this thing on my back.
Speaker 2: Yeah.
Speaker 1: I know you're not a medical doctor, but it's just
Speaker 1: I could just use your no. Uh. So I had
Speaker 1: one of my son's friend. My son is really too chess,
Speaker 1: and his friend was playing chess on his iPad and
Speaker 1: he my son asked who he was playing. He said,
Speaker 1: I'm playing AI instead of just like playing the computer.
Speaker 1: It was the first time I'd heard somebody refer to
Speaker 1: it as AI instead of playing the computer. And as
Speaker 1: you know, we knew you're coming on. I was like
Speaker 1: looking at all the headlines and it felt like a
Speaker 1: lot of the stories that are are coming up are
Speaker 1: basically on the same continuum of progress of like things
Speaker 1: that the tech industry has been advancing towards for a
Speaker 1: long time. And I'm I'm like starting to wonder if
Speaker 1: because because I think a lot of people have a
Speaker 1: hard time conceptualizing, like, so what exactly is AI though,
Speaker 1: And I think there's a lot of people like capitalizing
Speaker 1: off of that, because now it's like it's no longer
Speaker 1: just algorithms are making it hard to tell what is
Speaker 1: true and what isn't in on social media. Now it's
Speaker 1: like AI is gonna fuck up this election. Everybody. You know.
Speaker 1: Miles was talking about how like CS was, you know,
Speaker 1: full of all these products that are like, yeah, but
Speaker 1: there's Ai in the rapid rehydration sports drink.
Speaker 2: Everything said was posted in this weird way to be like, yeah,
Speaker 2: this thing and now it's got Ai in it, and
Speaker 2: you're like AI in it? What do you mean we're
Speaker 2: talking about. A coffee maker is like yeah, dude, he's
Speaker 2: got Ai in there, and everyone's like bathlessly being like
Speaker 2: oh my god, this new fucking thing has Ai in it.
Speaker 2: But again it just sounds like algorithms. But also people
Speaker 2: are also I think also confusing like large, large language
Speaker 2: models for being like, oh, so the computer is gonna
Speaker 2: think like a person, and then are my coffee machine's
Speaker 2: gonna think like a human and problem solve like a
Speaker 2: barista versus like so I just stick a little brain
Speaker 2: in there, right, So I guess like the glibway of
Speaker 2: summarizing it would be that, like, you know, there were
Speaker 2: these large language models that impress people quite a bit,
Speaker 2: and they've used that to change the word for like
Speaker 2: all tech advances to be just like AI for like
Speaker 2: branding purposes. Kind of.
Speaker 1: I don't think that's true about all of it. And
Speaker 1: there's definitely some things that seem to be advancing more
Speaker 1: quickly than I'm comfortable with, and that I think people
Speaker 1: are comfortable with. But like, I guess just I'm curious
Speaker 1: to hear like your thoughts on that. As you're seeing
Speaker 1: so many stories and products and all these things, and
Speaker 1: children playing chess misusing the phrase AI, what are your thoughts.
Speaker 3: I mean, my first thought when you were saying that
Speaker 3: about the sports drink, I was like, maybe the Stanley Cup.
Speaker 4: Has AI in it.
Speaker 3: That's why the virus plugging in the technical markets stargning
Speaker 3: its quest for world domination. Yeah, I mean, I think
Speaker 3: this is one of those cases where two things can
Speaker 3: be true at once, Like it can be true that
Speaker 3: we've seen masive developments in large language models and generator
Speaker 3: of AI and other kinds of like you know, sort
Speaker 3: of big data projects, and at the same time, lots
Speaker 3: of firms are jumping on the AI train and marketing
Speaker 3: a lot of things is AI that you know, even
Speaker 3: if you somehow degree a decide on one definition of
Speaker 3: what AI is, we would probably say that these things
Speaker 3: definitely aren't AI enabled in any way. And actually I
Speaker 3: spent like a couple of years interviewing scientists and engineers
Speaker 3: at this big tech firm, and one of the things
Speaker 3: that they were super concerned about was this exact problem.
Speaker 4: So saying, you know, oh well.
Speaker 3: Ten or fifteen years ago, we would have just called
Speaker 3: this a decision tree. Now we're calling it a That
Speaker 3: doesn't mean there's something wrong with that technology, but it
Speaker 3: does mean that maybe the way AI is being used
Speaker 3: is more to do with branding, more to do with
Speaker 3: selling it as a product, and less to do with
Speaker 3: its actual technical functions or what the tools can actually do.
Speaker 3: So like a lot of my job as an AI
Speaker 3: ethicis is just like asking customers and people to just
Speaker 3: be a little bit more critical and ask those questions
Speaker 3: around can this tool actually do what it says on
Speaker 3: the ten What does it mean for something to BAI
Speaker 3: or AI powered?
Speaker 4: And it's it going to actually help you get where
Speaker 4: you want to be?
Speaker 3: Because you know, it actually doesn't matter if it has
Speaker 3: an AI function if like that AI function is not
Speaker 3: going to help you achieve your goal.
Speaker 4: So, like an example of.
Speaker 3: This is like a lot of tools, say AI powered
Speaker 3: hiring tools is an example, I know best, Like they'll say, okay,
Speaker 3: we have an AI function, right, so we use AI
Speaker 3: to help analyze say, like the words that the candidate
Speaker 3: uses in the interviews. But like a lot of these
Speaker 3: tools have like a toggle on off function, so you
Speaker 3: can just like turn the AI part off, which is
Speaker 3: what a lot of companies will do. They'll buy in
Speaker 3: an AI powered tool, but then because that opens them
Speaker 3: up to a lot of liabilities if they actually use
Speaker 3: AI to process candidates, they'll just turn that bit off, so.
Speaker 4: They kind of you know, try to have things both ways.
Speaker 3: I think where you're getting a tool that seems really
Speaker 3: high tech, but you're like not actually using that function.
Speaker 3: So yeah, I think this kind of idea of AI
Speaker 3: as branding is also something that we should all really
Speaker 3: be a bit concerned about.
Speaker 2: Yeah. Yeah, well, and also just seems like there's this
Speaker 2: weird thing too where companies are like, yeah, we use
Speaker 2: AI and other times don't fucking tell them we're using AI,
Speaker 2: Like you know what I mean, It's like what the
Speaker 2: fuck is it? Because recently there's this video game Apex
Speaker 2: Legends that there was like some art artwork that came
Speaker 2: out for like a new thing evolving Final Fantasy, and
Speaker 2: people were like, wait, I think this is like generative
Speaker 2: AI was used for some of these like models because
Speaker 2: like the fingers don't look right, et cetera. And it
Speaker 2: was like a whole thing where it's like embarrassed to
Speaker 2: admit or shouldn't have used AI. So there's there's like
Speaker 2: this interesting balancing act where people like, don't use it there, Yes,
Speaker 2: I'm glad my insulated mug has AI in it, and
Speaker 2: but we're but like we're still kind of finding like
Speaker 2: what is useful, what is acceptable, what is embarrassing or whatever.
Speaker 2: So yeah, it just feels like so many things are
Speaker 2: still up in the air in regards to its use.
Speaker 1: Yeah.
Speaker 4: Yeah, And I think you're right.
Speaker 3: There's this interesting dynamic where like, on the one hand,
Speaker 3: I saw a lot of critiques on TikTok, which is
Speaker 3: again how I spend most of my time sort of
Speaker 3: mindlessly scrolling past mugs and other various bits and pieces.
Speaker 3: But there were a lot of critiques of that new
Speaker 3: Disney film, right, wish, which is kind of blending two
Speaker 3: D animation three D animation. And one of the critiques
Speaker 3: people kept saying was like the song sounds like it's
Speaker 3: AI generated, or the art looks AI generated. It was
Speaker 3: being used differently in this like quite derogatory way, Whereas
Speaker 3: you're right, like a lot of AI startups sell themselves
Speaker 3: in the idea that like wear an AI first company.
Speaker 3: I think there was a study that was done with it,
Speaker 3: like a few years ago, with like European based AI
Speaker 3: startups which showed i think, you know, like something like
Speaker 3: up to forty percent of those AI startups like didn't
Speaker 3: that use AI.
Speaker 4: They were just marketing themselves as AI startups.
Speaker 3: So there's a lot of kind of you know, like
Speaker 3: you know, weird sort of misleading advertising going on. But
Speaker 3: then it can also lead to some like really strange
Speaker 3: other phenomena like the Wizard of Odds phenomenon, which is
Speaker 3: when you actually have companies having humans pretending to be AI,
Speaker 3: not the other way around, so that they look more
Speaker 3: tiped forward. So you think you're talking to an AI
Speaker 3: chatpot and you're not. You're actually talking to a human
Speaker 3: pretending to be an AI. So it's kind of just
Speaker 3: viraled down.
Speaker 1: So also, isn't one of Amazon's big companies called the
Speaker 1: Mechanical Turk, Like based on the there was like an
Speaker 1: early instance where a robot was like really good at
Speaker 1: playing chess and woe like beating all these people at chests,
Speaker 1: and it turned out they just put a chess master
Speaker 1: inside a like robot suit and that's who was beating everybody.
Speaker 1: Like it feels like they're knowingly doing that. They're you know, yeah,
Speaker 1: they're they're trying to make it seem like they are
Speaker 1: using advanced technology when they're not. I think it like that.
Speaker 1: One of the big questions that I've had all along
Speaker 1: is like in reading articles interviewing like Sam Altman or
Speaker 1: these people who are at the forefront in these massive
Speaker 1: positions of power in the tech industry and specifically around AI,
Speaker 1: like they really seem to be willing to sell the
Speaker 1: threat and like evoke like terminator to type imagery when
Speaker 1: they're talking about like, you know, I think the last
Speaker 1: time You're on we talked about how Sam Altman, the
Speaker 1: head of Open Eie what like in a New Yorker
Speaker 1: interview is like, yeah, keep like keep a cyanide capsule
Speaker 1: on me, you know, just in case the robots take
Speaker 1: over and I gotta I gotta go because I don't
Speaker 1: want to see what that looks like.
Speaker 2: Yeah, I don't want my Stanley Cup to revolt against me.
Speaker 1: And it's like, well, he of and of all people
Speaker 1: knows that that's like not a threat right now, like
Speaker 1: at this moment. But he is doing this dance that
Speaker 1: we're talking about right where he it is driving major
Speaker 1: massive volume for him to convince people with money that
Speaker 1: like the thing they're doing is not part of is
Speaker 1: not on this continuum with like past technological advances. It's
Speaker 1: this new thing that's going to like come in and
Speaker 1: like you know, be a magical HyperIntelligence.
Speaker 4: Yeah.
Speaker 3: And I think there's something particularly ironic when it is
Speaker 3: people like sam Oltman, who you know, may very well
Speaker 3: actually believe all of these things, right, I don't know personally,
Speaker 3: I mean, I don't want to say, oh, he's just
Speaker 3: sort of trying to deliberately create this hype like in
Speaker 3: a very cynical way.
Speaker 4: Maybe he really does believe that. But surely if you really.
Speaker 3: Thought, like, oh, there's actually like a meaningful risk that
Speaker 3: robots could take over and I'm gonna have to.
Speaker 4: Take my site an eye tablet.
Speaker 3: When you just stop investing and making these things, you know,
Speaker 3: these are people who have, like actually do have the
Speaker 3: power to shape the direction of tech development. And I
Speaker 3: think there's something particularly ironic, you know, quite hypocritical about
Speaker 3: scaremongering about AI and AGI while also actively orienting your
Speaker 3: company towards building it and also simultaneously like undercutting regulation.
Speaker 3: So like, at the same time that Oltman was going
Speaker 3: really public about the risks of artificial intelligence, open AI
Speaker 3: was like simultaneously lobbying for weaker regulation with the EUAI Act.
Speaker 3: And I think we see this a lot with Elon Musk,
Speaker 3: for example, warning around the dangers of AI based simultaneously
Speaker 3: firing toward this whole ethical AI team. So to some extent,
Speaker 3: you know, I'm not saying that they deliberately trying to
Speaker 3: weaponize this narrative, but there's just a real mismatch between
Speaker 3: what they're saying and like what they're actually doing and
Speaker 3: the domains that they can control.
Speaker 1: Yeah, at the same time, the people at the forefront
Speaker 1: of you know, understanding what climate change was going to
Speaker 1: look like, We're at Exxon and Chevron, and you know,
Speaker 1: they they were perfectly willing to be like this is
Speaker 1: fucking bad, you guys. It's not our fault, it's your fault.
Speaker 1: Maybe you should switch to paper straws. I think so. Yeah,
Speaker 1: the consensus among people like that, Like I was in
Speaker 1: Davos this past week, and I don't know if you
Speaker 1: guys were there and just talking to some of the
Speaker 1: people there, and I was not in Davos.
Speaker 3: But the.
Speaker 1: Like the idea that sure, we can have these ethical concerns,
Speaker 1: but that's the progress and like what capitalism tells us
Speaker 1: to do is inevitable, Like there's no there's no arguing
Speaker 1: with that. It's just like we're going to always do
Speaker 1: what delivers the most shareholder value. Yeah, and like anything
Speaker 1: else is naive.
Speaker 2: On the World Economic Forums website, like four takeaways from
Speaker 2: you know, like the gathering in Davos, Like one of
Speaker 2: them was talking about like AI is all the buzz,
Speaker 2: and a lot of it was definitely focused on like
Speaker 2: this is how like we're gonna fucking boost global GDP,
Speaker 2: this is how we can close the gaps in like
Speaker 2: the lack of skilled labor, Like it's all gonna happen.
Speaker 2: Then this philosopher spoke like on something about like what
Speaker 2: we completely lose our touch to know what it means
Speaker 2: human anyway, that was like a whole other thing. But
Speaker 2: then this other person came on to talk about like
Speaker 2: they really like sort of nodded at maybe there's something
Speaker 2: to contend with here, but I feel like more of
Speaker 2: the takeaway was like this is y'all, this is how
Speaker 2: we're also gonna get more richer, please, So it's yeah,
Speaker 2: like it's they're definitely trying to do many things at
Speaker 2: the same time, which is like boosting in our in
Speaker 2: our sort of like Zeitgeist. They consciousness that like AI
Speaker 2: is like the fucking like the new pluton like uranium
Speaker 2: plutonium rod that can power everything and also destroy us,
Speaker 2: but also like good for profits. So it feels like
Speaker 2: this omni issue and it just depends on your own
Speaker 2: sort of like your sort of dispositions to sort of
Speaker 2: figure out like what the which version of it you're seeing.
Speaker 2: And then recently, I feel like the latest thing I
Speaker 2: saw as it relates to like politics, because that's where
Speaker 2: I see like it having the most impact right now.
Speaker 2: Like I've seen on YouTube, so many like mid Journey
Speaker 2: created thumbnails to like make it look like certain things
Speaker 2: are happening in the world that aren't just as a
Speaker 2: way to get people to click, but also like in
Speaker 2: New Hampshire, where there's a primary apparently there was like
Speaker 2: a fake Joe Biden robo call that people were trying
Speaker 2: to suspect whether it was like used through some kind
Speaker 2: of AI voice tool or an impressionist or whatever. That
Speaker 2: that's where I feel like we're starting to see the
Speaker 2: real kind of stuff impact our real world rather than
Speaker 2: being like no one works at McDonald's anymore. I guess
Speaker 2: all that to say is is that you know, from
Speaker 2: your perspective, that's why I'm like, okay, doctor carry Like
Speaker 2: I get it. AI is in our toasters now or whatever.
Speaker 2: I can put that aside. But you know, like when
Speaker 2: I think that's the for I think for usespecially in
Speaker 2: the US with this election you're happening, that's where I
Speaker 2: see like a lot of potential for like just it's
Speaker 2: just really these tools that allow people to add to
Speaker 2: like a media narrative very easily in an un compelling way.
Speaker 2: That feels like one of the most potent things we're
Speaker 2: going to see this year. But I'm am, I off, like,
Speaker 2: what from your perspective, what are the things we should
Speaker 2: be looking at, or maybe some things that are distractions.
Speaker 3: No, No, I mean I think you're definitely on there
Speaker 3: when it comes to the meaningful risks posed by AI
Speaker 3: and its ability to help generate disinformation. And because we've
Speaker 3: got I think, over seventy elections this year, so it's
Speaker 3: a huge year internationally for elections, including as you mentioned,
Speaker 3: the US election, and we've seen kind of the past
Speaker 3: few elections in the US and also elsewhere, like the
Speaker 3: way that disinformation and kind of the mass spreading of
Speaker 3: forms of political ideology has been hugely damaging I think
Speaker 3: in many ways to our information society and the way
Speaker 3: that we conduct political elections. And we've seen unfortunately examples
Speaker 3: of specifically AI generated misinformation. But I think actually it
Speaker 3: was in the Slovakian elections a few weeks ago where
Speaker 3: there were a number of AI generated clips and deep fakes,
Speaker 3: including one where one of the candidates was I think
Speaker 3: the audio was edited in a way, but it appeared
Speaker 3: that they said they were going to double the price
Speaker 3: of beer, which in that context was like a huge
Speaker 3: which kind of outcry, like really very very damaging to things.
Speaker 4: President's so important. Yeah, and so people were like.
Speaker 3: Whoa you know, and so, you know, we do see
Speaker 3: examples of this At the same time, I think, you know,
Speaker 3: for me, this is one of those classic examples where
Speaker 3: tech illuminates a problem that's already there, right, so AI
Speaker 3: can provide people the tools to make more convincing misinformation,
Speaker 3: maybe to make that more scale. These things are both bad,
Speaker 3: but I think we need to say, actually, what makes
Speaker 3: people vulnerable the misinformation in the first place? What makes
Speaker 3: people vulnerable to fake news? Why do people still choose
Speaker 3: to consume and share fake news even when they know
Speaker 3: it might not be factually true? Like these are all
Speaker 3: things where again, you know, I think technology is often
Speaker 3: treated as a domain just for computer scientists or mathematicians.
Speaker 3: But this is why we need psychologists, and we need
Speaker 3: people from the humanities and the social scientists, we need
Speaker 3: political scientists to try and understand, you know, what makes
Speaker 3: in communities vulnerable to these kinds of narratives and ideas.
Speaker 3: And I think until we do that and really prioritize
Speaker 3: this kind of research, building bitter media literacy and bitter
Speaker 3: resilience to these narratives, like, we're not going to necessarily
Speaker 3: be able to find a quick tech fix.
Speaker 1: Yeah, I would just stand. I would just like accept
Speaker 1: going eight years into the past in terms of like
Speaker 1: how much media there was, like how much money was
Speaker 1: being spent on media, because it's just such a fucking
Speaker 1: just waste land out there these days, like all all
Speaker 1: of the legacy media outlets are just gone or not
Speaker 1: spending money they are they seem as likely to be
Speaker 1: using AI tools. Like I got this headline from the
Speaker 1: La Times this weekend sent through to my phone. The
Speaker 1: headline was could your life could use more? Wonder question
Speaker 1: mark from the La Times, Like it's I don't know
Speaker 1: that they're using AI, Like maybe it's just a typo,
Speaker 1: but like I don't know, Sports Illustrated like we found
Speaker 1: out about them getting caught using AI, uh and it
Speaker 1: was you know, the articles are just there and like
Speaker 1: saying nothing. So like it's just this weird situation where
Speaker 1: the people who I think typically we would be counting
Speaker 1: on to be like gatekeepers for this sort of like
Speaker 1: misinformation are also the ones who are like trying to
Speaker 1: get by using the technology to replace humans.
Speaker 2: Yeah.
Speaker 1: So it's just a such a weird environment and it
Speaker 1: just feels like we're facing a blizzard of of misinformation
Speaker 1: now instead of you know, something that you can like
Speaker 1: point to and be like, okay, here's one thing, one
Speaker 1: lie that they're trying to spread. Now it's like there's
Speaker 1: forty a day. Basically could you life use more?
Speaker 2: Wonder could And you're like, mom, maybe, but like it's
Speaker 2: also I feel like it's just accelerated just degradation of
Speaker 2: like journalism in general, and like, you know, look at
Speaker 2: what happened to Pitchfork in other places, or like I
Speaker 2: think a lot of media companies do a look at
Speaker 2: it is like, yeah, sure, this website that used to
Speaker 2: have all these great journalists, people don't come there for
Speaker 2: like their human writing anymore. It's just a brand that
Speaker 2: brings people to click on things. And if I can
Speaker 2: see that sort of tent with all this fake tent
Speaker 2: or content as y'all call it, that people will just
Speaker 2: go continue to click, it is like, and that's how
Speaker 2: we make money. It's not even that what's written there
Speaker 2: is important. It's just that I can create a little
Speaker 2: click website that people do clickies on all day and
Speaker 2: fuck all the human like contribution aspect to it. And yeah,
Speaker 2: then we're left with more and more people getting laid
Speaker 2: off and just these like really bizarre like you can
Speaker 2: tell it's just wild that you can tell pretty quickly. Now,
Speaker 2: I feel like when I'm starting to read something with
Speaker 2: a I'm like you're leaning into these like very specific
Speaker 2: details so much in the writing or it's like it
Speaker 2: reminds me again of like when I used to bullshit
Speaker 2: on an essay and high school and be like George Washington,
Speaker 2: who was also known as our nation's first president, and
Speaker 2: like just adding all this detail about George Washington rather
Speaker 2: than like getting to the point or commentary about what
Speaker 2: he did. And so yeah, like it's just I feel
Speaker 2: like those are the other meaningful ways that we see
Speaker 2: things going downhill.
Speaker 3: But it's yeah, yeah, I mean I feel like just
Speaker 3: the sad way you said, yeah, it was like a
Speaker 3: pretty good summary. So I feel going on Twitter nowadays,
Speaker 3: like I just, you know, all my joy from that
Speaker 3: platform has gone. But I think you point out something
Speaker 3: really important, which is while the revenue model for news
Speaker 3: sites is clickspace and advertising base, like I think we're
Speaker 3: not necessarily also going to see a solution to this
Speaker 3: problem because unfortunately, you know, and I know this from
Speaker 3: doing like my own social media promotion with the podcast
Speaker 3: I do the Good Robot. The thing that generates money
Speaker 3: is controversy effectively, like nothing does as well as the
Speaker 3: post that I do on TikTok where someone has, you know,
Speaker 3: a go at me because they don't like my particular
Speaker 3: interpretation of Star Trek or whatever. It can be pretty
Speaker 3: good null, but that as soon as a fight starts
Speaker 3: in your comments, that's when a video starts to get views.
Speaker 3: And so, you know, Kathy O'Neil, the AI ethicist, has
Speaker 3: a really interesting book on this called The Shame Machine,
Speaker 3: which he talks about who profits from public shaming, who
Speaker 3: profits from like these big Twitter pilons, Like it's big tech,
Speaker 3: it's firms like Twitter or x or whatever that will
Speaker 3: inevitably be called next year. But you know, it's the
Speaker 3: big platforms, and it's not the people who are doing
Speaker 3: the piling on or the people getting piled on. And
Speaker 3: so I think we see kind of a similar thing
Speaker 3: with a lot of these news media organizations, which is
Speaker 3: when the incentive is just to get as much visibility
Speaker 3: as possible.
Speaker 2: Rather than to be informing.
Speaker 3: You know, providing you know, yeah, true information. You know,
Speaker 3: I think we're not going to find a solution.
Speaker 1: Yeah, all right, we're going to take a quick break
Speaker 1: and we're going to come back and talk about maybe
Speaker 1: some good things, some good possibilities, like is good technology possible? Still,
Speaker 1: we will be right back, and we're back. And one
Speaker 1: of the things that your new book, doctor mcnernie, you
Speaker 1: talk about is what is good technology and is it possible?
Speaker 1: And I feel like I'm so used to this hyper
Speaker 1: capitalism paradigm that I don't think we can have technology
Speaker 1: without having like loss of jobs and free will. But
Speaker 1: I don't know, I've seen this like recent reappraisal of
Speaker 1: like the Luddite movement, which is just a phrase that
Speaker 1: I grew up using to be like anybody who didn't
Speaker 1: want to use a computer and you know, was slightly
Speaker 1: resistant to technology technological progress. And now people like pointing out, no,
Speaker 1: they didn't just want to destroy all machines. They were
Speaker 1: focused on the ones that took jobs and led to
Speaker 1: wage losses. But we turned them into like old man
Speaker 1: screaming at cloud because of our paradigm of like, yeah,
Speaker 1: but that's counterprogress, that's unrealistic. Like so what is my
Speaker 1: closed off capitalist mind missing out on when I think
Speaker 1: about like the direction that technology can take like what
Speaker 1: are the good things that aren't just like basically AI
Speaker 1: being McKinsey.
Speaker 3: Yeah, no, no, I mean, first, I do love this
Speaker 3: reappraisal of the Loutist movement. I know Brian Merchant has
Speaker 3: a book out called Blood in the Machine which is
Speaker 3: like specifically try to reframe the Luddites, this movement. It
Speaker 3: gives what a mation in the UK as the origins
Speaker 3: of the revolution against Big Pick. And I do love
Speaker 3: this because I do think the Ludyites have been unfairly
Speaker 3: maligned as these tech haters. But yeah, second, you know
Speaker 3: so myself and my work wife, doctor Eleanol Drage co
Speaker 3: edited this book called The Good Robot, which is the
Speaker 3: same as our podcast on this provocative question, and we
Speaker 3: mean it very much as like a suggestion and idea,
Speaker 3: not like an inevitability that technology, you know, maybe can
Speaker 3: be good in.
Speaker 4: A lot of spaces. That definitely doesn't sound like.
Speaker 3: A particularly radical idea, particularly in the like tech type
Speaker 3: spaces we've discussed, but like for people like us who
Speaker 3: spend our day to day looking at these really awful
Speaker 3: effects technology like either because they have been designed to
Speaker 3: be really awful, like predictive policing, tools, or because they're
Speaker 3: being exploited and used in like really harmful ways, like
Speaker 3: the way that technologies used to perpetrate gender based violence.
Speaker 3: It can be really easy to be unable to see
Speaker 3: any kind of positive possibilities for a lot of these
Speaker 3: new technologies. But while I definitely, you know, think that
Speaker 3: there's a real place for just the total refusal of
Speaker 3: people like the Luodites or the neo Luodite movement, which
Speaker 3: is kind of trying to bring back a lot of
Speaker 3: these ideas. We want to challenge ourselves and all the
Speaker 3: guests we have in our podcasts to say, like, you know, what,
Speaker 3: does what would it mean for technology to be good?
Speaker 3: And so for us that's feminist and pro justice and
Speaker 3: afformed by all these different kinds of ideas about equality
Speaker 3: and fairness and also what would that look like sort
Speaker 3: of grounded in our everyday lives. So for me, for example,
Speaker 3: a lot of thinking about good technology is trying to
Speaker 3: reclaim technologies that we might not think of as being
Speaker 3: very like high tech, often because they've been associated with women.
Speaker 3: So like I knit, and I have a pair of
Speaker 3: knitting needles on the table next to me, and knitting
Speaker 3: is often not understood as being like a very high
Speaker 3: tech practice. But in the nineteen eighties, when people are
Speaker 3: trying to get more girls and women back into computer science,
Speaker 3: there was this idea that if you can knit, you
Speaker 3: can code, because if you can read a knitting pattern,
Speaker 3: then you can use a coding program like and so
Speaker 3: sometimes now computer science conferences you'll see people put a
Speaker 3: knitting pattern up on the screen and just say what
Speaker 3: coding language is this, And then usually only one or
Speaker 3: two people, often one of the few female attendees will say, oh,
Speaker 3: that's a knitting pattern, because they're the only ones that
Speaker 3: can understand that kind of code. So I think there's
Speaker 3: something really beautiful and like reclaiming those particular kinds of
Speaker 3: technologies that have been maybe excluded from the way we
Speaker 3: talk about tech on my again work wife who co
Speaker 3: edited this book, well she edited most of it actually,
Speaker 3: so who really did the heavy lifting on this book.
Speaker 3: Eleanor talks about the whisk as her example of a
Speaker 3: good technology, and she says she loves the way it looks,
Speaker 3: she likes how she can use it in all these
Speaker 3: different ways, and she says, you know, she's sure there's
Speaker 3: ways that you can misuse this but you know, she's
Speaker 3: it's something that just like makes her life better and
Speaker 3: is designed well in a very simple way. I unfortunately
Speaker 3: have already undermined this good technology for her because I
Speaker 3: then told her about when I was about fourteen, my
Speaker 3: school went to a trip at the Technology Museum in Auckland.
Speaker 3: It's good motet if you're from New Zealand. Everyone's in
Speaker 3: Auckland's been to this museum because it's not that much
Speaker 3: to do in Aland for a school trip. And then
Speaker 3: one of the girls in my class wound the hair
Speaker 3: of another girl into like an antique egg beta.
Speaker 4: Then they couldn't get her out. She got stuck.
Speaker 3: You know, children can make full technologies bad. But apart
Speaker 3: from that, you know, I think like trying to find
Speaker 3: these like little examples of technology that aren't about the
Speaker 3: kind of like big hype of AI, but maybe bring
Speaker 3: us back into the ways that we use technology to
Speaker 3: reshape how worlds and make things a bit better.
Speaker 4: Is what I like to do with this question.
Speaker 2: Is when you think of like, you know, I think
Speaker 2: that the one version is like, well, this generative AI,
Speaker 2: like it democratizes certain things, and I think while on
Speaker 2: one hand, it may allow people access to like create
Speaker 2: things that they haven't before. It also makes other Like
Speaker 2: you're saying, it's the use of it that makes things
Speaker 2: that sort of ultimately determines whether or not a technology
Speaker 2: is good or you know, used in a positive or
Speaker 2: negative way? Is there like when you look at all
Speaker 2: like for all the people that are preaching and proclaiming
Speaker 2: about how AI is opening the door to something new,
Speaker 2: what like as it relates to sort of these law
Speaker 2: large language models, what are the ways that that can't
Speaker 2: Like is that more about a use case or we
Speaker 2: need to lean more into the regulations to make sure
Speaker 2: that AI isn't wielded by nefarious powers? Like how do
Speaker 2: you look at that specific technology and think, Okay, while
Speaker 2: there's definitely like a lot of biased or weird uses
Speaker 2: of it, like, there's also another way to look at
Speaker 2: this and not just kind of like lean into the
Speaker 2: skynet version.
Speaker 3: Yeah, I mean I would take this in a lot
Speaker 3: of different ways. Like my first and sort of most
Speaker 3: important route in is I would say who makes these
Speaker 3: models and who has control over them and who can
Speaker 3: afford to because you know, one of the big changes
Speaker 3: I think that's happened in the last few years is
Speaker 3: that language models have gone from much smaller models that
Speaker 3: maybe like one researcher with a reasonable budget could train
Speaker 3: themselves a lab, to being these absolutely huge models that
Speaker 3: you need a massive amount of energy, a massive amount
Speaker 3: of data, and a massive amount of money to create.
Speaker 3: And so what that means is that companies with a
Speaker 3: move advantage like Google, like open ai are the ones
Speaker 3: who can afford to make these models. And I think
Speaker 3: increasingly it's going to be harder and harder as the
Speaker 3: models get bigger for small firms to enter that market.
Speaker 3: So what we end up with them is a monopoly,
Speaker 3: and I think we're starting to see some of the
Speaker 3: effects of that monopoly right now, where you have a
Speaker 3: few big tech firms kind of having a hand on
Speaker 3: like most of the most powerful and effective models. And
Speaker 3: so I think like even though people say, oh, this
Speaker 3: is going to democratize AI because everyone can generate text
Speaker 3: with these models, It's like, yes, but you know, very
Speaker 3: few people are profiting from it. And also, you know,
Speaker 3: I think very few people then have control as well
Speaker 3: over how long we're able to use those models for
Speaker 3: one day, will they just all be turned off or
Speaker 3: will they be shifted in a way, you know, so
Speaker 3: I think there's still kind of a concentration of control. Yeah,
Speaker 3: And I think second, like you mentioned kind of biases
Speaker 3: and like weird stuff in the models super important, Like
Speaker 3: large language models are trained on data scrape from the Internet,
Speaker 3: and that can be not the best place, as.
Speaker 4: We all know.
Speaker 3: It can be right for all kinds of information, but
Speaker 3: it's also full of a lot of exclusions. So like,
Speaker 3: for example, again when I was working talking to these
Speaker 3: data scientists and engineers at this big tech firm with us,
Speaker 3: things like, oh, well, where do you pull your training
Speaker 3: data from? And they'd say Wikipedia, for example, and you know,
Speaker 3: would say, oh, but like Wikipedia is not a very
Speaker 3: equitable place. Like women are really really vaskally underrepresented on
Speaker 3: Wikipedia pages, both in terms of who writes them and
Speaker 3: also in terms of who gets Wikipedia pages written about them.
Speaker 3: So the physicist Jess Waded here in the UK has
Speaker 3: had this long running project where she just adds a
Speaker 3: woman to Wikipedia like every day, and she's done that,
Speaker 3: I think now for like years. But that it kind
Speaker 3: of just shows like how inequitable though that distribution is.
Speaker 3: If you're training a model on data from Wikipedia, implicitly,
Speaker 3: you might not be trying to do this in any way,
Speaker 3: like you're also training that model to believe in a
Speaker 3: world where say, like women make up of the population
Speaker 3: not fifty percent plus. So there's a lot of like
Speaker 3: bio season harms that come just from exclusion. Another example
Speaker 3: of this is, you know, I have a good friend
Speaker 3: who is a linguist, and something she talks about is
Speaker 3: community that don't have written languages are already automatically just
Speaker 3: not going to be able to partake and whatever benefits
Speaker 3: might come from large language models, whether that's signed languages
Speaker 3: or languages that are only oral, and so you know,
Speaker 3: I think there's just a lot of different ways that
Speaker 3: even beyond these kind of immediate harms of like the
Speaker 3: AI has produced something that we think is really offensive
Speaker 3: or gross that we could see the use of large
Speaker 3: language models maybe creating further inequities.
Speaker 1: Now, a lot of the AI like promise, like the
Speaker 1: developments that are being promised. So even at Davos, like
Speaker 1: this past Davos, at this page I had to miss unfortunately,
Speaker 1: and I hate to miss Davos because I learned so
Speaker 1: much there.
Speaker 2: But you've been to four Davi.
Speaker 1: Havn't you Devia my fourth dim was the best man.
Speaker 1: We all did mally and just had a cuddle puddle.
Speaker 1: But Sam Altman, I don't know if he's like consciously
Speaker 1: scaling back people's expectations, but he was like, soon you
Speaker 1: might just be able to say what are my most
Speaker 1: important emails today and have AI summarize them. I was
Speaker 1: just like, all right, Like I doesn't like outlook already
Speaker 1: have an offer, like offer a shitty version of that already.
Speaker 1: So it's like it just feels like the versions of
Speaker 1: AI that I'm hearing, Like there's this older New Yorker
Speaker 1: article that was like, I'm not that worried about AI.
Speaker 1: I think it's from like the kill us all perspective.
Speaker 1: I think it's going to be like a little McKenzie
Speaker 1: in everyone's pocket, Like it's going to be this like
Speaker 1: economic optimization tool that like everybody has access to, and
Speaker 1: that's going to just make everything shitty and boring. So
Speaker 1: I don't know, like I'm just curious for your thoughts
Speaker 1: on that, and like if there are examples of just
Speaker 1: like functionality from AI that actually like capture your imagination
Speaker 1: where you're like, oh shit, that would be like cool,
Speaker 1: that's a cool idea of like something that would be
Speaker 1: fun and you know, improve people's lives, even if it's
Speaker 1: just like make their video games better or whatever.
Speaker 3: Yeah, I mean maybe the email thing appeals to some people. Personally,
Speaker 3: I want fewer emails. I don't want summary of my emails.
Speaker 3: I just want my inbox to quietly shut down through
Speaker 3: the hours of like five pm, to like send a
Speaker 3: AM every day and just be like I'm email free.
Speaker 3: And then the run at em Bogass I think has
Speaker 3: this idea of hyper employment, which is like the technologies
Speaker 3: that say they're going to make our lives easier and
Speaker 3: more stress free actually make our lives much busier and
Speaker 3: we now waste a lot more time. So he talks
Speaker 3: about emails as a way of, you know, saying like, oh,
Speaker 3: we're gonna have far fewer meetings and we're gonna like
Speaker 3: have spend less time like sending each other letters or whatever.
Speaker 3: Sorry I'm from the post internet generation, but then now
Speaker 3: we spend like so much time like answering emails. And
Speaker 3: I think AI feels a bit like this, like when
Speaker 3: people say like AI is going to save you so
Speaker 3: much time, I'm like, you are not a teacher an educator,
Speaker 3: because the amount of time we have wasted this year
Speaker 3: trying to figure out what to do with AI generated
Speaker 3: essays like absolutely not. Yeah, and so I feel like
Speaker 3: things like the AI email summarized I since could end
Speaker 3: up in a very similar appile. But you know, kind
Speaker 3: of to come to the more positive side of your question,
Speaker 3: like what makes me excited, I think a couple of things.
Speaker 3: Like one is like anything where like AI can genuinely
Speaker 3: scale up in a way that is not too ecologically
Speaker 3: damaging or costly a process that is already going well,
Speaker 3: where the statistics and the procedures in place are working
Speaker 3: for us. Because AI is able to scale things, you know,
Speaker 3: it's not necessarily able to do new things always. So
Speaker 3: if we know we have a sorting or categorization process
Speaker 3: that works, that's I think AI computer vision.
Speaker 4: These kinds of systems can be really useful.
Speaker 3: Where it doesn't work is when you're asking AI to
Speaker 3: do something that like we don't actually have good processes
Speaker 3: in place to do so, like when a tool says, oh,
Speaker 3: I can like power candidate's personality from their face, Like.
Speaker 4: No, you can't do that. That's just a straight up phrenology.
Speaker 4: Please don't do that.
Speaker 3: But also Secondly, like, you know, if we had easy
Speaker 3: ways of telling if someone was going to be good
Speaker 3: for a job, like humans will be able to do
Speaker 3: it already, Like this is a much much more complicated
Speaker 3: than you're making it out to be. A second kind
Speaker 3: of use I think I find really exciting or makes
Speaker 3: me like you're really happy. I think it's particularly tools
Speaker 3: around trying to kind of like support particular community as
Speaker 3: needs in a way that is really driven by that community.
Speaker 3: So for example, in New Zealand where I'm from, there's
Speaker 3: been a lot of effort put into different kinds of
Speaker 3: like AI powered tools and data sovereignty programs around Maudi traditions,
Speaker 3: the Maudi language or three a Maudi and like I think,
Speaker 3: you know, this is an example of where like that's
Speaker 3: been led by Maudi people and is in a response
Speaker 3: to kind of the way that in colonial New Zealand,
Speaker 3: like there a Maudi was like very deliberately stamped out,
Speaker 3: and there's been a huge movement to try and kind
Speaker 3: of protect and revive the language. And I think it's
Speaker 3: like when your projects like this that makes me a
Speaker 3: bit more hopeful about the way that AI machine learning
Speaker 3: could be used to you know, promote these pro justice projects.
Speaker 3: But you know, I think those projects that always have
Speaker 3: to exist in a little bit of tension with like
Speaker 3: big tech. And we've seen this like with other organizations,
Speaker 3: for example like Masacana, which is the amazing grassroots organization
Speaker 3: which aims to bring the like four thousand different African
Speaker 3: languages into our natural language processing models or large language models.
Speaker 4: You know.
Speaker 3: But I know that these kinds of groups often do
Speaker 3: struggle with this idea like do we commercialize because then
Speaker 3: will we be brought into this hyper capitalist world? Do
Speaker 3: we keep this to ourselves? But yeah, I think it's
Speaker 3: it is important sometimes to step back and be like,
Speaker 3: there are really interesting community projects which are trying to
Speaker 3: use these techniques and these kinds of knowledge in ways
Speaker 3: that push back against like the email summarizing bot.
Speaker 1: Right, is there a historical present? Like I was reading
Speaker 1: some articles about the competition between the United States and
Speaker 1: China and how the US is like trying to freeze
Speaker 1: export of like certain chips to China because they think
Speaker 1: that will allow China to catch up with them, And
Speaker 1: it feels like we're there's going to be inevitably an
Speaker 1: argument where they're like, we need to just go pedal
Speaker 1: to the floor on AI development because this is the
Speaker 1: new Manhattan Project. Trust us, you talk a lot about
Speaker 1: just like this, this alternate possibility of like what what
Speaker 1: if we didn't use this technology for hypercapitalism and militarism.
Speaker 1: Are there examples where, like from history that you're aware of,
Speaker 1: where like technology hasn't been has successfully been like protected
Speaker 1: from those sorts of things. Are there any even a
Speaker 1: very small examples where people have been able to keep
Speaker 1: technology like fenced off from that sort of thing.
Speaker 3: Yeah, no, I mean this is something that really preoccupies me.
Speaker 3: I spend a lot of time mapping and tracking with
Speaker 3: the AI now institute this narrative of an AI arms
Speaker 3: race between the US and China and how that story
Speaker 3: is super damaging because it can cause us like race
Speaker 3: to the bottom and leads to us trying to develop
Speaker 3: AI faster and faster without necessarily trying to make it
Speaker 3: better or safer. And do you know, I think we've
Speaker 3: seen some positive movements when it comes to AI regulation recently,
Speaker 3: from like the US's commitment or declaration around AI through
Speaker 3: to the Bletchley Declaration in the UK and the EUAI Act.
Speaker 3: But at the same time, you know, I think that
Speaker 3: this sort of racing narrative like still looks and it's
Speaker 3: still sometimes used to try and push back against regulatory measures,
Speaker 3: particularly by people with investments in big tech. But yeah,
Speaker 3: at the same time, I also think this question of, like,
Speaker 3: can we look to history to find ways to tell
Speaker 3: different stories about AI maybe bring about different futures is
Speaker 3: something that really interests me. I think the comparison that
Speaker 3: is most often made between AI and another technology when
Speaker 3: it comes to like regulation and governance is nuclear and
Speaker 3: specifically nuclear weapons. Like and like you mentioned, Manhattan Project,
Speaker 3: suddenly kind of this sort of language of like an
Speaker 3: Oppenheimer moment when it comes to AI, and this kind
Speaker 3: of idea of being like the cusp of a new
Speaker 3: cold water will be AI driven rather than nuclear weapons
Speaker 3: driven is a very common media narrative. But something I
Speaker 3: try to do, like with my own research, is to
Speaker 3: try and look for and support different kinds of historical
Speaker 3: analogies that maybe offer maybe less kind of less hawkish
Speaker 3: futures when it comes to international politics. So for example,
Speaker 3: Maya Indira Ganish, who's a fantastic researcher at Believer Human
Speaker 3: Center where I'm at, looks to like histories of feminists
Speaker 3: cyber governance in the early two thousands, as a way
Speaker 3: of saying, like, actually, we have a lot of precedents
Speaker 3: for thinking about the ethics of the internet. Why aren't
Speaker 3: we bringing this into thinking about AI? Or Matischmas, who's
Speaker 3: a legal researcher, looks the histories of technological restraints, So like,
Speaker 3: when did we choose not to make a technology even
Speaker 3: though we could because we thought that it actually wouldn't
Speaker 3: be good for the world and for societies. And so
Speaker 3: I think, you know, like making sure we have examples
Speaker 3: outside of nuclear because wild nuclear can be still useful
Speaker 3: in some ways, Like it's only one metaphor, and metaphors
Speaker 3: are inherently limited. They tell us something about the world,
Speaker 3: but they can't tell us everything. And I thinks having
Speaker 3: these alternative historical examples can be really useful for thinking
Speaker 3: a bit differently.
Speaker 1: Yeah.
Speaker 2: So, yeah, it's just funny because in the end, it
Speaker 2: always feels like thing with potential to create like unforeseen
Speaker 2: levels productivity or power. It's like and then we made
Speaker 2: it a weapon.
Speaker 1: Then we like put it in the bomb, you know,
Speaker 1: kind of.
Speaker 2: Like and yeah, like we really do have to sort
Speaker 2: of break out of that thinking. I mean, I wonder
Speaker 2: precisely because our brains are filled with sky Net and
Speaker 2: Oppenheimer and the Manhattan Project, that that's we're just We're
Speaker 2: just in this really weird pattern of always looking at
Speaker 2: something that has the potential to unlock new levels of
Speaker 2: something are inherently going to always be like, but how
Speaker 2: does how do our enemies kill us with it? And
Speaker 2: then we begin to lose the plot there. So yeah,
Speaker 2: I'm I'm yeah, look to these other examples to try
Speaker 2: and again open my mind to looking at it less
Speaker 2: of like and then how they make and then how
Speaker 2: they make global domination with that?
Speaker 3: Right, Yeah, I mean I think it's either it's like
Speaker 3: how do we kill someone with it? Or as I
Speaker 3: think the history of like how tech is represented in
Speaker 3: Hollywood would show us like how do we have sex
Speaker 3: with it? And this is like a very classic trip
Speaker 3: in sci fi, right, It's like you get like a
Speaker 3: dude in his basement who makes like a sex spot.
Speaker 3: And I remember interviewing Jack Harbuston, who's like this very
Speaker 3: famous feminist and queer theorist with Eleanor on the podcast,
Speaker 3: and he was talking about the film X Markina. Have
Speaker 3: you seen this since from like twenty fourteen. It's like
Speaker 3: a kind of a kind of an indie film, but
Speaker 3: had quite a lot of prestige I think success particularly like.
Speaker 1: Tech Circles, Yeah for sure.
Speaker 2: Yeah.
Speaker 3: Yeah, And so I remember we were talking about x
Speaker 3: Markina and Jack Harbison was saying like it sort of
Speaker 3: shows like the limits of the imagination, like particularly like
Speaker 3: the tech pro imagination that he has like all this
Speaker 3: expertise at his fingertips, all this data and he basically
Speaker 3: just makes like sex robots and like that's really.
Speaker 4: Good, really thing to do with it.
Speaker 3: And I think, you know, to some extent, like we're
Speaker 3: still a little bit trapped in that imagination, which is
Speaker 3: why I think like both like different projects to do
Speaker 3: with AI, but also different stories about AI are really crucial, right.
Speaker 2: Yeah, Yeah, we have to get out of the fuck
Speaker 2: or fear paradigm. Right that we have the technology, it's
Speaker 2: going to do one of the two, man, So yeah,
Speaker 2: we need a new ways.
Speaker 1: I'm here to do two things, fuck something or kill
Speaker 1: because I'm scared of it.
Speaker 2: Yeah. Yeah.
Speaker 1: Well, doctor Kerry mcinernie, what a pleasure having you back
Speaker 1: on the Daily Geist. Where can people find you?
Speaker 2: Follow?
Speaker 1: You all that good stuff.
Speaker 4: You can find me at Carrie A.
Speaker 3: Mcinernie on Twitter slash x reluctantly still there, I know
Speaker 3: those are around. That's the Good Robot Book, which you
Speaker 3: can find at Bloomsbury for pre order. It'll be out
Speaker 3: next month, I think, also on Amazon, but yes, please
Speaker 3: take a look if you're interested in all things feminism
Speaker 3: and technology.
Speaker 1: Amazing and is there a work of media that you've
Speaker 1: been enjoying.
Speaker 3: Oh gosh, all that's coming to mind right now is
Speaker 3: this tweet that I saw that I just moved to
Speaker 3: London quite recently, and it was a tweet where someone
Speaker 3: had said should I like stay in bed or get
Speaker 3: out of bed and inevitably spend one hundred and forty dollars?
Speaker 4: And I feel like that's literally my life right now.
Speaker 3: I just spend all my time deciding like do I
Speaker 3: risk going outside? And this very beautiful but very expensive
Speaker 3: city I've been enjoying that.
Speaker 2: Yeah, it's uh, it's funny too because even comparatively, like
Speaker 2: coming from la I'm like, man, I wish there was
Speaker 2: London prices here. Yeah.
Speaker 1: The US is bad right now right now, and it's
Speaker 1: gonna get better one day. I kicks in.
Speaker 2: Yeah, exactly. Can a I bring the prices down? No, unfortunately,
Speaker 2: but like it's funny too because we were just on
Speaker 2: the heels of like that story that came out about like, yeah,
Speaker 2: a lot of the cost of living of ills that
Speaker 2: we're feeling because of greed flation and really nothing to
Speaker 2: do with anything else aside from companies being like, yeah, yeah,
Speaker 2: we can squeeze them.
Speaker 1: Let's squeeze them. If only there was a daily comedic
Speaker 1: news podcast that has been saying that for years.
Speaker 2: That makes me very mad. And if there is, let
Speaker 2: us know about that podcast. Yeah, that sounds like a
Speaker 2: good show. Miles.
Speaker 1: Where can people find you as their working media you've
Speaker 1: been enjoying?
Speaker 2: Uh yeah, let's see. You can find me at Miles
Speaker 2: of Gray, at all the app based platforms. You can
Speaker 2: find us Jack and Miles on our basketball podcast Miles
Speaker 2: and Jack Got Mad map please, And if you like
Speaker 2: a bit of ninety day reality trash, you can check
Speaker 2: me out on four to twenty day Fiance that I
Speaker 2: do with Sofia Alexandra. Let's see. Let's see. Let's see
Speaker 2: a tweet I like this one is from the hype
Speaker 2: with five four wise tweeted boarding a flight, a guy
Speaker 2: is trying to sit down in seat sixteen D because
Speaker 2: that's his seat, but there's a lady already sitting there.
Speaker 2: He asks if she's in the right seat, and she says, no,
Speaker 2: I'm actually fifteen D, but sixteen is my lucky number,
Speaker 2: So do you mind if I stay here? And he goes, what,
Speaker 2: it's a wild like we always see stories like this
Speaker 2: or people like just on like just out for vibes purposes,
Speaker 2: like do you mind if I, like don't sit in
Speaker 2: my seat and because I just like a window better,
Speaker 2: Like huh no.
Speaker 4: No, this is my pet peek.
Speaker 1: I'm generally a pretty easy switch on the on the plane,
Speaker 1: I don't I don't really give a fuck. I mean,
Speaker 1: obviously if I'm sitting next to my kids, but like
Speaker 1: if if it's just me, I'll switch with you. Yeah, yeah,
Speaker 1: you can target me weird vibes people, I'll switch with you.
Speaker 1: I'll be like, oh, you seem attached to it.
Speaker 2: I mean, I get like, if I'm just sitting in
Speaker 2: an identical seat just in a row behind, I guess not,
Speaker 2: but it's just so weird for the person that sort.
Speaker 2: It just irks me a bit. Is that you feel
Speaker 2: that you are entitled to your vibe seat.
Speaker 1: God, Like, what it must be like to live in
Speaker 1: a head like that though, Yeah, goddamn.
Speaker 2: I would be like what would happen if I said, no,
Speaker 2: the plane goes down right, The plane goes down right,
Speaker 2: the plane goes down right? Yeah, then you know what,
Speaker 2: I'm not feeling too great, So you know what, I
Speaker 2: think I want my original seat. Thanks get your asked
Speaker 2: to fifteen D doctor mcnernie. You were saying that's your
Speaker 2: pet peeve? Is somebody try really is?
Speaker 3: Because I'm like a we towel of a person. So
Speaker 3: someone just like sits in my seat and it's like,
Speaker 3: this is my seat. Now, I'm like, I resent you
Speaker 3: so much? But also am I really.
Speaker 4: Going to pick a fight? But what if you're just like,
Speaker 4: what sixteen is my lucky number? Oh it's crazy who's
Speaker 4: going to win on that?
Speaker 2: Yeah?
Speaker 3: But no, I resent that the person that tweeted I'm
Speaker 3: with you, Yeah my seat please?
Speaker 2: I mean I get to like, like from jack your perspectives,
Speaker 2: like whatever, it's not that big of a deal for
Speaker 2: me to like sit there. But there's also just this
Speaker 2: part of like how quickly the world just owed you everything.
Speaker 1: Mm hmmm, Oh, I will be sitting in my new
Speaker 1: seat for the entire flight, sweating with anger at them
Speaker 1: to keep it inside, and I'll have a summer later on.
Speaker 2: Like you know what, I'm going to say something, ladies
Speaker 2: and gentlemen, we are making our descent, so if you'd like,
Speaker 2: please put your seat back. I should have said something,
Speaker 2: should have said something next.
Speaker 1: My seat's twenty seven c right across from the laboratory.
Speaker 2: Okay, the stink seat over in stinc hut tweet.
Speaker 1: I've been enjoying. Something that got retweeted a lot was
Speaker 1: this tweet from Emily K tweeted. The thing about Taylor
Speaker 1: Swift is that she so perfectly encapsulates through her lyrics
Speaker 1: the interior lives of women. It's why we all can't
Speaker 1: stop listening. We're all saying, wait, you felt that way,
Speaker 1: We were all feeling this way. Do men have someone
Speaker 1: like that? And then metal dot t xt responded we do, yeah,
Speaker 1: and screen capped the chorus from the boys are back
Speaker 1: in town, which God, which reads the boys are back
Speaker 1: in town. The boys are back in town. I said,
Speaker 1: the boys are bagging down, the boys are backing down,
Speaker 1: Like seven times. I didn't realize that said it so
Speaker 1: many times in a row. So yeah, we got that
Speaker 1: one cover. Yeah, you want to know how men's minds work.
Speaker 1: We're just excited that the boys are back in town,
Speaker 1: and that's basically it. You can find me on Twitter
Speaker 1: at Jack Underscore O'Brien. You can find us on Twitter
Speaker 1: at Daily Zeitgeist. We're at the Daily Zeitgeist on Instagram.
Speaker 1: We have a Facebook fampage and a website, Daily zeiguist
Speaker 1: dot com, where we post our episodes and our footnotes
Speaker 1: where we link off to the information that we talked
Speaker 1: about today's episode, as well as a song that we
Speaker 1: think you might enjoy. Miles, what song do we think
Speaker 1: people might enjoy?
Speaker 2: Uh? It's rainy here in La. I was just I've
Speaker 2: been listening to some Alex, some jazz, you know, some
Speaker 2: saxophone from Joe Henderson, who's a great sax player. This
Speaker 2: is a track called black Narcissus. Uh, and just a
Speaker 2: good just a nice rainy day song just to have
Speaker 2: on and just look out your window, do some reading,
Speaker 2: whatever whatever you want to do. But yeah, this is
Speaker 2: it Joe Henderson Black Narcissus.
Speaker 1: All right, we will look off to that footnotes Today.
Speaker 1: Zaike is a production by Heart Radio. For more podcast
Speaker 1: from My heart Radio, visit the iHeartRadio, ap Apple podcast,
Speaker 1: or wherever you listen to your favorite shows. That's gonna
Speaker 1: do it for us this morning, back this afternoon to
Speaker 1: tell you what is trending and we'll talk to you
Speaker 1: all then Bye bye. She drank a chop and pods