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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.

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Speaker 2: Hey, y'all.

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Speaker 1: So we are doing a mailbag episode as a promise.

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Speaker 1: But when Joey and Mike and myself sat down to record,

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Speaker 1: we realized that a lot of the conversations we were

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Speaker 1: having were sort of focused on one area, and that

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Speaker 1: is our careers, our backgrounds, how the podcast comes together.

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Speaker 1: So this is sort of a mailbag theme episode that

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Speaker 1: speaks to those issues. We'll have more mailbag episodes to come.

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Speaker 1: Thanks so much for listening, Mike, Joey. Happy almost new Year,

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Speaker 1: Thank you for being here, Thanks for having me.

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Speaker 2: Hey Bridgid, Yeah, happy New Year? Are happy almost a year?

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Speaker 3: I think at this point when this episode comes out,

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Speaker 3: it'll be the new year officially, but we are currently

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Speaker 3: in twenty twenty five a ready to leave twenty twenty five.

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Speaker 2: Oh my god, tell me about it.

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Speaker 1: We could do that thing where we pretend that we're

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Speaker 1: recording it the day of Yeah, like, oh, how's your

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Speaker 1: first few days of twenty twenty six going? Can you

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Speaker 1: believe that topical thing happened? We're all still reeling from

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Speaker 1: topical things. I can't believe he did that.

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Speaker 2: I was crazy.

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Speaker 4: Uh yeah, yeah, yeah, I was gonna visit that place,

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Speaker 4: but I guess that's out now.

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Speaker 2: There's actually a nuclear bomb currently headed towards our house

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Speaker 2: as we're recording this. Crazy what I don't know.

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Speaker 1: In the news cycle that we have now, Like we're

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Speaker 1: all joking, but genuinely, when I make up in the morning,

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Speaker 1: I don't even know what I'm gonna see.

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Speaker 2: I really I have stopped.

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Speaker 1: I used to think things used to be a lot

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Speaker 1: more predictable these days. I'm like, I don't even know

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Speaker 1: when the morning starts. I don't even know what is

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Speaker 1: gonna happen. So honestly, truly, it could be and this

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Speaker 1: where we're joking, but it could be anything.

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Speaker 4: Yeah, And we're just so desensitized to things, like I

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Speaker 4: was rem remembering how like remember a couple of years

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Speaker 4: ago the government said that there are aliens and we're

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Speaker 4: all like, yeah, well you know, yeah, we have like

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Speaker 4: bigger problems, Like we have a lot going.

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Speaker 2: On in our own lives right now. Alien Yeah, you

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Speaker 2: forgot about it. I forgot about it.

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Speaker 1: There is actually a documentary out right now called The

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Speaker 1: Age of Disclosure, which I started watching but I have

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Speaker 1: not finished. That claims to be you know, essentially an

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Speaker 1: inconvenient truth but about aliens. And it's like called the

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Speaker 1: military knows about this and all the information that we have,

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Speaker 1: and da da da. It's so funny to me that

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Speaker 1: it's come and gone barely a blip, barely a blit, and.

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Speaker 3: I have not an inconvenient truth about aliens. It's such

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Speaker 3: a funny sentence, even back to I'll be real, like

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Speaker 3: I keep my end of year traditions is all go

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Speaker 3: through and make my list of like things that I did,

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Speaker 3: like big moments, and I keep going back and being

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Speaker 3: like Charlie Kirk, washat this year not that long ago,

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Speaker 3: like two months ago, Like I feel like that happened

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Speaker 3: like five years ago at this point.

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Speaker 1: Uh wild how that was such a huge cultural moment

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Speaker 1: for like seventy two hours and now other than Erica

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Speaker 1: Kirk being a mainstay with pyrotechnics on stages all of that,

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Speaker 1: it almost never comes up.

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Speaker 2: It's like that came in went exactly.

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Speaker 4: Yeah. I I wonder if that's like as true for

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Speaker 4: them as it is for us, though, like my understanding

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Speaker 4: is that a lot of maga people got really mad

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Speaker 4: at Trump when he attacked Rob Reiner the day after

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Speaker 4: he was murdered and like specifically referenced the killing of

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Speaker 4: Charlie Kirk. And so yeah, I don't know. Like my

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Speaker 4: big enduring takeaway from that whole episode is how like

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Speaker 4: radically different the media bubbles we live in are, and

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Speaker 4: you know, like I've certainly moved on, but I think

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Speaker 4: they're still like deep in.

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Speaker 1: Well, in case anybody's to cancel me, I'm still mourning

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Speaker 1: Charlie Kirk.

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Speaker 2: Every day I light a candle in his honor.

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Speaker 1: I go to Starbucks and I say, give me the

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Speaker 1: Kirk because I'm a true patriot. So if you're looking

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Speaker 1: for somebody to cancel, it's producer Mike, because he's he's

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Speaker 1: over already, He's he's sufficiently mourned.

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Speaker 2: So what does that tell you?

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Speaker 1: I do think that you're onto something about the media bubbles,

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Speaker 1: because we were talking about how before Trump made his

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Speaker 1: comments about Rob Reiner, I saw popular right wing figures

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Speaker 1: saying do you see how no one is be searching

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Speaker 1: Rob Reiner in death? Dah da da da, And then

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Speaker 1: ten minutes later, Trump had that horrible tweet, and part

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Speaker 1: of me, you know, when people were surprised by Trump's

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Speaker 1: comments about that, part of me was like, do you

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Speaker 1: know this man?

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Speaker 2: Like there's the only information that you're getting about Trump?

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Speaker 1: Like what kind of media bubbles are you in that

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Speaker 1: the idea that Trump would be disrespectful of his enemy

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Speaker 1: even when his enemy was brutally murdered like that, Like

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Speaker 1: the next day, what world are you living in in

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Speaker 1: terms of your media bubble or algorithm where that will

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Speaker 1: be surprising information or not completely expected information.

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Speaker 4: I had the exact same response, and I think they

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Speaker 4: probably just don't see that stuff.

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Speaker 1: Well, it's actually I thought a good segue into our

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Speaker 1: mailbag episode, you know we I was thinking about this

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Speaker 1: before we got on the mic, and we've never done

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Speaker 1: a mailback episode before, So bear with us if it

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Speaker 1: seems like we're not so professional at this, because this

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Speaker 1: is our first time doing this format, and I was thinking,

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Speaker 1: why did I want to do this? Why was this

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Speaker 1: something that I had in my mind? Because we've been

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Speaker 1: doing this podcast. We start that we launched the show

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Speaker 1: in summer of twenty twenty, I think May of twenty twenty,

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Speaker 1: so we're coming up on we've been doing it over

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Speaker 1: five years. We're coming up on six years, and since

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Speaker 1: that time, I feel that we've learned. So I've learned

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Speaker 1: so much. I feel like we've heard so much from

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Speaker 1: our listeners, the audience. I've you know, when we first

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Speaker 1: started this, it was just me and our producer Toy Harrison,

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Speaker 1: and then Mike was more behind the scenes, and then

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Speaker 1: we gained Joey.

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Speaker 2: I feel like we really become a team.

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Speaker 1: So like, in addition to all the different shows and

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Speaker 1: stories and rabbit holes and tangents of the Internet that

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Speaker 1: we get to explore, I feel like we've all kind

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Speaker 1: of learned and grown a little bit together in this work.

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Speaker 2: I don't know. Maybe maybe this just sounds a little

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Speaker 2: sappy because it's the end of the year and I'm

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Speaker 2: having a margarita, But hey, what are you offering?

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Speaker 4: Yeah, maybe the real podcasts were the friends we made

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Speaker 4: along the way. Maybe maybe, Yeah, I'm with you. I

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Speaker 4: feel like I've learned a ton doing doing this podcast.

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Speaker 4: Getting to work on it, you know, got to know

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Speaker 4: more about you, bridget, got to know Joey and Tari,

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Speaker 4: learned a lot about podcastings or the business side, the

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Speaker 4: production side, and so much about just our digital landscape

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Speaker 4: and the information social ecosystem that we all live in

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Speaker 4: that is just so critical to like all areas of

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Speaker 4: our lives. Yeah, it's been. It's really been a fun,

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Speaker 4: interesting learning experience.

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Speaker 2: Yeah, agreed.

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Speaker 3: I mean, I got I'm kind of like the latest

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Speaker 3: addition to the show. Which is also funny because at

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Speaker 3: this point I've I think it's been three years that

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Speaker 3: I've been working on Yeah, that's crazy, I was because

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Speaker 3: I'm coming off four years okay, and yeah, I've been

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Speaker 3: working on the show for three years now, but kind

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Speaker 3: of saying, like I my journey has been, like I

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Speaker 3: came on originally as an editor kind of totally by chance,

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Speaker 3: because it was around Tari and I had connected she

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Speaker 3: was looking for more help for the shows right when

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Speaker 3: I came on as a full time producer at iHeart

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Speaker 3: got to know the show through editing and through you know,

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Speaker 3: hearing these stories each week.

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Speaker 2: And then about I think.

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Speaker 3: Two years ago now, Bridget had actually taught to me

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Speaker 3: about an episode that I did for Seffmun've Never Told You,

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Speaker 3: which is show that I will guest host every once

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Speaker 3: in a while, and it was sort of like but

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Speaker 3: even before that, I feel like this show to me,

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Speaker 3: like I kind of came into it and was like, I, yes,

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Speaker 3: like I love writing around feminist issues. I was always

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Speaker 3: somebody who was very into the Internet and very online,

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Speaker 3: but I never really thought of it as like that's tech,

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Speaker 3: that's writing about tech, and I, I don't know, I

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Speaker 3: guess this is now me also being a little a

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Speaker 3: little corny and half a glass of white wine. And

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Speaker 3: but uh, you know, I really do feel like this

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Speaker 3: show has sort of helped me like own in what

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Speaker 3: I like to report on and what I like to

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Speaker 3: talk about.

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Speaker 2: Like again, I always I love the Internet. I grew

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Speaker 2: up at the Internet.

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Speaker 3: I feel Bridgete we really bonded over like having very

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Speaker 3: similar experiences with that.

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Speaker 2: I also was always like, I'm not a tech person.

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Speaker 3: I'm not a like traditional science person and the lightest

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Speaker 3: the only class I've ever failed in my life was physics,

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Speaker 3: So I like I always was sort of like, I'm

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Speaker 3: not in the tech side.

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Speaker 2: That's too like, that's that's to whatever for me. I'm

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Speaker 2: more of like the social issues.

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Speaker 3: But but what it was, I feel like through through

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Speaker 3: like this show has kind of given me the confidence

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Speaker 3: to be like, yeah, no, I'm a tech reporter. I

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Speaker 3: work on issues like even yeah, yeah, like this is

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Speaker 3: an area that I am interested in. This is something

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Speaker 3: that like I've kind of decided I want to continue

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Speaker 3: like doing research in and stuff like that. And so yeah, anyways,

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Speaker 3: so thank you bridget So for for for starting this

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Speaker 3: whole show and starting you.

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Speaker 1: Know, I mean, I like, oh my god, You're I

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Speaker 1: really feel like you were the missing ingredient of the show.

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Speaker 1: Like you, I feel like your perspective I think really

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Speaker 1: informs the work that we do every day. You are

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Speaker 1: also in pockets of the Internet that I'm not personally into.

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Speaker 2: Like you have brought the gen Z voice. I brought

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Speaker 2: the gen Z voice already.

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Speaker 1: We joke about this, how the three of us. I'm

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Speaker 1: a millennial, Joey is gen Z? Mike, what do you?

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Speaker 1: What do you claim?

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Speaker 2: I don't. I don't want to put words in your mouth.

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Speaker 4: Well, I'm like right on the cusp of gen X

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Speaker 4: and millennial. I identify as Orion Trail generation.

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Speaker 2: Okay wait, I kind of feel that though, because I'm.

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Speaker 3: A little bit more on the gen Z side. But

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Speaker 3: I am like early gen Z. So I always thought

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Speaker 3: I was a millennial growing up. You're we will We'll

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Speaker 3: claim you. You're one of our Thank you.

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Speaker 2: Yeah, I grew I grew up with VHS tapes. There

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Speaker 2: you go.

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Speaker 3: I had a flip phone until I was fifteen, So

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Speaker 3: classic millennial shit.

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Speaker 1: If you ever wore a blazer or anything else business

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Speaker 1: casual that would have been appropriate in a job interview

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Speaker 1: to a nightclub welcome back.

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Speaker 3: I don't know about nightclub because I was again like

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Speaker 3: fourteen fifteen and that was a trend.

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Speaker 2: But I didn't have like homecoming, you know, yes, some

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Speaker 2: sort of a non professional setting.

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Speaker 1: If you if a blazer made an appearance in a

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Speaker 1: non professional setting, I say, spiritually, you're a millennial.

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Speaker 3: I do feel like listeners chime in if you want

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Speaker 3: this episode, because I do.

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Speaker 2: I have been like sort of soft pitching a person.

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Speaker 3: I think we should do an episode about the whole

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Speaker 3: like millennial nostalgia that's going on on like my TikTok

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Speaker 3: feed now, which is mostly gen Z people, people being

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Speaker 3: like I should have been in Williamsburg, like working for

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Speaker 3: BuzzFeed in twenty twelve and watch them girls and like

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Speaker 3: all of the I think it's fascinating because I'm like,

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Speaker 3: I think we all just are are feeling nostalgic about

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Speaker 3: when we were teenagers. Yeah, but but yeah, it does

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Speaker 3: make me wonder what are going to be like the

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Speaker 3: gen Z things.

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Speaker 1: Oh, I'm so curious. I was the old I mean

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Speaker 1: that you just described me. I brief I didn't live

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Speaker 1: in Williamsburg, but I did live in Bushwick, which I remember.

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Speaker 1: My my broker was like, it's East Williamsburg. I said, okay, ladies.

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Speaker 2: We're still doing that. They're still doing that. Yeah.

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Speaker 1: I worked in American apparel, which if you know what

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Speaker 1: that means, you know that you would know that you

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Speaker 1: know what I'm talking about, Like I I'll talk about this,

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Speaker 1: Oh my god, the American apparel in downtown Silver Spring, Maryland.

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Speaker 1: Like I yes, all of all that nostalgia that was

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Speaker 1: my life. Okay, So I want to start with this

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Speaker 1: first email from Lauren.

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Speaker 2: Thank you so much for writing in Lauren. Lauren writes, Hi,

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Speaker 2: Tango TI team.

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Speaker 1: I've been listening to the podcast since the beginning and

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Speaker 1: following bridges work for a while. I'm a big fan.

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Speaker 1: Thank you so much, Lauren. This question is for Bridget

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Speaker 1: and everyone who works on the show. I've heard you

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Speaker 1: talk a bit about how much you love podcasting and

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Speaker 1: I'm really interested in your process. What does it look

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Speaker 1: like when you sit down and put an episode together?

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Speaker 1: How do you conduct your research? I think as audience

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Speaker 1: members we don't always consider how much work goes into

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Speaker 1: an episode, and what we're hearing is the final product

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Speaker 1: of a huge amount of work. So I'm really interested

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Speaker 1: in the behind the scenes of it all. Thank you

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Speaker 1: for all that you do. Your show has been my

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Speaker 1: go to podcast for when I'm ready to get chores done,

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Speaker 1: as so much of the content makes me want to rage,

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Speaker 1: clean and a good way. Yes, I always find your

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Speaker 1: takes thoughtful, nuance, and time late. It challenges me to

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Speaker 1: think critically about tech and the media I consume every day.

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Speaker 1: I feel like this one of you write this email

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Speaker 1: to pretend to be because this is the email that

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Speaker 1: every podcaster wishes they would get, So thank you, Lauren.

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Speaker 1: This email is what I if I was having a

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Speaker 1: bad day, I would want one of you to write

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Speaker 1: an email like this and pretend to be a listener.

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Speaker 2: Yes, thank you, Lauren. I would bridge it if it

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Speaker 2: were me.

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Speaker 3: There would also be a note of the end that's like, Also,

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Speaker 3: Joey's really cool and they should be everywhere. I don't

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Speaker 3: know why they're not the biggest celebrity right now.

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Speaker 2: But yeah, thank you Laura. This is a great email.

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Speaker 1: Yeah, Mike, next time you write an email to make

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Speaker 1: Joey and I feel better, add that to the PS.

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Speaker 2: Just kidding, just kidding, Yeah.

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Speaker 1: I So the thing I like abut this email one

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Speaker 1: is that I also put on media to rage clean,

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Speaker 1: so we have that in common. I like this email

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Speaker 1: because it honors that putting the podcast together is actually

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Speaker 1: kind of a lot of work. It's worked that I love,

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Speaker 1: and it's worked that I am grateful and lucky to

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Speaker 1: be doing.

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Speaker 2: And it's worked that you will never hear me complaining

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Speaker 2: about on the mic.

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Speaker 1: Not to say that it's not you know, I have

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Speaker 1: times where I'm like, this is so much work, But

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Speaker 1: it's not energy that I bring to the show ever,

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Speaker 1: because truly, you know, it's a voluntary project and I'm

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Speaker 1: so lucky that they get to do it together and

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Speaker 1: all of that.

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Speaker 2: And then also I would say the.

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Speaker 1: Work that goes into putting together a show I do,

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Speaker 1: even even though it can be a lot to manage,

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Speaker 1: I do find it interesting.

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Speaker 2: I do. I do.

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Speaker 1: I am like a dog with a bone, where if

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Speaker 1: I just get an idea about something. Researching it is

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Speaker 1: sort of part of the part of the fun of it.

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Speaker 1: So I would say how episodes come together is generally

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Speaker 1: I start with some conversation that is happening, where like

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Speaker 1: every it's in the zeitgeist, right, it's you don't need

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Speaker 1: to you're not it's not a it's not a hidden

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Speaker 1: pocket of the Internet. It's a conversation everybody is having.

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Speaker 1: And then I'll try to say, like, well, what are

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Speaker 1: what are the parts of this conversation or the threads

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Speaker 1: or the nuance that is getting missed. And typically more

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Speaker 1: times than not, there is some aspects that reflects the

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Speaker 1: margin realized experience, and whether that's the experience of women,

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Speaker 1: of black folks, people of color, trans folks, queer folks, uh,

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Speaker 1: people with disabilities, indigenous folks, you.

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Speaker 2: Know, working folks. Right.

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Speaker 1: A lot of our media, tech media especially really centers

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Speaker 1: the idea of like CEOs and founders and Sam Altman

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Speaker 1: and Mark Zuckerberg, and we kind of forget about the

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Speaker 1: everyday person who was using technology, who is a working person,

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Speaker 1: not somebody who is wealthy, right, And so I try

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Speaker 1: to find the missed ways that identity is actually fueling

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Speaker 1: something and for me, a lot of times that jumps out,

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Speaker 1: but sometimes I have to like take a little bit

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Speaker 1: of time to think about it because you know, this

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Speaker 1: is gonna be a weird comparison. But if you've ever

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Speaker 1: seen that movie My Big Fat Greek Wedding where the

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Speaker 1: Greek dad is like, I can make it tell me

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Speaker 1: the Tell me any word and I can tell you

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Speaker 1: how it's actually a Greek word. I feel that way

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Speaker 1: about tech and internet stories. Tell me any tech or

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Speaker 1: internet story and I can tell you how it's actually

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Speaker 1: the story of like a marginalized person or a marginalized

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Speaker 1: experience or something like that.

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Speaker 3: I'm laughing at that, but like that really is by

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Speaker 3: the way, most stories, though, you can find that element

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Speaker 3: because it is.

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Speaker 2: That's the thing about working in issues.

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Speaker 3: Of like inequality of like gender races or whatever, is

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Speaker 3: there's all that's only gonna be rooted in whatever at.

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Speaker 2: The end of the day.

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Speaker 3: So yeah, this is similar to how I uh, that's

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Speaker 3: on a tangent, but I was My friends will make

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Speaker 3: fun of me because they're like every single time they'll

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Speaker 3: like go watch a movie together, you will like at

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Speaker 3: the end be like and here's why it actually was

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Speaker 3: a gay allegory, and I'm like, because everything is a

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Speaker 3: gay allegory.

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Speaker 2: Yeah, I love that. That's the best part of media jobs.

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Speaker 1: Side note, I did just get into a very long

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Speaker 1: back and forth on Reddit about the movie and book

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Speaker 1: American Psycho and the gay thing.

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Speaker 2: My God day, amigory.

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Speaker 1: Gay allegory, y'all gay allegory this year for the first time.

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Speaker 3: Finally, after I finally like actually sat down and watched

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Speaker 3: it and immediately was like, oh my god, yeah, that's likes.

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Speaker 2: This was written by a gay man, I can tell.

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Speaker 2: I ask.

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Speaker 1: Yeah, So once I have kind of gotten whatever the

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Speaker 1: identity thing that I that I want to sort of

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Speaker 1: like blow up and make the whole story, I kind

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Speaker 1: of have my marching orders from that point is the research.

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Speaker 1: And if I had to say, there was one thing

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Speaker 1: that people probably don't see on the show is how

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Speaker 1: much research goes into not just every episode, everything that

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Speaker 1: I say. I am the kind of person that like

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Speaker 1: I will there I could probably count on one hand

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Speaker 1: the amount of times that I've said something on the

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Speaker 1: show or I was not absolutely certain because I have

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Speaker 1: read no less than three articles about that thing. Sometimes

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Speaker 1: I'm put on the spot and I'll have to say, well,

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Speaker 1: in my opinion, da da da da. But for the

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Speaker 1: most part, every line that I have said is something

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Speaker 1: I have read and can confirm and have based on something.

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Speaker 2: And so I'm generally reading multiple like.

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Speaker 1: Long form articles or having interviews and conversations some of

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Speaker 1: which that don't even make it on the show, to

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Speaker 1: help flesh out, you know, the story that I'm trying

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Speaker 1: to tell in the episodes that you all hear that

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Speaker 1: have got like an interview I'm listening to. Basically, I'm

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Speaker 1: like finding the right person to speak to an issue.

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Speaker 1: I'm pre interviewing them. I'm I'm outlining, like where are

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Speaker 1: what the what's the conversation to go, but also sort

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Speaker 1: of trying to strategically leave room for the twists and

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Speaker 1: turns and where they're gonna take me. I've had many

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Speaker 1: an interview where from the beginning of that interview to

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Speaker 1: the end, I was I could not tell you where

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Speaker 1: we were going to go, so make leaving room for

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Speaker 1: that the editing process.

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Speaker 2: I don't even know if this is interesting to people

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Speaker 2: to hear this, this how the.

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Speaker 1: Sausage is made, But you know, I listen through every

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Speaker 1: interview multiple times just the raw audio, and you kind

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Speaker 1: of get an ear for it, right. You get an

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Speaker 1: ear for the beats of the story. You get an

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Speaker 1: ear for the things that are like, Okay, well this

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Speaker 1: can be cut. You get an ear for how to

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Speaker 1: prune this into a story that that you know isn't

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Speaker 1: just a good interview, but has a beginning, middle, and end.

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Speaker 1: Mike will tell you that when we first started the podcast,

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Speaker 1: I would probably spend just in terms of making edits

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Speaker 1: to audio, I probably would spend what.

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Speaker 2: Would you what do you say?

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Speaker 4: Oh, I mean, I'd be hard pressed to say what

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Speaker 4: is like editing versus like researching, But you you would

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Speaker 4: spend like tens of hours on every episode, which was

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Speaker 4: just like not sustainable, right, And yeah, you know it's

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Speaker 4: it's it's funny. I started this segment saying about, you know,

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Speaker 4: I got to I got to learn so much over

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Speaker 4: these years working on the show, And that's certainly true. Uh,

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Speaker 4: some additional things that I didn't mention that I've learned,

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Speaker 4: or like getting the skills of conducting an interview, the

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Speaker 4: skills of editing footage to tell a story, and then

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Speaker 4: the additional skill of doing all of that under like

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Speaker 4: a super tight deadline of you know, got to get

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Speaker 4: two episodes out per week, got to get it done.

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Speaker 4: You know, I came from an academic ish setting where

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Speaker 4: research projects would unfold over months or sometimes years. Right

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Speaker 4: there would just be like seemingly endless research, and then

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Speaker 4: writing a document would be a task that involved multiple

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Speaker 4: people over again, many weeks or months of revisions and

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Speaker 4: then ending up with a like a research article, which

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Speaker 4: is just a very different thing than the storytelling that

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Speaker 4: you're able to do. And and it's just been really

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Speaker 4: cool and fun and interesting to get exposure to those

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Speaker 4: skills and bridget you're like very good at it.

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Speaker 2: Let's take a quick break at our back.

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Speaker 1: So when we first got greenlit for the show, I

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Speaker 1: would spend a few days from soup to nuts at

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Speaker 1: the beginning, each episode was a few days of like

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Speaker 1: deep work, and I was so you remember, I was

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Speaker 1: so hung up on the editing, right, I was like,

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Speaker 1: the reason I want to do this show is because

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Speaker 1: I think that marginalized people deserve beautifully edited, beautifully story escaped,

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Speaker 1: like stories of our digital resilience and our digital selves

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Speaker 1: and lives. And you know, when I was pitching, I

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Speaker 1: would talk about how you know, if you listen to

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Speaker 1: podcasts like This American Life, or for me it was

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Speaker 1: a Starley Kine's Mystery Show, you get these beautifully layered,

439
00:21:46,680 --> 00:21:49,440
Speaker 1: beautifully thoughtfully edited stories.

440
00:21:49,480 --> 00:21:51,679
Speaker 2: And I was like, that's what that's what we deserve.

441
00:21:51,720 --> 00:21:55,119
Speaker 1: When people talk about internet stories for marginalized people, so

442
00:21:55,240 --> 00:21:57,679
Speaker 1: often they're just so hastily thrown together, and I was like,

443
00:21:57,720 --> 00:22:02,159
Speaker 1: I want to document our loving tributes to ourselves online. Well,

444
00:22:02,240 --> 00:22:04,800
Speaker 1: turns out that's a lot of freaking work. And it

445
00:22:04,840 --> 00:22:08,800
Speaker 1: was like, I don't know that the story. I feel

446
00:22:08,800 --> 00:22:11,800
Speaker 1: that the stories are good, and all of the editing

447
00:22:11,840 --> 00:22:13,959
Speaker 1: that I was bringing was important to me, but it

448
00:22:14,000 --> 00:22:15,520
Speaker 1: was sort of just icing.

449
00:22:15,960 --> 00:22:18,920
Speaker 2: And so now we're I. And also, when you are.

450
00:22:19,040 --> 00:22:21,480
Speaker 1: Doing work like that, you don't get to respond to

451
00:22:21,520 --> 00:22:24,399
Speaker 1: what's what's current, right, because if all your work is

452
00:22:24,440 --> 00:22:28,320
Speaker 1: made in advance in the can, when something really happens

453
00:22:28,320 --> 00:22:29,560
Speaker 1: and you're like, I want to speak to that, you

454
00:22:29,560 --> 00:22:30,760
Speaker 1: don't really have a way to do that. And so

455
00:22:30,800 --> 00:22:32,800
Speaker 1: I found myself kind of getting into a trap where

456
00:22:33,840 --> 00:22:36,680
Speaker 1: we were putting out content that I was like very

457
00:22:36,720 --> 00:22:38,520
Speaker 1: proud of, but it wasn't speaking to the moment.

458
00:22:38,920 --> 00:22:40,639
Speaker 2: Then we started doing the news round Up.

459
00:22:40,760 --> 00:22:43,520
Speaker 1: We got to hear from Mike and Joey and other

460
00:22:43,600 --> 00:22:46,679
Speaker 1: folks and who are on my radar and the tech landscape.

461
00:22:46,720 --> 00:22:48,440
Speaker 2: And I feel like that.

462
00:22:48,520 --> 00:22:52,480
Speaker 1: Really changed the game as well, because one it created

463
00:22:52,680 --> 00:22:55,880
Speaker 1: a space where I could speak a little bit more

464
00:22:55,880 --> 00:22:56,840
Speaker 1: off the cuff.

465
00:22:56,640 --> 00:22:57,840
Speaker 2: You know, when I'm interviewed.

466
00:22:57,880 --> 00:23:01,320
Speaker 1: When I'm interviewing somebody there interview, it's very important to

467
00:23:01,400 --> 00:23:03,720
Speaker 1: me that their interview is like take center stage and

468
00:23:03,840 --> 00:23:05,960
Speaker 1: is the main thing that you're hearing.

469
00:23:06,000 --> 00:23:07,320
Speaker 2: And so you don't hear a lot of me. And

470
00:23:07,359 --> 00:23:09,520
Speaker 2: people would say I like the show, but I don't

471
00:23:09,520 --> 00:23:11,520
Speaker 2: really feel like I hear Bridget or know who she is.

472
00:23:11,560 --> 00:23:13,719
Speaker 1: And the News round Up, I think it kind of

473
00:23:13,840 --> 00:23:16,679
Speaker 1: lowers the stakes a little bit and also gives a

474
00:23:16,760 --> 00:23:19,879
Speaker 1: chance to, you know, wrap up, like what are the

475
00:23:19,920 --> 00:23:22,600
Speaker 1: things that happened this week? And weirdly, I feel like

476
00:23:23,480 --> 00:23:26,400
Speaker 1: the News Roundup has become more of the podcast than

477
00:23:26,440 --> 00:23:27,440
Speaker 1: the interview episodes.

478
00:23:27,480 --> 00:23:29,840
Speaker 3: In some ways, we have been getting more listens on

479
00:23:29,880 --> 00:23:32,280
Speaker 3: the news us that we have just from the numbers

480
00:23:32,280 --> 00:23:33,280
Speaker 3: on the events.

481
00:23:33,359 --> 00:23:34,560
Speaker 2: Yeah. Yeah.

482
00:23:34,600 --> 00:23:37,600
Speaker 4: I will say though that when I see people on

483
00:23:37,840 --> 00:23:41,520
Speaker 4: like Blue Sky or something just randomly reference an episode,

484
00:23:42,040 --> 00:23:44,400
Speaker 4: they're usually referencing one of the interview episodes.

485
00:23:44,680 --> 00:23:49,560
Speaker 2: Huh yeah, well, listeners, tell us what you like. It

486
00:23:49,560 --> 00:23:50,880
Speaker 2: would actually be useful to know.

487
00:23:51,240 --> 00:23:54,880
Speaker 1: Like how people are engaging with this, So yeah, let

488
00:23:54,920 --> 00:23:58,040
Speaker 1: us know how that lands for you and Lauren. Thank

489
00:23:58,040 --> 00:24:00,399
Speaker 1: you so much for this email. I hope this answered

490
00:24:00,400 --> 00:24:01,720
Speaker 1: your question. I also hope that was interesting.

491
00:24:01,720 --> 00:24:05,800
Speaker 2: Wait do you want the post productions now? I'm I'm

492
00:24:05,880 --> 00:24:10,520
Speaker 2: sorry post production listeners. This is what always happens is

493
00:24:10,520 --> 00:24:11,600
Speaker 2: that I'll get an email.

494
00:24:11,680 --> 00:24:14,760
Speaker 3: This is a perfect this is a perfect tangent because

495
00:24:14,840 --> 00:24:18,280
Speaker 3: what happens is Bridget does all of that, and then

496
00:24:19,000 --> 00:24:24,200
Speaker 3: firstday night, somewhere between ten pm and three.

497
00:24:24,000 --> 00:24:30,040
Speaker 2: Am, Yes, I will get email from Bridget. I'm I

498
00:24:30,080 --> 00:24:31,600
Speaker 2: can't step and this is so real.

499
00:24:31,720 --> 00:24:35,560
Speaker 3: This is absolutely fucking I can't fault you because again

500
00:24:35,960 --> 00:24:38,280
Speaker 3: we've talked about this where I'm like, Bridget, I get it.

501
00:24:38,320 --> 00:24:41,000
Speaker 3: I'm also somebody that I'm either awake at three am

502
00:24:41,240 --> 00:24:45,600
Speaker 3: or I fell asleep at nine pm, and I'm whatever. So, listeners,

503
00:24:45,640 --> 00:24:49,480
Speaker 3: if you're wondering why Friday episodes now since they've switched

504
00:24:49,480 --> 00:24:53,280
Speaker 3: to news roundups suddenly come up come out like really

505
00:24:53,359 --> 00:24:56,440
Speaker 3: late at night, it's because and this isn't And I'm

506
00:24:56,480 --> 00:24:58,639
Speaker 3: not Bridget. I'm not saying this is a fault.

507
00:24:58,640 --> 00:24:59,160
Speaker 2: It is a heart.

508
00:24:59,240 --> 00:25:00,600
Speaker 3: It is like, you know what, that's the thing with

509
00:25:00,920 --> 00:25:03,240
Speaker 3: if you want to like with love, if you but

510
00:25:03,280 --> 00:25:04,840
Speaker 3: that's it is the thing of you, if you want

511
00:25:04,920 --> 00:25:08,120
Speaker 3: stuff that is like responding to the immediate stories sometimes.

512
00:25:07,920 --> 00:25:09,560
Speaker 2: So there's a little bit of like there's gonna be

513
00:25:09,600 --> 00:25:10,360
Speaker 2: some turn around time.

514
00:25:11,440 --> 00:25:16,879
Speaker 5: But yeah, I guess like real quick for me to

515
00:25:16,960 --> 00:25:19,040
Speaker 5: kind of what you were saying before, Bridget, Like people

516
00:25:19,040 --> 00:25:20,119
Speaker 5: come up to me all the time they're like, I

517
00:25:20,160 --> 00:25:21,920
Speaker 5: love podcasts, like what is your daily job?

518
00:25:22,119 --> 00:25:23,320
Speaker 2: Like what does it look like?

519
00:25:23,400 --> 00:25:26,080
Speaker 3: And I'm like, so, you don't know the amount of

520
00:25:26,080 --> 00:25:27,880
Speaker 3: work that has to go into even just a talk

521
00:25:27,920 --> 00:25:30,040
Speaker 3: show where it's because because this the way that the

522
00:25:30,320 --> 00:25:32,800
Speaker 3: I I took over editing the Friday episodes when I

523
00:25:32,800 --> 00:25:36,480
Speaker 3: originally came out of the show, which originally were similar

524
00:25:36,480 --> 00:25:38,560
Speaker 3: to the Shuesday episodes, where it was an interview and

525
00:25:38,600 --> 00:25:40,800
Speaker 3: a story, and then at some point we switched over

526
00:25:40,840 --> 00:25:45,879
Speaker 3: to the news round uh format. But for even something

527
00:25:45,920 --> 00:25:47,520
Speaker 3: like the news round up where it's just two people

528
00:25:47,520 --> 00:25:48,680
Speaker 3: talking back and forth, like.

529
00:25:49,440 --> 00:25:50,400
Speaker 2: I get the files.

530
00:25:51,160 --> 00:25:54,119
Speaker 3: I did earlier say that I failed the one physics

531
00:25:54,160 --> 00:25:55,120
Speaker 3: class average a take.

532
00:25:55,200 --> 00:25:57,400
Speaker 2: But technically my I am an engineer.

533
00:25:58,119 --> 00:26:01,159
Speaker 3: Uh so there is an audio engineering aspect I have

534
00:26:01,200 --> 00:26:05,000
Speaker 3: to like put all of these files into. We use

535
00:26:05,040 --> 00:26:08,359
Speaker 3: a platform called Isotope mainly, and then there's we use

536
00:26:08,400 --> 00:26:13,399
Speaker 3: the Adobe platforms here at iHeart not everybody does, but

537
00:26:13,480 --> 00:26:16,919
Speaker 3: I do and most of us too. So there's like

538
00:26:17,000 --> 00:26:19,600
Speaker 3: certain kind of programs I run it through and I

539
00:26:19,640 --> 00:26:23,000
Speaker 3: have to add certain filters depending on how the audio

540
00:26:23,080 --> 00:26:25,800
Speaker 3: sounds that day. This is the very This is where

541
00:26:25,800 --> 00:26:28,600
Speaker 3: I get to be like guys, technically I'm an engineer.

542
00:26:30,119 --> 00:26:32,159
Speaker 2: And then eventually the file is.

543
00:26:32,160 --> 00:26:35,359
Speaker 3: Done, I will then put it in Adobe Audition, which

544
00:26:35,400 --> 00:26:37,920
Speaker 3: is the if you are familiar with audio at all

545
00:26:38,040 --> 00:26:39,920
Speaker 3: or with familiar with the Adobe Suite.

546
00:26:40,080 --> 00:26:41,560
Speaker 2: That's an editing software.

547
00:26:44,680 --> 00:26:46,520
Speaker 3: Going back to how you were talking about like wanting

548
00:26:46,560 --> 00:26:49,600
Speaker 3: this to sound more polished and the editing side of things.

549
00:26:50,200 --> 00:26:53,160
Speaker 3: I'm the one whenever there's like a mistake that happens

550
00:26:54,280 --> 00:26:57,240
Speaker 3: and Bridges like, never mind, I couldn't dole.

551
00:26:57,119 --> 00:26:58,399
Speaker 2: Behind the beside these scenes.

552
00:26:58,400 --> 00:27:00,520
Speaker 3: Behind the scenes, bridge will like literally do like a

553
00:27:00,560 --> 00:27:03,439
Speaker 3: beep sound like She'll be like beep, and then I'll

554
00:27:03,520 --> 00:27:07,240
Speaker 3: have to edit out I'm saying this like, oh my god,

555
00:27:07,280 --> 00:27:08,879
Speaker 3: I have to do it. Meanwhile, I'm like, this is

556
00:27:08,960 --> 00:27:11,119
Speaker 3: my job that I worked very hard to get and

557
00:27:11,240 --> 00:27:13,240
Speaker 3: like enjoy doing both like same.

558
00:27:13,119 --> 00:27:14,520
Speaker 2: I'm like, I just say what you are saying where

559
00:27:14,520 --> 00:27:16,359
Speaker 2: I'm like, I'm not like, I'm like, I can't really complain.

560
00:27:16,440 --> 00:27:17,280
Speaker 2: I do love what I do.

561
00:27:18,400 --> 00:27:20,480
Speaker 3: But Bridgie, Yeah, Bridgitte will be like if there's a

562
00:27:20,520 --> 00:27:22,080
Speaker 3: segment that she's like, never mind, I want to say

563
00:27:22,119 --> 00:27:25,040
Speaker 3: pre say that, She'll be like beep and then re yeah,

564
00:27:25,080 --> 00:27:27,920
Speaker 3: there we go. Uh you do it better than I whatever,

565
00:27:28,040 --> 00:27:30,119
Speaker 3: because I'm the one editing myself, but I have to

566
00:27:30,119 --> 00:27:31,639
Speaker 3: be on air, so I always will just be like,

567
00:27:32,800 --> 00:27:34,600
Speaker 3: that's not what I wanted to say, And that's my

568
00:27:34,960 --> 00:27:37,560
Speaker 3: indication to myself that I'm like, I know, I wanted

569
00:27:37,560 --> 00:27:38,600
Speaker 3: to ask what is it?

570
00:27:38,760 --> 00:27:42,359
Speaker 2: What is it like? So, Joey, is it a weird

571
00:27:42,480 --> 00:27:43,520
Speaker 2: rare position.

572
00:27:43,200 --> 00:27:46,920
Speaker 1: Where they are both a speaker like they're a host

573
00:27:47,040 --> 00:27:49,440
Speaker 1: like they're speaking on the show, but also the one

574
00:27:49,440 --> 00:27:52,720
Speaker 1: who is editing, so editing themselves.

575
00:27:53,560 --> 00:27:58,080
Speaker 2: Yeah, what is that? Like? Well, so I guess editing

576
00:27:58,119 --> 00:27:59,760
Speaker 2: your own voice is hard, guys.

577
00:28:00,000 --> 00:28:05,080
Speaker 3: It is a weird like ego death experience that I

578
00:28:05,160 --> 00:28:09,040
Speaker 3: never really thought was gonna be Anyways, sometimes I'll like

579
00:28:09,119 --> 00:28:12,200
Speaker 3: finish the recording, go and like scream for a couple

580
00:28:12,240 --> 00:28:14,600
Speaker 3: of minutes, and then like come back here and upload

581
00:28:14,640 --> 00:28:17,199
Speaker 3: it and start editing, and then immediately we'll be like,

582
00:28:17,320 --> 00:28:20,720
Speaker 3: nobody talked to me for two hours. I just edited

583
00:28:20,720 --> 00:28:26,000
Speaker 3: my own voice for like five hours straight. I want

584
00:28:26,040 --> 00:28:29,600
Speaker 3: to just pretend I don't know. I will say I've

585
00:28:29,680 --> 00:28:33,239
Speaker 3: been a performer my whole life. I've been like, like

586
00:28:33,320 --> 00:28:34,800
Speaker 3: I we've talked about this before.

587
00:28:34,920 --> 00:28:36,560
Speaker 2: I was a theater kid back in the day. I

588
00:28:36,760 --> 00:28:39,720
Speaker 2: was like I was an actor for a little bit.

589
00:28:39,720 --> 00:28:41,840
Speaker 3: I have done all these different like broadcast things where

590
00:28:41,840 --> 00:28:43,400
Speaker 3: I'm like, I'm used to hearing my own voice.

591
00:28:43,400 --> 00:28:44,600
Speaker 2: I kind of had to get over that.

592
00:28:45,800 --> 00:28:49,160
Speaker 3: It also sucks, like I'm not gonna lie like it is.

593
00:28:49,360 --> 00:28:51,200
Speaker 3: I feel like I'm constantly and I'm just like, why

594
00:28:51,280 --> 00:28:52,320
Speaker 3: the why did I say that?

595
00:28:53,320 --> 00:28:57,320
Speaker 2: I don't know why? Uh, but yeah, I try my best.

596
00:28:57,360 --> 00:28:59,640
Speaker 3: That The nice thing about editing your own voice, though,

597
00:28:59,680 --> 00:29:01,040
Speaker 3: is then you get to kind of be your own

598
00:29:01,160 --> 00:29:03,640
Speaker 3: like self editor, where if I like, there definitely have

599
00:29:03,760 --> 00:29:06,640
Speaker 3: been episodes where like I've gone in a whole tangent

600
00:29:06,680 --> 00:29:07,600
Speaker 3: and then listened back.

601
00:29:07,480 --> 00:29:10,600
Speaker 2: And been like that was stupid. I'm taking that all out.

602
00:29:11,120 --> 00:29:12,200
Speaker 2: My favorite thing.

603
00:29:12,120 --> 00:29:15,040
Speaker 1: Is when Mike and I do an episode, we send

604
00:29:15,040 --> 00:29:20,160
Speaker 1: it to Joey and Joey is like, hey, let's let's

605
00:29:20,160 --> 00:29:20,720
Speaker 1: just take us out.

606
00:29:20,760 --> 00:29:23,320
Speaker 3: Yeah, it's funny because we've never actually got to talk about.

607
00:29:23,080 --> 00:29:23,760
Speaker 2: This space and face.

608
00:29:23,920 --> 00:29:25,920
Speaker 3: But sometimes it does reach the point because again, like

609
00:29:26,040 --> 00:29:27,400
Speaker 3: usually when I'm in an editing.

610
00:29:27,240 --> 00:29:30,000
Speaker 2: Session, it's like four hours straight, five hours straight and.

611
00:29:30,040 --> 00:29:32,240
Speaker 3: Be just listening to this, and sometimes I do feel

612
00:29:32,280 --> 00:29:33,920
Speaker 3: kind of bad because bridge in Michael get an email

613
00:29:34,000 --> 00:29:36,360
Speaker 3: for me that's like, Hi, I know what you were

614
00:29:36,400 --> 00:29:38,240
Speaker 3: trying to say here, but that's not when it came

615
00:29:38,320 --> 00:29:40,800
Speaker 3: up as it sounded really bad, I just cut it out.

616
00:29:41,000 --> 00:29:41,920
Speaker 2: No, I am agree.

617
00:29:42,080 --> 00:29:42,920
Speaker 4: I appreciate it.

618
00:29:43,040 --> 00:29:46,400
Speaker 1: You have saved us probably from you, you've saved us

619
00:29:46,440 --> 00:29:49,520
Speaker 1: from we don't even know the stuff that you've saved us.

620
00:29:49,480 --> 00:29:52,040
Speaker 3: But I believe, like I'll email you guys too when

621
00:29:52,040 --> 00:29:54,080
Speaker 3: I'm finished with mine and I'm like, I did my

622
00:29:54,120 --> 00:29:57,640
Speaker 3: best to make myself nap sound stupid. But also if

623
00:29:57,680 --> 00:29:59,760
Speaker 3: you listen to this and you're like, Joey, why the

624
00:29:59,760 --> 00:30:02,480
Speaker 3: fuck did you say that? Which just happened a couple

625
00:30:02,520 --> 00:30:04,520
Speaker 3: of times, and you know what, I'm great, Flip Bridget

626
00:30:04,600 --> 00:30:06,240
Speaker 3: hasn't said that said that to me in the email.

627
00:30:06,320 --> 00:30:10,440
Speaker 3: That's me paraphrasing, but it's been much nicer. It's been

628
00:30:10,480 --> 00:30:13,160
Speaker 3: more of a like, I know what you're trying to say,

629
00:30:13,200 --> 00:30:15,360
Speaker 3: but I don't know if that's it and anyway, but

630
00:30:15,400 --> 00:30:17,720
Speaker 3: I'm like, but you need somebody to listen back and

631
00:30:17,760 --> 00:30:20,880
Speaker 3: tell you, like, hey, the thing you're I get what

632
00:30:20,920 --> 00:30:22,520
Speaker 3: you're trying to say, but that's not coming across.

633
00:30:22,600 --> 00:30:25,400
Speaker 2: Let's just let's just cut this out. Yeah.

634
00:30:25,520 --> 00:30:28,640
Speaker 1: I once when I was first working as a podcaster,

635
00:30:29,320 --> 00:30:32,880
Speaker 1: so we had done an episode early early on, it

636
00:30:32,960 --> 00:30:35,280
Speaker 1: might have been my second or third time even like

637
00:30:35,520 --> 00:30:38,560
Speaker 1: doing a podcast where I was on the mic and

638
00:30:38,600 --> 00:30:41,640
Speaker 1: she was like, I don't think we should run this

639
00:30:41,800 --> 00:30:47,520
Speaker 1: because Bridget, you sound like a fucking like what did

640
00:30:47,560 --> 00:30:51,479
Speaker 1: she say? She was like, you sound like Valerie Sol honest,

641
00:30:51,560 --> 00:30:53,440
Speaker 1: like you're gonna go start taking this oh oh my

642
00:30:53,480 --> 00:30:54,440
Speaker 1: god men.

643
00:30:54,920 --> 00:30:57,640
Speaker 2: And I listened back and I was like, I sound insane?

644
00:30:58,080 --> 00:30:59,479
Speaker 2: Is this what I said? Like?

645
00:30:59,680 --> 00:31:02,080
Speaker 1: You you could not I you could have told me

646
00:31:02,160 --> 00:31:04,920
Speaker 1: that they had done they had done an AI vocal

647
00:31:04,960 --> 00:31:07,680
Speaker 1: clone of my voice because I was on such a rant,

648
00:31:07,840 --> 00:31:10,560
Speaker 1: but in the booth it felt natural and it felt normal.

649
00:31:10,720 --> 00:31:14,440
Speaker 1: But listening back, you know when you're when you're cortisol,

650
00:31:14,520 --> 00:31:16,720
Speaker 1: when your cortisol has gone down and you're no longer

651
00:31:16,760 --> 00:31:19,320
Speaker 1: in the moment of like ranting and ranting, I was like,

652
00:31:19,480 --> 00:31:23,440
Speaker 1: I sound insane. It's really sounds like she really did

653
00:31:23,560 --> 00:31:26,080
Speaker 1: need the biggest solid by saying, don't worry, this is

654
00:31:26,120 --> 00:31:27,000
Speaker 1: going in the vault.

655
00:31:32,920 --> 00:31:33,080
Speaker 3: More.

656
00:31:33,080 --> 00:31:50,400
Speaker 1: After a quick break, let's get right back into it.

657
00:31:50,520 --> 00:31:53,400
Speaker 1: Seeing as though we all have kind of come from

658
00:31:53,520 --> 00:31:57,200
Speaker 1: different professional backgrounds to do this work, I was surprised

659
00:31:57,200 --> 00:31:59,280
Speaker 1: that we got so many emails from listeners who were

660
00:31:59,280 --> 00:32:03,120
Speaker 1: interested in sort of our career trajectories and the idea

661
00:32:03,160 --> 00:32:05,440
Speaker 1: of like making career changes and how we came to

662
00:32:05,520 --> 00:32:08,080
Speaker 1: podcasting in the first place. We got an email from

663
00:32:08,160 --> 00:32:10,600
Speaker 1: Chase that says, I hope you guys are doing well

664
00:32:10,640 --> 00:32:13,040
Speaker 1: and taking time for yourselves during this crazy time. My

665
00:32:13,120 --> 00:32:14,960
Speaker 1: name is Chase. I'm twenty four. I've been listening to

666
00:32:15,000 --> 00:32:17,360
Speaker 1: your podcast for a few months now. I enjoy it

667
00:32:17,400 --> 00:32:19,040
Speaker 1: and I love hearing your takes on all things tech

668
00:32:19,080 --> 00:32:21,720
Speaker 1: media and society. You both are so insightful and I

669
00:32:21,720 --> 00:32:23,920
Speaker 1: appreciate your work so much, especially during this time of

670
00:32:23,920 --> 00:32:26,640
Speaker 1: misinformation and the lack of integrity and mainstream journalism. So

671
00:32:26,680 --> 00:32:28,600
Speaker 1: I said that all to say thanks for the work

672
00:32:28,640 --> 00:32:28,880
Speaker 1: that you do.

673
00:32:28,920 --> 00:32:30,360
Speaker 2: It's really important. Okay.

674
00:32:30,400 --> 00:32:32,520
Speaker 1: My question is for Bridget as someone who has gone

675
00:32:32,600 --> 00:32:34,920
Speaker 1: down a non traditional career path. How did you grapple

676
00:32:34,960 --> 00:32:37,400
Speaker 1: with this? What was your north star kept you motivated?

677
00:32:37,400 --> 00:32:39,479
Speaker 1: And how did you turn your passion into a career.

678
00:32:39,800 --> 00:32:41,720
Speaker 1: For context, as I said, I'm twenty four, I'm going

679
00:32:41,760 --> 00:32:42,920
Speaker 1: to think of trying to figure out what to do

680
00:32:42,960 --> 00:32:45,040
Speaker 1: with my life while staying too true to myself and

681
00:32:45,120 --> 00:32:48,239
Speaker 1: my passions. Thanks Chase. I love this email. Thank you

682
00:32:48,280 --> 00:32:52,239
Speaker 1: so much Chase, and it's written to me. But I

683
00:32:52,320 --> 00:32:55,160
Speaker 1: know that we've all had I don't know.

684
00:32:55,200 --> 00:32:56,640
Speaker 2: Interesting career paths.

685
00:32:56,920 --> 00:33:01,120
Speaker 1: My career path has been very Caddy Wampus, my late

686
00:33:01,160 --> 00:33:03,760
Speaker 1: father or God rest his soul, used to say that

687
00:33:03,800 --> 00:33:08,160
Speaker 1: when I was in college, because I majored, I double

688
00:33:08,240 --> 00:33:11,440
Speaker 1: majored in English literature and Women's studies, and he would

689
00:33:11,480 --> 00:33:14,360
Speaker 1: tell people, this is my daughter, she is majoring in

690
00:33:14,400 --> 00:33:15,440
Speaker 1: future unemployment.

691
00:33:17,720 --> 00:33:19,480
Speaker 2: Lovingly, that was his joke.

692
00:33:19,840 --> 00:33:22,000
Speaker 1: He used to beg me to say like, Oh, please

693
00:33:22,000 --> 00:33:26,680
Speaker 1: take a minor in business administration or chemistry or something.

694
00:33:27,320 --> 00:33:29,600
Speaker 2: So I went to undergrite a East Carolina University.

695
00:33:30,240 --> 00:33:33,400
Speaker 1: I kind of had a couple of different majors dance performance,

696
00:33:33,400 --> 00:33:35,560
Speaker 1: which again my dad was not thrilled about, because I

697
00:33:36,120 --> 00:33:38,960
Speaker 1: loved dance, and I loved kind of the intersection of

698
00:33:39,000 --> 00:33:43,840
Speaker 1: theater and dance, and I anything involving physicality was my thing,

699
00:33:43,920 --> 00:33:48,320
Speaker 1: and so I did like modeling and portrait modeling and dance,

700
00:33:48,360 --> 00:33:50,600
Speaker 1: and I thought I was going to have a careers

701
00:33:50,600 --> 00:33:52,000
Speaker 1: that I don't know how you would you how you

702
00:33:52,000 --> 00:33:55,680
Speaker 1: didn't say I thought I would thought I thought I

703
00:33:55,680 --> 00:33:58,680
Speaker 1: would be happiest having some kind of a physical career

704
00:33:58,720 --> 00:34:01,720
Speaker 1: where my physical self, my physical body and presentation was

705
00:34:01,840 --> 00:34:04,320
Speaker 1: part of how I how I made my money right.

706
00:34:05,640 --> 00:34:08,879
Speaker 2: A performance career, A performance career, I feel like, yeah,

707
00:34:09,000 --> 00:34:11,080
Speaker 2: that's the word. I'm looking for you too, Joey.

708
00:34:11,200 --> 00:34:13,280
Speaker 3: I also, yeah, I was gonna say. I was talking like, Bridget,

709
00:34:13,280 --> 00:34:15,160
Speaker 3: what do you We've never talked about this before. I

710
00:34:15,160 --> 00:34:18,799
Speaker 3: didn't know you were a dancer too, So I also

711
00:34:18,880 --> 00:34:24,040
Speaker 3: kind of came I'm just ironically also from a performance background.

712
00:34:24,080 --> 00:34:26,680
Speaker 2: But I laughed a little bit earlier I didn't end

713
00:34:26,800 --> 00:34:28,120
Speaker 2: up studying it in college.

714
00:34:28,360 --> 00:34:30,759
Speaker 1: It's funny because I've talked to so many people that

715
00:34:30,840 --> 00:34:35,120
Speaker 1: come from a like it's like a modern dance or

716
00:34:35,160 --> 00:34:38,360
Speaker 1: a theater or performance background who now do tech and

717
00:34:38,440 --> 00:34:39,000
Speaker 1: media work.

718
00:34:39,200 --> 00:34:40,560
Speaker 2: There's like an intersection there.

719
00:34:40,680 --> 00:34:43,920
Speaker 1: Producer Mike and I, but just in Barcelona interviewing someone

720
00:34:44,040 --> 00:34:47,160
Speaker 1: who is like a digital rights activist now and part

721
00:34:47,200 --> 00:34:51,280
Speaker 1: of her work brings in her background studying performance and

722
00:34:51,520 --> 00:34:52,600
Speaker 1: what she calls like the.

723
00:34:52,480 --> 00:34:54,880
Speaker 2: Theater of the absurd, the theater of protest.

724
00:34:54,520 --> 00:34:59,239
Speaker 1: And her work is all about using data to make

725
00:34:59,320 --> 00:35:03,520
Speaker 1: up kind of a public spectacle of embarrassment for people

726
00:35:03,560 --> 00:35:06,560
Speaker 1: in power, and that is so grounded in her work

727
00:35:06,600 --> 00:35:09,239
Speaker 1: as a theater professional. And so I do think there's

728
00:35:09,239 --> 00:35:11,640
Speaker 1: some sort of intersection points between these two things.

729
00:35:12,520 --> 00:35:14,120
Speaker 2: Yeah, and so I you.

730
00:35:14,080 --> 00:35:17,759
Speaker 1: Know, when college, I was a little miss on campus, right,

731
00:35:17,840 --> 00:35:19,840
Speaker 1: I this this is I I've said this before. I

732
00:35:19,840 --> 00:35:21,200
Speaker 1: don't know if I said it on the podcast, but

733
00:35:21,800 --> 00:35:24,200
Speaker 1: I wrote, I had my own column in the paper,

734
00:35:24,320 --> 00:35:26,440
Speaker 1: I had a zine. I was a DJ on the

735
00:35:26,520 --> 00:35:31,040
Speaker 1: radio on our college radio station, WZMB. I was DJ Coldslaw,

736
00:35:32,760 --> 00:35:35,279
Speaker 1: which is a name. It's a it's a it's a

737
00:35:35,280 --> 00:35:35,919
Speaker 1: goofy name.

738
00:35:36,040 --> 00:35:37,279
Speaker 2: It's I got it.

739
00:35:37,200 --> 00:35:42,120
Speaker 1: From the graphic novel ghost World by Daniel Close. The

740
00:35:42,280 --> 00:35:45,160
Speaker 1: main character of that graphic novel was a girl called

741
00:35:45,280 --> 00:35:48,640
Speaker 1: Enid Coleslaw, who I felt was my like spiritual twin,

742
00:35:48,760 --> 00:35:49,680
Speaker 1: and so that's why.

743
00:35:49,520 --> 00:35:50,480
Speaker 2: I was DJ Coleslaw.

744
00:35:51,000 --> 00:35:53,400
Speaker 1: And there was one day a month on campus where

745
00:35:53,680 --> 00:35:56,080
Speaker 1: my column came out in the paper. You could hear

746
00:35:56,160 --> 00:35:59,000
Speaker 1: me on the college radio station, you know, you could

747
00:35:59,000 --> 00:36:02,880
Speaker 1: get the zine. Basically, my opinions were coming at you

748
00:36:03,080 --> 00:36:06,160
Speaker 1: from land, the sky and air right.

749
00:36:06,280 --> 00:36:09,160
Speaker 2: There was no escaping my voice if you were on campus.

750
00:36:09,680 --> 00:36:11,600
Speaker 2: And yeah, I guess.

751
00:36:11,520 --> 00:36:16,720
Speaker 1: That really was my north star, you know, just being

752
00:36:16,800 --> 00:36:21,360
Speaker 1: somebody who had something to say. I mean, it sounds

753
00:36:21,400 --> 00:36:24,560
Speaker 1: so cheesy, but I feel like every aspect of my

754
00:36:24,800 --> 00:36:27,319
Speaker 1: career and my passions of my life have come back

755
00:36:27,360 --> 00:36:32,280
Speaker 1: to the importance of self expression, the importance of the truth.

756
00:36:33,719 --> 00:36:37,399
Speaker 1: I don't want to get too personal, but I grew

757
00:36:37,480 --> 00:36:42,640
Speaker 1: up in a household where it was sometimes difficult to

758
00:36:42,680 --> 00:36:46,759
Speaker 1: express yourself, and it was sometimes difficult to say the

759
00:36:46,840 --> 00:36:48,920
Speaker 1: truth and really say it with conviction and say what

760
00:36:48,960 --> 00:36:51,000
Speaker 1: you meant. There was a there was a sometimes there

761
00:36:51,040 --> 00:36:54,920
Speaker 1: was a cost, or a penalty attached to saying something

762
00:36:54,960 --> 00:36:57,640
Speaker 1: and saying it true, like like saying something that carried

763
00:36:57,640 --> 00:37:00,600
Speaker 1: emotional truth. And so I think that today, when you

764
00:37:00,640 --> 00:37:04,520
Speaker 1: say the truth, the truth always finds an audience, even

765
00:37:04,560 --> 00:37:08,400
Speaker 1: when we're living in immedia climate where lies abound, Right

766
00:37:08,520 --> 00:37:10,520
Speaker 1: Like when when when you live in a media climate

767
00:37:10,520 --> 00:37:12,919
Speaker 1: where lies are everywhere and lies are cheap, and lies

768
00:37:12,920 --> 00:37:14,759
Speaker 1: are fast, and lies are easy to produce and lies

769
00:37:14,760 --> 00:37:17,719
Speaker 1: are incentivized, truth is what cuts cuts through. And so

770
00:37:17,800 --> 00:37:20,040
Speaker 1: I think that's really been the north star of my career.

771
00:37:20,880 --> 00:37:25,359
Speaker 1: I had a disastrous stint in graduate school. I went

772
00:37:25,400 --> 00:37:28,480
Speaker 1: to University of Maryland. I was accepted into their m a.

773
00:37:28,600 --> 00:37:32,760
Speaker 1: pH d program, and y'all, I was the dumbest person

774
00:37:32,760 --> 00:37:34,759
Speaker 1: in my fucking PhD program. I was like the I

775
00:37:35,239 --> 00:37:40,240
Speaker 1: like just could not get it together. I I januine,

776
00:37:40,239 --> 00:37:41,040
Speaker 1: I januine I Like.

777
00:37:41,080 --> 00:37:42,560
Speaker 2: I would have nights where I would say, like, oh

778
00:37:42,560 --> 00:37:43,319
Speaker 2: what am I doing here?

779
00:37:43,320 --> 00:37:44,960
Speaker 1: I would I would be up at night being like

780
00:37:45,120 --> 00:37:48,799
Speaker 1: this is not But also it was very important to

781
00:37:48,880 --> 00:37:52,360
Speaker 1: my parents and my family in general that I get

782
00:37:52,440 --> 00:37:55,480
Speaker 1: an advanced degree. I am I am the least educated

783
00:37:55,520 --> 00:38:00,719
Speaker 1: person in my family. And yeah, I I I mean

784
00:38:01,239 --> 00:38:05,240
Speaker 1: I say this Yeah, I am the least educated person

785
00:38:05,239 --> 00:38:10,719
Speaker 1: in my family. Uh and uh, it's just funny because

786
00:38:11,680 --> 00:38:14,080
Speaker 1: I in a million years, never thought that the career

787
00:38:14,239 --> 00:38:16,480
Speaker 1: that I am in would be where I was. And

788
00:38:16,760 --> 00:38:20,000
Speaker 1: I gotta say, I am so grateful every day that

789
00:38:20,080 --> 00:38:22,960
Speaker 1: I had the guts to leave my graduate program, because.

790
00:38:22,800 --> 00:38:24,200
Speaker 2: If I was still in that there's a verse.

791
00:38:24,320 --> 00:38:26,240
Speaker 1: I know people who are still in that grad program

792
00:38:26,280 --> 00:38:29,400
Speaker 1: and I dropped out like fifteen years ago, right like

793
00:38:29,600 --> 00:38:32,799
Speaker 1: it is for people who have PhDs. Mike is one

794
00:38:32,840 --> 00:38:35,560
Speaker 1: of them. Genuinely, I do not know how you did it.

795
00:38:36,040 --> 00:38:41,360
Speaker 1: The fortitude that it takes I do not have. Yeah,

796
00:38:41,400 --> 00:38:42,399
Speaker 1: so I guess, So I guess.

797
00:38:42,440 --> 00:38:43,280
Speaker 2: I said it to say.

798
00:38:43,080 --> 00:38:46,160
Speaker 1: That I am someone who has started over a lot

799
00:38:46,160 --> 00:38:48,960
Speaker 1: in my career. That we got another email about you

800
00:38:49,000 --> 00:38:51,080
Speaker 1: know what it's like to start over. For a long

801
00:38:51,120 --> 00:38:52,759
Speaker 1: part of my career, I thought I wanted to be

802
00:38:52,920 --> 00:38:56,759
Speaker 1: an academia. That didn't work out, and I realized what

803
00:38:56,840 --> 00:38:59,319
Speaker 1: I enjoyed about academia was being in front of a

804
00:38:59,320 --> 00:39:01,480
Speaker 1: classroom and working with young people and students, so like

805
00:39:01,560 --> 00:39:03,160
Speaker 1: that was really where I.

806
00:39:03,840 --> 00:39:05,480
Speaker 2: Found an energy that I had that I had been

807
00:39:05,480 --> 00:39:05,919
Speaker 2: looking for.

808
00:39:06,120 --> 00:39:08,200
Speaker 1: But you know, in academia the teaching is supposed to

809
00:39:08,239 --> 00:39:11,520
Speaker 1: be like supplement ary academic research that you're producing. That's

810
00:39:11,560 --> 00:39:12,920
Speaker 1: meant to be the main thing. And I was like, oh,

811
00:39:12,960 --> 00:39:14,760
Speaker 1: I'm really more into the teaching. So then I taught

812
00:39:14,760 --> 00:39:17,960
Speaker 1: for several years. Then from there I worked more in

813
00:39:18,000 --> 00:39:21,120
Speaker 1: like political activism and organizing. I got a job at

814
00:39:21,200 --> 00:39:24,520
Speaker 1: MSNBC start doing journalism. I really have taken kind of

815
00:39:24,520 --> 00:39:29,919
Speaker 1: a strange circuitous route. I'm rambling, and I was going

816
00:39:29,920 --> 00:39:33,479
Speaker 1: here because I wanted to set up to dovetail to Mike.

817
00:39:33,920 --> 00:39:37,560
Speaker 1: Because you are somebody who actually did finish your PhD.

818
00:39:38,000 --> 00:39:40,239
Speaker 1: You never make me call you doctor Ramato, even though

819
00:39:40,239 --> 00:39:42,520
Speaker 1: you could you should.

820
00:39:43,120 --> 00:39:44,920
Speaker 2: I think it's your right. I think it's your right

821
00:39:44,960 --> 00:39:47,879
Speaker 2: just say you're a doctor. A motto like no when

822
00:39:47,920 --> 00:39:50,640
Speaker 2: he's like emailing a company with a complaint or like

823
00:39:50,760 --> 00:39:53,560
Speaker 2: you want something free, you're you're not above doing it.

824
00:39:53,880 --> 00:39:56,839
Speaker 4: That's the main time I pull it out, when I'm

825
00:39:56,840 --> 00:39:59,719
Speaker 4: like complaining about something and want them to know like, no,

826
00:40:00,120 --> 00:40:02,920
Speaker 4: I'm someone whose complaints are backed up by evidence.

827
00:40:05,480 --> 00:40:09,800
Speaker 2: I guess quick addition to that, because Chase, when.

828
00:40:12,160 --> 00:40:14,680
Speaker 3: Mike and Bridgett sent out this email with the prompts

829
00:40:14,680 --> 00:40:16,319
Speaker 3: that we were talking about I have flag this one

830
00:40:16,320 --> 00:40:19,000
Speaker 3: where I was like, I like, in your email you

831
00:40:19,040 --> 00:40:21,239
Speaker 3: said I'm twenty four. I'm twenty six, so I'm two

832
00:40:21,280 --> 00:40:22,000
Speaker 3: years older than.

833
00:40:21,920 --> 00:40:23,440
Speaker 2: You, And I.

834
00:40:25,040 --> 00:40:27,080
Speaker 3: Was like, I'll give my opinion as somebody who like

835
00:40:28,200 --> 00:40:28,920
Speaker 3: I kind of get it.

836
00:40:28,960 --> 00:40:31,200
Speaker 2: I don't know, because I resit a lot of what

837
00:40:31,200 --> 00:40:31,600
Speaker 2: you were saying.

838
00:40:31,600 --> 00:40:33,400
Speaker 3: I really resonate with where I think like it is

839
00:40:33,440 --> 00:40:35,799
Speaker 3: a time in your life where and I'm saying this

840
00:40:35,920 --> 00:40:38,719
Speaker 3: here where I'm still figuring out what the hell I'm

841
00:40:38,760 --> 00:40:42,040
Speaker 3: doing and what I want to do with my life. Personally, though,

842
00:40:42,080 --> 00:40:45,640
Speaker 3: I will say like my route to getting into podcasting

843
00:40:46,160 --> 00:40:49,839
Speaker 3: was because I also this is something where it's it's

844
00:40:49,880 --> 00:40:52,160
Speaker 3: not a traditional career path. Everybody I work with has

845
00:40:52,160 --> 00:40:54,920
Speaker 3: a different path that they got into it. For me,

846
00:40:55,440 --> 00:40:58,799
Speaker 3: I studied journalism in college. I for a while really

847
00:40:58,800 --> 00:41:01,440
Speaker 3: wanted to go into the film industry, uh, and then

848
00:41:01,480 --> 00:41:03,720
Speaker 3: sort of got to college and was like, never mind,

849
00:41:03,840 --> 00:41:05,040
Speaker 3: I am more of a writer.

850
00:41:05,280 --> 00:41:07,960
Speaker 2: I want to do all of this study journalism.

851
00:41:08,600 --> 00:41:11,360
Speaker 3: Got really involved with the bridget you kind of you

852
00:41:11,400 --> 00:41:13,279
Speaker 3: mentioned this when you were talking. I rot involved with

853
00:41:13,360 --> 00:41:17,960
Speaker 3: my college's radio program, so I was not as like

854
00:41:19,320 --> 00:41:23,400
Speaker 3: the big name on campus bridget Tide. But but you know,

855
00:41:23,520 --> 00:41:25,720
Speaker 3: but I was. I was super involved with the radio studio.

856
00:41:25,760 --> 00:41:27,719
Speaker 3: I kind of found my niche of like media that

857
00:41:27,760 --> 00:41:29,880
Speaker 3: I was into. I was doing a lot with that.

858
00:41:30,000 --> 00:41:33,640
Speaker 3: I had some audio editing experience. Because of that, I

859
00:41:33,800 --> 00:41:36,400
Speaker 3: got kind of lucky in a weird way where I

860
00:41:36,480 --> 00:41:38,839
Speaker 3: graduated in the middle of the pandemic. But also it

861
00:41:38,880 --> 00:41:41,520
Speaker 3: was right when podcasting was taking off.

862
00:41:42,760 --> 00:41:44,239
Speaker 2: Again. That's why I say I'm like it was it

863
00:41:44,280 --> 00:41:45,359
Speaker 2: was lucky and to way lucky.

864
00:41:45,600 --> 00:41:48,360
Speaker 3: I'm lucky away because if you know anything about if

865
00:41:48,400 --> 00:41:51,400
Speaker 3: anybody listening was a was a junior senior at the

866
00:41:51,400 --> 00:41:54,200
Speaker 3: time when COVID started, it was a weird time.

867
00:41:54,840 --> 00:41:57,120
Speaker 2: I had an internship that I was about a month

868
00:41:57,120 --> 00:41:59,480
Speaker 2: and two that got cut short that I immediately freaked

869
00:41:59,520 --> 00:42:01,880
Speaker 2: out and was like my career so I'm never gonna whatever.

870
00:42:02,160 --> 00:42:04,040
Speaker 2: But but it also it was like it was a

871
00:42:04,080 --> 00:42:06,759
Speaker 2: time when they were looking for people that had audio experience.

872
00:42:07,120 --> 00:42:10,759
Speaker 2: It was a new industry, and I just happened to

873
00:42:10,960 --> 00:42:14,560
Speaker 2: have that experience. But yeah, I I The thing that

874
00:42:14,600 --> 00:42:16,279
Speaker 2: I really emphasize, I think for a lot of people

875
00:42:16,400 --> 00:42:18,520
Speaker 2: is like I I all do real like when I wasn't,

876
00:42:18,680 --> 00:42:21,799
Speaker 2: I never was a big, like podcast listener before I

877
00:42:21,880 --> 00:42:25,680
Speaker 2: started this career path. Yeah, because I and part of

878
00:42:25,719 --> 00:42:27,120
Speaker 2: it was just that I was like, I knew I

879
00:42:27,160 --> 00:42:31,160
Speaker 2: was into media. I knew I was into like storytelling,

880
00:42:31,520 --> 00:42:32,560
Speaker 2: talking about things.

881
00:42:32,640 --> 00:42:35,920
Speaker 3: I was into the like pop culture. I again, for

882
00:42:35,960 --> 00:42:37,600
Speaker 3: a while, really wanted to go to film. I had

883
00:42:37,640 --> 00:42:40,480
Speaker 3: that like that background too. I had done a couple

884
00:42:40,520 --> 00:42:43,880
Speaker 3: of internships that were in like the documentary sort of field,

885
00:42:44,560 --> 00:42:46,400
Speaker 3: and it worked out really well where it was like this,

886
00:42:47,000 --> 00:42:49,880
Speaker 3: these things that I liked doing, and there's an industry

887
00:42:49,920 --> 00:42:52,279
Speaker 3: that I'm able to do all of them. Podcasting was

888
00:42:52,320 --> 00:42:54,080
Speaker 3: the thing when I graduated. That was the big thing.

889
00:42:54,280 --> 00:42:56,680
Speaker 3: There's gonna be something else currently or in a couple

890
00:42:56,680 --> 00:42:57,080
Speaker 3: of years.

891
00:42:57,560 --> 00:42:58,399
Speaker 2: That's such a.

892
00:42:58,320 --> 00:43:02,440
Speaker 1: Good way to put it, because the stuff that I

893
00:43:02,520 --> 00:43:05,320
Speaker 1: the skills that I got just sort of like fell

894
00:43:05,400 --> 00:43:07,719
Speaker 1: ass backward into that I use every day now and

895
00:43:07,800 --> 00:43:09,640
Speaker 1: have been really helpful of my career. There are things

896
00:43:09,640 --> 00:43:12,560
Speaker 1: I would have never, you know, thought would pick up,

897
00:43:12,600 --> 00:43:15,960
Speaker 1: Like I got into podcasting because I was the opposite

898
00:43:15,960 --> 00:43:18,360
Speaker 1: of you. I was just a voracious listener of podcasts

899
00:43:18,400 --> 00:43:21,520
Speaker 1: early on, and I was I was. I was there

900
00:43:21,640 --> 00:43:24,800
Speaker 1: for that early wave of podcasting. The sort of wild

901
00:43:24,840 --> 00:43:28,120
Speaker 1: wild West before that second boom, and when you were

902
00:43:28,120 --> 00:43:31,640
Speaker 1: graduating into audio production, Like I was just there as

903
00:43:31,640 --> 00:43:34,200
Speaker 1: a as a listener of podcasts and the feel at

904
00:43:34,200 --> 00:43:36,359
Speaker 1: that point this was like two thousand and eight, two

905
00:43:36,360 --> 00:43:38,600
Speaker 1: thousand and nine, it wasn't that big of a space.

906
00:43:38,680 --> 00:43:42,120
Speaker 1: And so just by some being somebody who liked podcasts

907
00:43:42,160 --> 00:43:43,960
Speaker 1: a lot and like knew all the shows and had

908
00:43:44,000 --> 00:43:46,640
Speaker 1: listened to them all, I was able to show up

909
00:43:46,680 --> 00:43:48,960
Speaker 1: in that space professionally. I never thought that would be

910
00:43:48,960 --> 00:43:51,120
Speaker 1: something that would be at an avenue for me. So

911
00:43:51,480 --> 00:43:54,240
Speaker 1: I say that to say it really reflects your career

912
00:43:54,320 --> 00:43:59,600
Speaker 1: path of just sort of happenstance, luck being in the

913
00:43:59,680 --> 00:44:01,880
Speaker 1: right way the right time, and then also really following

914
00:44:01,960 --> 00:44:03,920
Speaker 1: what it is that you that that feels like an

915
00:44:03,960 --> 00:44:07,000
Speaker 1: alignment things. Yeah, I could never have on paper planned

916
00:44:07,080 --> 00:44:08,719
Speaker 1: for the career that I have now.

917
00:44:08,800 --> 00:44:10,800
Speaker 2: I think all of the twists.

918
00:44:10,360 --> 00:44:15,480
Speaker 1: And turns and you know, weirdness, stopovers and pit stuffs

919
00:44:15,680 --> 00:44:17,359
Speaker 1: are part of it in a kind of way.

920
00:44:17,440 --> 00:44:19,719
Speaker 2: That's that's sort of part of the journeys. That sounds

921
00:44:19,760 --> 00:44:22,600
Speaker 2: so cheesy, but it's true. No, it's real though.

922
00:44:22,640 --> 00:44:26,120
Speaker 3: I Mean, I I like the first because and again

923
00:44:26,320 --> 00:44:29,440
Speaker 3: I came into this show as a producer, and I

924
00:44:29,480 --> 00:44:32,040
Speaker 3: came into iHeart as a producer. But like the first

925
00:44:32,719 --> 00:44:36,000
Speaker 3: episode that I wrote and co hosted was like about

926
00:44:36,560 --> 00:44:39,279
Speaker 3: like a comic book character first stuff bomb never told

927
00:44:39,360 --> 00:44:41,239
Speaker 3: you or they had like mentioned that they wanted to

928
00:44:41,320 --> 00:44:44,440
Speaker 3: do an episode, and I was like, I emailed Samantha

929
00:44:44,480 --> 00:44:48,440
Speaker 3: Andy as the hosts who like they're amazing, love them,

930
00:44:48,800 --> 00:44:50,839
Speaker 3: And I was like, you mentioned this character, you mentioned

931
00:44:50,840 --> 00:44:52,000
Speaker 3: one doing an episode about this.

932
00:44:52,320 --> 00:44:54,600
Speaker 2: I I really love this character.

933
00:44:54,640 --> 00:44:56,839
Speaker 3: I would love to be involved with it somehow, And

934
00:44:56,920 --> 00:44:58,200
Speaker 3: like they were like, if you want to write it,

935
00:44:58,239 --> 00:44:59,960
Speaker 3: go ahead, and I was sort of like, oh wow, gay,

936
00:45:00,160 --> 00:45:02,040
Speaker 3: So yeah, it is like a weird like you kind

937
00:45:02,040 --> 00:45:04,440
Speaker 3: of just got to wait for the opportunity. Which and

938
00:45:04,480 --> 00:45:06,759
Speaker 3: again I'm saying this too, this is a it's a

939
00:45:06,800 --> 00:45:11,000
Speaker 3: double edged sword of Also I will recognize, like I

940
00:45:11,040 --> 00:45:12,640
Speaker 3: said it earlier, I'm twenty six.

941
00:45:12,719 --> 00:45:14,600
Speaker 2: I feel like I've been really lucky, where like.

942
00:45:14,640 --> 00:45:19,720
Speaker 3: I success is like is it's I feel so like, wow,

943
00:45:19,840 --> 00:45:23,239
Speaker 3: I'm one of those like barstool podcasts or something being like,

944
00:45:23,239 --> 00:45:25,359
Speaker 3: oh my god, the key to success is but but

945
00:45:25,360 --> 00:45:27,360
Speaker 3: for real, but really like the the key to success

946
00:45:27,440 --> 00:45:27,799
Speaker 3: is like.

947
00:45:28,040 --> 00:45:30,800
Speaker 2: I'm not the key to it. Never mind forget you

948
00:45:30,840 --> 00:45:32,000
Speaker 2: don't trying to say you don't have to.

949
00:45:32,760 --> 00:45:35,080
Speaker 3: I think the way to do well is it's the

950
00:45:35,160 --> 00:45:37,399
Speaker 3: it's the combination of like having those skills ready. Where

951
00:45:37,400 --> 00:45:39,760
Speaker 3: again I was like, I have this background in radio,

952
00:45:40,400 --> 00:45:42,640
Speaker 3: I've worked on audio, I have a portfolio I can

953
00:45:42,680 --> 00:45:45,560
Speaker 3: send people, and like, when I got the interview for

954
00:45:45,600 --> 00:45:47,640
Speaker 3: this job, I was like, here, I have all these

955
00:45:47,640 --> 00:45:49,759
Speaker 3: things I can send you. That was really a leg up,

956
00:45:49,760 --> 00:45:52,359
Speaker 3: but also being like and once you were ready for

957
00:45:52,360 --> 00:45:54,600
Speaker 3: me to be like, can you write an episode about this?

958
00:45:54,760 --> 00:45:56,839
Speaker 3: I was like, yeah, let's go. I love this thing,

959
00:45:56,920 --> 00:45:58,600
Speaker 3: Let's do it. And it's kind of been like a

960
00:45:58,600 --> 00:45:59,560
Speaker 3: snowball since then.

961
00:46:00,440 --> 00:46:04,640
Speaker 4: I think luck is a huge part of pretty much

962
00:46:04,640 --> 00:46:07,920
Speaker 4: every successful career, and hopefully some good luck, but like

963
00:46:07,960 --> 00:46:12,160
Speaker 4: a lot of bad luck too. But you know, what's

964
00:46:12,200 --> 00:46:15,319
Speaker 4: the old saying that, like luck is what happens when

965
00:46:15,440 --> 00:46:17,239
Speaker 4: preparation meets opportunity.

966
00:46:17,680 --> 00:46:18,719
Speaker 2: That's what I was thinking of.

967
00:46:18,800 --> 00:46:23,520
Speaker 4: Yeah, yeah, I think it's really true. You know, I'm

968
00:46:23,520 --> 00:46:27,960
Speaker 4: also somebody who's had a non traditional career. It's hard

969
00:46:27,960 --> 00:46:29,680
Speaker 4: to put a lot of labels on exactly what my

970
00:46:29,719 --> 00:46:33,640
Speaker 4: career is, but non traditional, perhaps it's better than anything.

971
00:46:35,080 --> 00:46:40,319
Speaker 4: And yeah, there was a lot of what I would

972
00:46:40,400 --> 00:46:43,680
Speaker 4: want to call luck, but was more just sort of

973
00:46:43,719 --> 00:46:50,560
Speaker 4: like unexpected opportunities that for whatever reason I had a

974
00:46:50,719 --> 00:46:57,880
Speaker 4: mix of qualifications for and or a willingness to take

975
00:46:58,040 --> 00:47:01,480
Speaker 4: a risk and an ability to take a risk. You know,

976
00:47:01,880 --> 00:47:07,640
Speaker 4: I think for any body who's contemplating a non traditional

977
00:47:07,680 --> 00:47:10,640
Speaker 4: career path, uh, and you probably know who you are

978
00:47:10,719 --> 00:47:12,960
Speaker 4: right like that. If you hear that phrase of that

979
00:47:13,000 --> 00:47:15,720
Speaker 4: and you're like, yeah, that's me, then yeah, you're probably

980
00:47:15,760 --> 00:47:16,239
Speaker 4: one of us.

981
00:47:16,920 --> 00:47:17,040
Speaker 3: Uh.

982
00:47:18,680 --> 00:47:22,040
Speaker 4: You know, you just have to know for yourself, like

983
00:47:23,560 --> 00:47:27,000
Speaker 4: how risky are you willing to be? I think that's

984
00:47:26,360 --> 00:47:29,360
Speaker 4: a big question that needs to be answered.

985
00:47:29,880 --> 00:47:32,239
Speaker 1: Yeah, if anybody this, I don't know if this is

986
00:47:33,000 --> 00:47:35,520
Speaker 1: interesting for anybody that's not trying to get into media,

987
00:47:35,560 --> 00:47:37,800
Speaker 1: but like I was just having a conversation with a

988
00:47:37,800 --> 00:47:40,439
Speaker 1: family member over the weekend about this about that's sort

989
00:47:40,440 --> 00:47:45,359
Speaker 1: of balancing act that goes into, at least for my work,

990
00:47:45,400 --> 00:47:47,640
Speaker 1: it goes into like making the financials work and then

991
00:47:47,680 --> 00:47:50,680
Speaker 1: the math math and how you have your one client

992
00:47:50,800 --> 00:47:53,080
Speaker 1: that pays for your ability to take this other client

993
00:47:53,160 --> 00:47:55,080
Speaker 1: or your ability to do this other passion project. That

994
00:47:55,080 --> 00:47:57,160
Speaker 1: doesn't really pay, but maybe it will. Like it really

995
00:47:57,200 --> 00:48:00,000
Speaker 1: is a little bit of a smitting plates dance, I

996
00:48:00,080 --> 00:48:03,520
Speaker 1: will say. We got an email from Steph from Winnipeg

997
00:48:03,960 --> 00:48:06,880
Speaker 1: who said that she heard that I we used to

998
00:48:06,880 --> 00:48:09,319
Speaker 1: be in education, which is true. What a different world

999
00:48:09,360 --> 00:48:12,160
Speaker 1: than podcasting. I'm in my mid thirties and I've considered

1000
00:48:12,160 --> 00:48:14,680
Speaker 1: a one eighty career change to myself, but it's very scary.

1001
00:48:15,080 --> 00:48:17,200
Speaker 1: Does Bridget have any advice on how to do without

1002
00:48:17,280 --> 00:48:19,200
Speaker 1: ruining your life? I hate the idea of starting over,

1003
00:48:19,280 --> 00:48:21,600
Speaker 1: but this is not it. For reference, I'm currently in

1004
00:48:21,640 --> 00:48:26,120
Speaker 1: accounting and administration looking at agrisciences. Lots of farming around here,

1005
00:48:26,160 --> 00:48:28,480
Speaker 1: And first of all, I just I love this email.

1006
00:48:29,000 --> 00:48:32,600
Speaker 1: I am all about a second, third, fourth act. I

1007
00:48:32,600 --> 00:48:35,560
Speaker 1: feel like I've had many of them in my career.

1008
00:48:35,920 --> 00:48:38,880
Speaker 1: But Mike, I do feel like this email speaks to

1009
00:48:38,880 --> 00:48:41,400
Speaker 1: what you were sort of answering right Like you know

1010
00:48:41,440 --> 00:48:45,719
Speaker 1: when I first met you. This is you were just

1011
00:48:45,760 --> 00:48:50,799
Speaker 1: a lowly data like just a lowly PhD HA who

1012
00:48:51,000 --> 00:48:53,320
Speaker 1: was I don't know, just doing some like pitdly little

1013
00:48:53,320 --> 00:48:55,320
Speaker 1: thing running a data team of one of the country's

1014
00:48:55,360 --> 00:48:58,879
Speaker 1: largest public health nonprofits. And I plucked you from that

1015
00:48:59,000 --> 00:49:03,120
Speaker 1: world of gardener and obscurity, and I said, come to podcasting.

1016
00:49:04,320 --> 00:49:06,920
Speaker 1: This is our this is our hallmark episode.

1017
00:49:07,320 --> 00:49:11,360
Speaker 3: Yeah, for the Christmas season, the holiday season, whatever.

1018
00:49:11,840 --> 00:49:16,520
Speaker 1: Yeah, I taught my true meaning of Christy. It's riskying

1019
00:49:16,560 --> 00:49:18,600
Speaker 1: at all to become a podcaster.

1020
00:49:20,080 --> 00:49:25,440
Speaker 4: Yeah, it's yeah, so I have. I also love this question.

1021
00:49:26,080 --> 00:49:31,520
Speaker 4: I love to hear about people like Steph who are

1022
00:49:32,680 --> 00:49:36,399
Speaker 4: even just contemplating big changes, because I think they can

1023
00:49:36,480 --> 00:49:40,319
Speaker 4: be like really scary and rightfully so. But I think

1024
00:49:40,360 --> 00:49:47,279
Speaker 4: also like spending another twenty thirty years toiling at a

1025
00:49:47,360 --> 00:49:52,399
Speaker 4: profession that like you don't enjoy and like maybe makes

1026
00:49:52,440 --> 00:49:57,879
Speaker 4: you miserable is its own kind of risky. And yeah,

1027
00:49:57,880 --> 00:49:59,800
Speaker 4: I'm somebody who I have.

1028
00:50:00,000 --> 00:50:00,799
Speaker 2: I've made.

1029
00:50:02,200 --> 00:50:07,920
Speaker 4: Three distinct, extremely hard pivots in my career. So when

1030
00:50:07,960 --> 00:50:09,799
Speaker 4: I first went to grad school, I was accepted into

1031
00:50:09,840 --> 00:50:13,080
Speaker 4: a PhD program in the psyche department at UW Madison,

1032
00:50:13,120 --> 00:50:18,680
Speaker 4: which is like a very prestigious program, and I went

1033
00:50:18,760 --> 00:50:22,800
Speaker 4: there to study psycho linguistics in a lab that did

1034
00:50:23,560 --> 00:50:27,600
Speaker 4: like linguistics and neuroscience. It was really cool, heady stuff.

1035
00:50:27,600 --> 00:50:31,440
Speaker 4: How does the brain learn language and store information about

1036
00:50:31,480 --> 00:50:33,440
Speaker 4: words and meanings? And how do we put them together

1037
00:50:33,440 --> 00:50:35,879
Speaker 4: to communicate what does that tell us about the way

1038
00:50:35,920 --> 00:50:40,120
Speaker 4: we understand the world? Really heavy interesting things. I'd done

1039
00:50:40,160 --> 00:50:44,520
Speaker 4: it somewhat undergraduate, some time off between to work in

1040
00:50:44,560 --> 00:50:48,000
Speaker 4: a lab, and then got to accepted this prestigious program.

1041
00:50:48,760 --> 00:50:50,960
Speaker 4: And after about ten years of this, I just realized

1042
00:50:50,960 --> 00:50:54,680
Speaker 4: that it was not for me. It's like super interesting research.

1043
00:50:54,800 --> 00:50:59,040
Speaker 4: I'm really glad that there are brilliant people continuing to

1044
00:50:59,080 --> 00:51:03,759
Speaker 4: study that and like push the frontiers of human understanding.

1045
00:51:03,960 --> 00:51:06,320
Speaker 4: It's why we have LLLMS now is because of people

1046
00:51:06,440 --> 00:51:09,960
Speaker 4: doing research in that area about like brain connectivity. But

1047
00:51:10,880 --> 00:51:13,759
Speaker 4: it just wasn't for me. You know, I didn't know

1048
00:51:13,800 --> 00:51:15,920
Speaker 4: this when I was younger, but over the course of

1049
00:51:15,960 --> 00:51:20,360
Speaker 4: about ten years of study, I realized that I really

1050
00:51:21,600 --> 00:51:26,920
Speaker 4: wanted to be doing something more directly applied. It's like

1051
00:51:27,000 --> 00:51:31,720
Speaker 4: solving like more immediate problems in people's life. Again, I

1052
00:51:31,760 --> 00:51:34,920
Speaker 4: really value basic science, but it just that wasn't it

1053
00:51:35,080 --> 00:51:37,720
Speaker 4: for me, and so I pivoted put together a whole

1054
00:51:37,719 --> 00:51:43,760
Speaker 4: new program with the help of some really compassionate, kind

1055
00:51:43,880 --> 00:51:49,600
Speaker 4: smart mentors. Worked in natural resource management for several years

1056
00:51:50,400 --> 00:51:54,120
Speaker 4: and that was really cool and interesting, and then from

1057
00:51:54,200 --> 00:51:56,480
Speaker 4: there got into tobacco control, which I think I've talked

1058
00:51:56,520 --> 00:51:58,279
Speaker 4: about on the show a fair amount. That's where you

1059
00:51:58,280 --> 00:52:01,080
Speaker 4: met me, Bridget when I was leading the data team

1060
00:52:02,440 --> 00:52:07,000
Speaker 4: for Truth Initiative, the country's largest nonprofit dedicated to eliminating

1061
00:52:07,000 --> 00:52:10,560
Speaker 4: the harm of tobacco to Americans. It was really cool.

1062
00:52:10,600 --> 00:52:15,160
Speaker 4: I was working on digital interventions to help people quit smoking,

1063
00:52:15,239 --> 00:52:18,359
Speaker 4: so like apps and online programs to help people quit

1064
00:52:18,400 --> 00:52:21,600
Speaker 4: smoking and vaping and whatever other tobacco products they wanted

1065
00:52:21,600 --> 00:52:23,359
Speaker 4: to do. It was like a public health service. We

1066
00:52:23,360 --> 00:52:26,520
Speaker 4: were helping millions of people. It was also a research platform.

1067
00:52:27,040 --> 00:52:29,880
Speaker 4: I got to work with like really smart, cool people.

1068
00:52:31,040 --> 00:52:34,279
Speaker 4: It was a good job, paid well, good benefits, and

1069
00:52:34,360 --> 00:52:37,800
Speaker 4: so pretty much everyone in my life was pretty shocked

1070
00:52:37,880 --> 00:52:44,280
Speaker 4: when I pivoted yet again to come work on this show.

1071
00:52:44,520 --> 00:52:48,560
Speaker 1: And you you're understellgate because you were like a slick

1072
00:52:48,800 --> 00:52:53,200
Speaker 1: professional guy like you were. I just want people to

1073
00:52:53,280 --> 00:52:58,560
Speaker 1: understand the ways on which you really had a really prestige.

1074
00:52:58,719 --> 00:53:00,880
Speaker 1: Not that what we do is not pursuced, but you

1075
00:53:00,920 --> 00:53:05,080
Speaker 1: had a very specific kind of prestigious career that I

1076
00:53:05,120 --> 00:53:07,319
Speaker 1: could tell, and I don't think I'm telling tales out

1077
00:53:07,320 --> 00:53:09,920
Speaker 1: of school to say was not aligned with what you

1078
00:53:09,960 --> 00:53:12,520
Speaker 1: wanted to be doing day to day.

1079
00:53:12,800 --> 00:53:16,279
Speaker 4: It wasn't that it was unaligned, but I just, you know,

1080
00:53:16,440 --> 00:53:24,400
Speaker 4: increasingly was it found my mind attracted to other problems. So, like,

1081
00:53:26,440 --> 00:53:31,319
Speaker 4: you know, if I'm really motivated by public health impact, right, Like,

1082
00:53:31,360 --> 00:53:33,520
Speaker 4: I'm somebody who's benefited from a lot of privilege in

1083
00:53:33,560 --> 00:53:37,640
Speaker 4: my life, uh, and it's important to me that what

1084
00:53:37,680 --> 00:53:40,520
Speaker 4: I do with my time here on this earth is

1085
00:53:40,920 --> 00:53:47,960
Speaker 4: like contributing to helping other people and trying to reduce

1086
00:53:48,000 --> 00:53:51,000
Speaker 4: the prevalence of smoking or actually reducing the prevalence of

1087
00:53:51,000 --> 00:53:54,200
Speaker 4: smoking is like one of the biggest things that you

1088
00:53:54,239 --> 00:53:57,120
Speaker 4: can do, right, Like it's it's so harmful in our

1089
00:53:57,160 --> 00:53:58,719
Speaker 4: society in ways that I think a lot of people

1090
00:53:58,800 --> 00:54:02,400
Speaker 4: just like really don't appreciate the magnitude of death and

1091
00:54:02,440 --> 00:54:06,719
Speaker 4: disease that's smoking causes and cost to the healthcare industry.

1092
00:54:10,280 --> 00:54:13,640
Speaker 2: But it just yeah, I guess.

1093
00:54:13,520 --> 00:54:16,640
Speaker 4: My you know, this was happening at like the end

1094
00:54:16,719 --> 00:54:19,879
Speaker 4: of the twenty tens, the first Trump era, And I've

1095
00:54:19,920 --> 00:54:23,799
Speaker 4: just always really been interested in the Internet from the

1096
00:54:23,880 --> 00:54:25,719
Speaker 4: earliest days. I think that's something we all have in

1097
00:54:25,719 --> 00:54:30,120
Speaker 4: common here. And you know, Bridget, as you were pulling

1098
00:54:30,120 --> 00:54:37,160
Speaker 4: this show together, trying to, in my opinion, really confront

1099
00:54:37,200 --> 00:54:43,000
Speaker 4: and address some of the root causes of problems with

1100
00:54:43,160 --> 00:54:45,279
Speaker 4: the internet right where it has. The Internet has so

1101
00:54:45,360 --> 00:54:50,200
Speaker 4: much potential to connect people, to democratize information, to raise

1102
00:54:50,239 --> 00:54:54,920
Speaker 4: awareness about important problems, to help people organize, to advocate

1103
00:54:55,080 --> 00:55:00,000
Speaker 4: for solutions, and increasingly I felt like it was being

1104
00:55:00,080 --> 00:55:04,680
Speaker 4: co opted to do other things, often in direct opposition

1105
00:55:04,719 --> 00:55:07,680
Speaker 4: to those like nobler ideals, and so, you know, at

1106
00:55:07,680 --> 00:55:10,520
Speaker 4: the beginning of this episode, one of the things Joey

1107
00:55:10,600 --> 00:55:20,399
Speaker 4: mentioned was feeling more emboldened, empowered, encouraged to take up

1108
00:55:20,440 --> 00:55:23,000
Speaker 4: space and conversations about technology. And so when I talk

1109
00:55:23,080 --> 00:55:26,560
Speaker 4: with people about why I'm doing this show, that is

1110
00:55:26,680 --> 00:55:32,120
Speaker 4: precisely the reason I think the Internet affects all of

1111
00:55:32,200 --> 00:55:35,840
Speaker 4: us in like profound ways, from how we pay for

1112
00:55:35,880 --> 00:55:38,080
Speaker 4: stuff at the store, to how we connect with our

1113
00:55:38,280 --> 00:55:41,279
Speaker 4: family members, to how we elect candidates, to how we

1114
00:55:42,280 --> 00:55:46,160
Speaker 4: decide to get vaccinated, like all of it is filtered

1115
00:55:46,160 --> 00:55:51,719
Speaker 4: through the Internet. And I really truly believe that we

1116
00:55:51,800 --> 00:55:55,440
Speaker 4: need to make the Internet better and address some of

1117
00:55:55,440 --> 00:55:59,520
Speaker 4: these problems before we're really going to be able to

1118
00:55:59,760 --> 00:56:03,520
Speaker 4: make progress on a lot of the other ills that

1119
00:56:03,600 --> 00:56:08,240
Speaker 4: are plaguing us and so yeah, it was a super

1120
00:56:08,239 --> 00:56:14,279
Speaker 4: hard pivot, not encouraged. Uh you know, definitely took a

1121
00:56:14,280 --> 00:56:19,480
Speaker 4: big financial hit on doing it, and the identity loss

1122
00:56:19,640 --> 00:56:25,719
Speaker 4: is real, but uh I I would do it again

1123
00:56:25,719 --> 00:56:30,200
Speaker 4: because it's it feels really good to you know, wake

1124
00:56:30,320 --> 00:56:35,280
Speaker 4: up every day and feel really connected to the output

1125
00:56:35,280 --> 00:56:37,239
Speaker 4: of what we're doing, not that I didn't before, but

1126
00:56:37,480 --> 00:56:40,840
Speaker 4: just also ownership of it. I think that makes a

1127
00:56:40,880 --> 00:56:44,160
Speaker 4: big difference to me. You know, like everybody is different

1128
00:56:44,200 --> 00:56:48,600
Speaker 4: in what they value and for me have I think

1129
00:56:48,640 --> 00:56:53,880
Speaker 4: having control over what I do with my time is

1130
00:56:53,880 --> 00:56:58,520
Speaker 4: a big one, and working on this podcast has uh

1131
00:56:59,440 --> 00:57:02,399
Speaker 4: you know, allowed me to have more of that as well.

1132
00:57:03,400 --> 00:57:07,760
Speaker 1: Okay, so speaking of how we have career stuff career paths,

1133
00:57:07,920 --> 00:57:10,800
Speaker 1: we got an email from Sampe who recently moved to Michigan,

1134
00:57:11,080 --> 00:57:12,839
Speaker 1: who writes, I would love to hear more about Priduce

1135
00:57:12,920 --> 00:57:15,000
Speaker 1: career paths. What did she study in school? How did

1136
00:57:15,040 --> 00:57:17,320
Speaker 1: she break into podcast? How did she get a host gig?

1137
00:57:17,840 --> 00:57:19,640
Speaker 1: This is actually one of my favorite stories to talk

1138
00:57:19,640 --> 00:57:22,760
Speaker 1: about because how I got my How I became a

1139
00:57:22,840 --> 00:57:26,160
Speaker 1: host on podcast is test one three being a voracious

1140
00:57:26,160 --> 00:57:28,520
Speaker 1: listener podcast and then two.

1141
00:57:29,200 --> 00:57:32,520
Speaker 2: I early in the early, early, early.

1142
00:57:32,320 --> 00:57:35,280
Speaker 1: Days of podcast And this was in for good two

1143
00:57:35,280 --> 00:57:38,240
Speaker 1: thousand and nine, twenty ten, before we had any idea

1144
00:57:38,440 --> 00:57:40,600
Speaker 1: of what what this medium was going to be. This

1145
00:57:40,760 --> 00:57:44,240
Speaker 1: was pre serial, right, So this was way before anybody

1146
00:57:44,360 --> 00:57:45,800
Speaker 1: was really making real money on this.

1147
00:57:45,840 --> 00:57:48,640
Speaker 2: People didn't. We were still counting metrics by hand and shit,

1148
00:57:48,720 --> 00:57:49,800
Speaker 2: like very early days.

1149
00:57:50,120 --> 00:57:51,840
Speaker 4: I just to put a pin in that, you know,

1150
00:57:52,120 --> 00:57:54,320
Speaker 4: folks like bridge've been in this industry for a long

1151
00:57:54,360 --> 00:57:59,240
Speaker 4: time will demarcate distinct error eras like the pre serial

1152
00:57:59,280 --> 00:58:01,240
Speaker 4: era and the post serial era.

1153
00:58:01,360 --> 00:58:03,080
Speaker 2: That is right, So I thank you for saying that.

1154
00:58:03,160 --> 00:58:04,680
Speaker 2: I know you mean, I know what you mean.

1155
00:58:06,040 --> 00:58:10,000
Speaker 1: So Cereal is when podcasting for a lot for people

1156
00:58:10,040 --> 00:58:11,960
Speaker 1: who like are like do this professionally.

1157
00:58:12,280 --> 00:58:16,200
Speaker 2: That is like the like before Christ and after Christ.

1158
00:58:16,240 --> 00:58:19,680
Speaker 2: Not to say that you know, Cereal and this American

1159
00:58:19,760 --> 00:58:21,720
Speaker 2: Life Team is Christ, but are they?

1160
00:58:22,400 --> 00:58:26,480
Speaker 1: But like, yeah, that was when they became much more professionalized.

1161
00:58:26,840 --> 00:58:29,760
Speaker 1: AD sales became a thing. Before that, it wasn't really

1162
00:58:29,960 --> 00:58:32,600
Speaker 1: that kind of scene. So I have been in the

1163
00:58:32,680 --> 00:58:34,920
Speaker 1: space since before Cereal was a thing, which is a

1164
00:58:34,960 --> 00:58:38,040
Speaker 1: long time. That's like a like I've been I've been

1165
00:58:38,040 --> 00:58:41,480
Speaker 1: I've been making podcasts professionally in some capacity for over

1166
00:58:41,520 --> 00:58:45,920
Speaker 1: ten years, and I remember seeing an advertisement for a

1167
00:58:45,920 --> 00:58:48,520
Speaker 1: podcast that was called The Flaming.

1168
00:58:48,160 --> 00:58:49,040
Speaker 2: Sort of Justice.

1169
00:58:49,560 --> 00:58:52,720
Speaker 1: I know, weird name, but it was hosted by my

1170
00:58:53,000 --> 00:58:56,040
Speaker 1: good friend and former boss Ben Wickler, who is now

1171
00:58:56,440 --> 00:58:59,760
Speaker 1: the chair of the Wisconsin Democratic Party. You've probably seen

1172
00:58:59,840 --> 00:59:03,840
Speaker 1: him on TV, like he in Madison, Wisconsin.

1173
00:59:03,920 --> 00:59:06,240
Speaker 2: He's a big deal. But he.

1174
00:59:07,800 --> 00:59:11,000
Speaker 1: Was working on this podcast project. It was him and

1175
00:59:11,200 --> 00:59:14,280
Speaker 1: the late Aaron Swartz. If you know him, he was

1176
00:59:14,360 --> 00:59:18,040
Speaker 1: this very prolific figure in the fight for digital rights,

1177
00:59:18,080 --> 00:59:21,600
Speaker 1: fight for an open Internet. Our buddies that Cool Zoned

1178
00:59:21,640 --> 00:59:24,160
Speaker 1: did an entire deep dive episode into him.

1179
00:59:24,800 --> 00:59:28,959
Speaker 2: He is a fascinating person, a personal hero.

1180
00:59:29,680 --> 00:59:32,400
Speaker 1: Definitely, definitely think folks should should look into his story

1181
00:59:32,400 --> 00:59:34,880
Speaker 1: because it is one that is really tragic but also

1182
00:59:34,960 --> 00:59:37,160
Speaker 1: one that is like full of hope for a better

1183
00:59:37,200 --> 00:59:43,640
Speaker 1: Internet landscape. And Aaron felt strongly that all of the

1184
00:59:43,760 --> 00:59:47,040
Speaker 1: highs and lows and wins and losses of the fight

1185
00:59:47,200 --> 00:59:49,680
Speaker 1: for social justice and social change and the fight for

1186
00:59:49,720 --> 00:59:52,160
Speaker 1: an open Internet, we should tell those stories the way

1187
00:59:52,160 --> 00:59:55,120
Speaker 1: that we tell other kinds of stories that are that

1188
00:59:55,240 --> 00:59:58,960
Speaker 1: have romance and David versus Goliath and good conquering over

1189
00:59:59,040 --> 01:00:02,080
Speaker 1: evil and that if we told these stories in that

1190
01:00:02,160 --> 01:00:05,040
Speaker 1: kind of way, that we could make people understand what

1191
01:00:05,160 --> 01:00:07,040
Speaker 1: was at stake and then want to take some sort

1192
01:00:07,040 --> 01:00:10,160
Speaker 1: of action. So I saw this call for applicants for

1193
01:00:10,520 --> 01:00:14,480
Speaker 1: this podcast that him and Benwickler had put together, and

1194
01:00:14,520 --> 01:00:15,400
Speaker 1: I was like, this.

1195
01:00:15,320 --> 01:00:17,000
Speaker 2: Is perfect for me. This is so many things that

1196
01:00:17,040 --> 01:00:17,320
Speaker 2: I like.

1197
01:00:17,720 --> 01:00:21,920
Speaker 1: Only problem was I had not I had never edited

1198
01:00:21,960 --> 01:00:25,160
Speaker 1: an audio before, right, So I put together a resume

1199
01:00:25,560 --> 01:00:31,800
Speaker 1: full of lies, just like straight up fabrications about my skills. Literally,

1200
01:00:31,800 --> 01:00:35,240
Speaker 1: I think I might have googled podcast resume and then

1201
01:00:35,280 --> 01:00:37,120
Speaker 1: I just copied and pasted whatever it said and put

1202
01:00:37,120 --> 01:00:38,400
Speaker 1: it over on my resume. And I was like, whatever,

1203
01:00:38,520 --> 01:00:40,640
Speaker 1: what are I gonna do? Like this is on this

1204
01:00:40,680 --> 01:00:42,640
Speaker 1: is a hail Mary anyway. And I remember at the

1205
01:00:42,640 --> 01:00:44,400
Speaker 1: time I was living in DC and the job was

1206
01:00:44,440 --> 01:00:46,760
Speaker 1: in Brooklyn, and so I was like, I'm already like

1207
01:00:46,880 --> 01:00:48,480
Speaker 1: a super super long shot anyway.

1208
01:00:48,840 --> 01:00:49,919
Speaker 2: What anyway, I got the job.

1209
01:00:50,200 --> 01:00:51,720
Speaker 1: So then I was like, fuck, now I have to

1210
01:00:51,800 --> 01:00:54,840
Speaker 1: learn how to use all these tools I lied about

1211
01:00:54,920 --> 01:00:58,840
Speaker 1: on my resume. Luckily YouTube existed, and this was so

1212
01:00:59,040 --> 01:01:03,640
Speaker 1: early days that nobody really knew about podcasting, Like nobody

1213
01:01:03,680 --> 01:01:06,800
Speaker 1: had a college degree in podcasting, so truly you could

1214
01:01:06,800 --> 01:01:08,680
Speaker 1: have said anything and this learns about the fly.

1215
01:01:08,760 --> 01:01:11,360
Speaker 2: And that was my first job in podcasting.

1216
01:01:11,480 --> 01:01:13,200
Speaker 1: At that point, I was a producer, so I was

1217
01:01:13,240 --> 01:01:16,320
Speaker 1: really behind the mic helping Ben, who was the host,

1218
01:01:16,440 --> 01:01:19,120
Speaker 1: sound his best. And he was such a if you've

1219
01:01:19,120 --> 01:01:21,720
Speaker 1: ever seen Ben Weckler speak, if you happen to live

1220
01:01:21,720 --> 01:01:24,320
Speaker 1: in Wisconsin or catch him on TV, like, he did

1221
01:01:24,320 --> 01:01:25,960
Speaker 1: not need a lot of help from me as a producer,

1222
01:01:26,000 --> 01:01:28,520
Speaker 1: but he was fantastic and a great person to learn from.

1223
01:01:28,720 --> 01:01:30,680
Speaker 1: I learned a lot about how to tell good stories

1224
01:01:30,680 --> 01:01:33,800
Speaker 1: from him, and then how to tell stories with the

1225
01:01:33,840 --> 01:01:37,280
Speaker 1: gravy toss that they that they deserve. And so from

1226
01:01:37,320 --> 01:01:41,000
Speaker 1: there I remember every now and then I would be

1227
01:01:41,280 --> 01:01:43,200
Speaker 1: on Mike. But at that point I really thought like

1228
01:01:43,240 --> 01:01:45,880
Speaker 1: I am a behind the scenes girly Like I am.

1229
01:01:46,080 --> 01:01:48,680
Speaker 2: You know, my job is to make the show sound.

1230
01:01:48,440 --> 01:01:51,280
Speaker 1: Good, make the trains run on time, make sure the

1231
01:01:51,320 --> 01:01:54,320
Speaker 1: interview is good, and make sure all of that. And

1232
01:01:54,880 --> 01:01:59,080
Speaker 1: you know, I guess, even thinking about it now, I

1233
01:01:59,120 --> 01:02:03,920
Speaker 1: think Ben was someone who saw something in me and

1234
01:02:04,040 --> 01:02:05,720
Speaker 1: was like, you'd actually be good on Mike. And it

1235
01:02:05,720 --> 01:02:08,400
Speaker 1: wasn't something that I even though I had done, like

1236
01:02:08,520 --> 01:02:12,320
Speaker 1: college radio and stuff. I didn't really trust my voice yet,

1237
01:02:12,680 --> 01:02:18,480
Speaker 1: and truly just getting the shot to make terrible content

1238
01:02:18,640 --> 01:02:21,600
Speaker 1: on microphone and then hearing it and cringing, really getting

1239
01:02:21,640 --> 01:02:24,520
Speaker 1: the space to learn and try, I think was opened

1240
01:02:24,560 --> 01:02:27,440
Speaker 1: up a whole lot of doors to me. And the

1241
01:02:27,600 --> 01:02:30,200
Speaker 1: podcast here on iHeart Well used to be stuff Media

1242
01:02:30,560 --> 01:02:33,480
Speaker 1: Stuff mom Ever told you their hosts were leaving, and

1243
01:02:33,520 --> 01:02:35,640
Speaker 1: then a friend of mine, Emily Airies, was like, I'm

1244
01:02:35,680 --> 01:02:37,080
Speaker 1: coming on as a new host. I think you'd be

1245
01:02:37,120 --> 01:02:39,320
Speaker 1: great as a co host. I was in Australia and

1246
01:02:39,360 --> 01:02:41,800
Speaker 1: so I had to do that interview at like four

1247
01:02:41,840 --> 01:02:45,400
Speaker 1: am on a Saturday for the time change, and it

1248
01:02:45,440 --> 01:02:48,320
Speaker 1: was just a lot, but I ended up getting that

1249
01:02:48,400 --> 01:02:50,400
Speaker 1: the job as the co host for Stuff mom.

1250
01:02:50,280 --> 01:02:52,920
Speaker 2: Ever told You, and early days were the hardest.

1251
01:02:52,920 --> 01:02:54,880
Speaker 1: Like I go back and listen to some of those

1252
01:02:54,920 --> 01:02:57,840
Speaker 1: episodes and I don't know what the hell I was

1253
01:02:57,840 --> 01:03:00,600
Speaker 1: talking about, But really you just had to learn.

1254
01:03:00,640 --> 01:03:02,360
Speaker 2: You just had to like flex the muscle, and.

1255
01:03:02,360 --> 01:03:05,720
Speaker 1: Like the more the more exposure therapy to your own voice,

1256
01:03:05,800 --> 01:03:08,640
Speaker 1: the more you become kind of more confident about how

1257
01:03:08,680 --> 01:03:11,600
Speaker 1: you speak. And really this the more that you know

1258
01:03:11,960 --> 01:03:14,840
Speaker 1: and feel strongly about what you have to say, it's like, really,

1259
01:03:15,240 --> 01:03:18,160
Speaker 1: that's if anybody out there listening is thinking about becoming

1260
01:03:18,240 --> 01:03:21,280
Speaker 1: a podcast or wants a job and podcasting or media,

1261
01:03:21,360 --> 01:03:24,080
Speaker 1: I would say like eighty percent of it is having

1262
01:03:24,080 --> 01:03:26,120
Speaker 1: a point of view and being able to express it

1263
01:03:26,160 --> 01:03:29,200
Speaker 1: clearly and having confidence in what you say. I'm a

1264
01:03:29,320 --> 01:03:32,320
Speaker 1: thousand for sure that not everybody listening agrees to every

1265
01:03:32,320 --> 01:03:34,720
Speaker 1: take that I have. I hear about it sometimes when

1266
01:03:34,760 --> 01:03:36,440
Speaker 1: people don't, and I am grateful for that, so I

1267
01:03:36,760 --> 01:03:39,240
Speaker 1: can confirm that to be true. But I think if

1268
01:03:39,240 --> 01:03:42,000
Speaker 1: you can present your point of view and say here's

1269
01:03:42,040 --> 01:03:44,800
Speaker 1: how I feel, what do you think people really respond

1270
01:03:44,840 --> 01:03:47,680
Speaker 1: to that? And so yeah, I came to being a

1271
01:03:47,720 --> 01:03:51,960
Speaker 1: host in sort of a roundabout way, but it's not anything.

1272
01:03:52,000 --> 01:03:55,520
Speaker 1: I'm not doing anything that is particularly special or challenging.

1273
01:03:55,920 --> 01:03:59,480
Speaker 1: I firmly believe that podcasting is one of the more

1274
01:03:59,560 --> 01:04:05,000
Speaker 1: forgiving mediums because people it's it's long forms, so people

1275
01:04:05,040 --> 01:04:06,880
Speaker 1: really have to engage with what you have to say.

1276
01:04:06,920 --> 01:04:10,240
Speaker 1: And even the podcast that I listen to every week

1277
01:04:10,240 --> 01:04:12,320
Speaker 1: and I'm obsessed with, I don't always agree with what

1278
01:04:12,360 --> 01:04:15,680
Speaker 1: they say, but there's something about hearing somebody exploring express

1279
01:04:15,720 --> 01:04:18,360
Speaker 1: themselves and explain themselves in their own words and make

1280
01:04:18,400 --> 01:04:18,920
Speaker 1: a case for.

1281
01:04:18,880 --> 01:04:21,600
Speaker 2: How they feel in you.

1282
01:04:21,800 --> 01:04:24,000
Speaker 1: If they tweet, if they candense that into a tweet,

1283
01:04:24,000 --> 01:04:26,280
Speaker 1: it's so easy, or a short form post, it's so

1284
01:04:26,320 --> 01:04:28,120
Speaker 1: easy to be like I don't agree, and like now

1285
01:04:28,120 --> 01:04:31,960
Speaker 1: we're in a flame war. Podcasting people, really, it's just

1286
01:04:32,000 --> 01:04:35,160
Speaker 1: a different the people who listen to podcasts, people who

1287
01:04:35,160 --> 01:04:37,640
Speaker 1: make them. It's just a different kind of space. People

1288
01:04:37,680 --> 01:04:41,960
Speaker 1: are very forgiving. People want to hear challenging attitudes and opinions,

1289
01:04:42,000 --> 01:04:44,480
Speaker 1: and I don't know, I'm lucky that this is the

1290
01:04:44,520 --> 01:04:47,640
Speaker 1: medium that I'm in. We did a whole meeting with

1291
01:04:47,760 --> 01:04:50,880
Speaker 1: cool Zone in the wake of Charlie Kirk's death, where

1292
01:04:51,040 --> 01:04:53,640
Speaker 1: one of the things that came up was how you

1293
01:04:53,680 --> 01:04:59,120
Speaker 1: know there is something about it where you know we're

1294
01:04:59,120 --> 01:05:01,000
Speaker 1: not like I don't want to I don't want to

1295
01:05:01,000 --> 01:05:02,760
Speaker 1: say the wrong thing and like diminish the work of

1296
01:05:02,800 --> 01:05:06,160
Speaker 1: any other creator, but like we're not like drama YouTubers

1297
01:05:06,240 --> 01:05:06,680
Speaker 1: or anything.

1298
01:05:06,760 --> 01:05:06,920
Speaker 2: Right.

1299
01:05:07,240 --> 01:05:09,920
Speaker 1: I think that podcasting the reason why I'm a podcaster

1300
01:05:10,000 --> 01:05:11,520
Speaker 1: and I feel very lucky to be in this space

1301
01:05:11,600 --> 01:05:13,600
Speaker 1: is that people listen to what you have to say,

1302
01:05:13,640 --> 01:05:16,280
Speaker 1: and it's like a long form medium and if somebody

1303
01:05:16,360 --> 01:05:21,320
Speaker 1: really wants to, you know, be combad about your opinion.

1304
01:05:21,400 --> 01:05:22,880
Speaker 1: They have to listen to like an hour of You

1305
01:05:23,000 --> 01:05:26,440
Speaker 1: Speak plus ads. And I think it's so different from

1306
01:05:27,040 --> 01:05:30,600
Speaker 1: other communities online, like the YouTube community, which I really

1307
01:05:30,680 --> 01:05:32,640
Speaker 1: admire and I love and I'm not putting anybody down

1308
01:05:32,680 --> 01:05:34,360
Speaker 1: who is part of it, but I know it's not

1309
01:05:34,520 --> 01:05:38,000
Speaker 1: for me because YouTube has this culture of you know,

1310
01:05:38,640 --> 01:05:42,160
Speaker 1: I'm gonna respond to what this other creator said, and

1311
01:05:42,200 --> 01:05:44,560
Speaker 1: then me responding to that creator, and then it's like

1312
01:05:44,560 --> 01:05:47,040
Speaker 1: you there's so many levels where you don't even remember

1313
01:05:47,080 --> 01:05:49,000
Speaker 1: the take that somebody is responding to anymore.

1314
01:05:49,320 --> 01:05:51,480
Speaker 2: That's that is so not my ministry.

1315
01:05:51,520 --> 01:05:54,720
Speaker 1: And I think that being in podcasting as a medium,

1316
01:05:54,720 --> 01:05:59,040
Speaker 1: I think it like is a little bit protective of

1317
01:05:59,680 --> 01:06:02,600
Speaker 1: some of the kind of back and forth that happens

1318
01:06:02,640 --> 01:06:03,840
Speaker 1: in other medium.

1319
01:06:09,640 --> 01:06:09,800
Speaker 3: More.

1320
01:06:09,840 --> 01:06:10,560
Speaker 2: After a quick.

1321
01:06:10,360 --> 01:06:27,240
Speaker 6: Break, let's get right back into it, all right, So

1322
01:06:27,280 --> 01:06:28,640
Speaker 6: this is our final question.

1323
01:06:29,040 --> 01:06:32,880
Speaker 4: Scarlet wrote in with a really great set of four

1324
01:06:32,920 --> 01:06:36,080
Speaker 4: different questions that we're gonna do as a bit of

1325
01:06:36,200 --> 01:06:39,360
Speaker 4: a lightning round. So I'll read first question, and then

1326
01:06:39,680 --> 01:06:44,080
Speaker 4: we'll each go around and say our answers, and we

1327
01:06:44,200 --> 01:06:48,440
Speaker 4: have like, let's say, like sixty seconds to justify your answer.

1328
01:06:50,080 --> 01:06:51,240
Speaker 4: How's that sounds that sound good?

1329
01:06:51,280 --> 01:06:52,960
Speaker 2: That sounds good. That's that sounds good to me?

1330
01:06:53,680 --> 01:06:57,520
Speaker 4: Okay, so Scarlet writes, I've been listening to your show

1331
01:06:57,560 --> 01:06:59,480
Speaker 4: for about two years now. You're one of my favorite

1332
01:06:59,520 --> 01:07:03,680
Speaker 4: Paraso podcast friends. I enjoy it, appreciate the thoughtful analysis,

1333
01:07:03,720 --> 01:07:06,240
Speaker 4: empathy and curiosity you bring to tech news, cutting through

1334
01:07:06,280 --> 01:07:10,440
Speaker 4: the BS cult of capitalism. Thank you, Scarlet. Okay, so

1335
01:07:10,760 --> 01:07:15,120
Speaker 4: here's the questions Joey Europe. First, what is your favorite

1336
01:07:15,120 --> 01:07:16,880
Speaker 4: movie with tech e themes and why?

1337
01:07:17,840 --> 01:07:18,959
Speaker 2: First thing that comes to mind.

1338
01:07:19,600 --> 01:07:21,400
Speaker 3: I have mentioned on the show before, I am a

1339
01:07:21,480 --> 01:07:24,480
Speaker 3: big fan of the movie ex makina A.

1340
01:07:25,440 --> 01:07:27,520
Speaker 2: I love Oscar Eyes. I'll watch anything that he's in.

1341
01:07:28,200 --> 01:07:32,480
Speaker 3: But b I think the ways that movie talks about

1342
01:07:32,920 --> 01:07:38,360
Speaker 3: technological advancements and like the capitalism behind tech, you know,

1343
01:07:38,520 --> 01:07:40,360
Speaker 3: that whole sort of thing, but also like how that

1344
01:07:40,480 --> 01:07:43,920
Speaker 3: pertains to like sex and sexuality and like exploitation of

1345
01:07:43,920 --> 01:07:48,240
Speaker 3: women and women's bodies. That really spoke to you when

1346
01:07:48,280 --> 01:07:49,960
Speaker 3: I saw that movie, and that was like one of

1347
01:07:50,000 --> 01:07:52,439
Speaker 3: the first movies that I saw that really dived into

1348
01:07:52,440 --> 01:07:52,920
Speaker 3: that topic.

1349
01:07:53,040 --> 01:07:55,320
Speaker 2: So yeah, big fan of that movie, love that movie.

1350
01:07:55,840 --> 01:07:57,280
Speaker 3: One more really quick that I want to shout out

1351
01:07:57,280 --> 01:07:58,880
Speaker 3: it's kind of an anti favorite. Oh well, no, it's

1352
01:07:58,880 --> 01:08:00,640
Speaker 3: more like a movie that used to go to my

1353
01:08:00,640 --> 01:08:02,960
Speaker 3: favorites and that was disappointed me. And that is the

1354
01:08:03,000 --> 01:08:07,120
Speaker 3: Ironman franchise, particularly the first Ironman movie.

1355
01:08:08,200 --> 01:08:10,160
Speaker 2: I have talked about on the show before. I've I've

1356
01:08:10,200 --> 01:08:12,520
Speaker 2: talked about this on the show before. I've also mentioned

1357
01:08:12,560 --> 01:08:14,880
Speaker 2: many times I'm a big Marvel fan. I'm stilso to

1358
01:08:14,920 --> 01:08:16,000
Speaker 2: say I'm a big Marvel fan.

1359
01:08:16,479 --> 01:08:18,360
Speaker 3: I used to love that movie when I was a kid,

1360
01:08:18,800 --> 01:08:20,919
Speaker 3: and I honestly, any time.

1361
01:08:20,720 --> 01:08:23,040
Speaker 2: I try to watch it now, it just feels so

1362
01:08:23,160 --> 01:08:27,200
Speaker 2: depressing because it is such a product of its time.

1363
01:08:27,320 --> 01:08:30,080
Speaker 3: It is such a like most superhero movies are very

1364
01:08:30,320 --> 01:08:33,720
Speaker 3: pro military industrial complex, like to an extent, this is

1365
01:08:33,800 --> 01:08:36,600
Speaker 3: like the poster child of that. It is such a

1366
01:08:36,640 --> 01:08:39,400
Speaker 3: portrait of just the like Afghanistan.

1367
01:08:38,760 --> 01:08:42,080
Speaker 2: War, Iraq War era, War on Terror.

1368
01:08:41,800 --> 01:08:45,560
Speaker 3: All of that, and watching it now back it's like

1369
01:08:45,640 --> 01:08:48,160
Speaker 3: it's a movie about like a tech billionaire being really

1370
01:08:48,160 --> 01:08:51,160
Speaker 3: cool and you know, I don't know, some of that

1371
01:08:51,240 --> 01:08:55,720
Speaker 3: stuff didn't really age super well in our current world that.

1372
01:08:55,640 --> 01:08:56,240
Speaker 4: We're living in.

1373
01:08:56,360 --> 01:08:59,160
Speaker 2: It is all I'm saying. But yeah, that's my second

1374
01:08:59,160 --> 01:09:02,080
Speaker 2: answer that question. I can't leave it at one. Sorry,

1375
01:09:02,840 --> 01:09:05,240
Speaker 2: I have to say I've never seen an iron Man movie.

1376
01:09:05,760 --> 01:09:07,759
Speaker 3: We've talked about this because I feel like we should

1377
01:09:07,800 --> 01:09:11,360
Speaker 3: do a watch party at some point, and definitely because

1378
01:09:11,439 --> 01:09:13,680
Speaker 3: I want to hear your thoughts. There's a lot of

1379
01:09:13,720 --> 01:09:16,240
Speaker 3: weird like Post nine a Live and racism and shit

1380
01:09:16,360 --> 01:09:18,360
Speaker 3: that it's it's interesting.

1381
01:09:18,400 --> 01:09:20,759
Speaker 2: It isn't interesting. It's interesting to see how it aged,

1382
01:09:21,000 --> 01:09:22,000
Speaker 2: you know it is.

1383
01:09:23,880 --> 01:09:25,720
Speaker 4: It's wild to think that that movie is over twenty

1384
01:09:25,840 --> 01:09:26,280
Speaker 4: years old.

1385
01:09:26,320 --> 01:09:29,280
Speaker 2: It is over. It really is. It is. No one

1386
01:09:29,360 --> 01:09:34,479
Speaker 2: is not. No one is not. Nor is that is that?

1387
01:09:34,680 --> 01:09:36,800
Speaker 2: It is not? I'm twenty six. It came out in

1388
01:09:36,840 --> 01:09:37,559
Speaker 2: two thousand and eight.

1389
01:09:38,160 --> 01:09:43,719
Speaker 4: On that way, okay, okay, but it can buy cigarettes, okay.

1390
01:09:43,880 --> 01:09:47,200
Speaker 4: Moving along with the Lightning round, bridget, what is your

1391
01:09:47,240 --> 01:09:48,559
Speaker 4: favorite movie with teching themes?

1392
01:09:48,600 --> 01:09:51,280
Speaker 2: And why Eternal Sunshine of a Spotless Mind.

1393
01:09:51,680 --> 01:09:53,639
Speaker 1: You might not be thinking of it as a tech movie,

1394
01:09:53,680 --> 01:09:55,760
Speaker 1: but it's a tech movie kind of the same way

1395
01:09:55,800 --> 01:09:58,080
Speaker 1: that the movie hurts a tech movie. I like movies

1396
01:09:58,120 --> 01:10:01,559
Speaker 1: that don't necessarily feel like tech movies, but are about

1397
01:10:02,000 --> 01:10:05,800
Speaker 1: new technologies and the way that they would actually you know,

1398
01:10:06,439 --> 01:10:09,639
Speaker 1: shape our lives. I think that oftentimes when we're talking

1399
01:10:09,680 --> 01:10:12,760
Speaker 1: about packet feels very sci fi. I like that the

1400
01:10:12,800 --> 01:10:15,880
Speaker 1: movie shows all of the emotional hang ups and relational

1401
01:10:15,920 --> 01:10:18,040
Speaker 1: hang ups, so that that that that kind of the

1402
01:10:18,080 --> 01:10:21,240
Speaker 1: availability of that kind of technology might actually show. And

1403
01:10:21,280 --> 01:10:24,639
Speaker 1: I like it because again, oftentimes, when we're talking about tech,

1404
01:10:24,680 --> 01:10:29,080
Speaker 1: I feel like we poo pooh that sort of everyday waste.

1405
01:10:29,120 --> 01:10:33,439
Speaker 1: That technology keeps you from getting over your X or

1406
01:10:33,680 --> 01:10:37,400
Speaker 1: helps you get over your ex. So I like the applicable,

1407
01:10:37,600 --> 01:10:40,479
Speaker 1: real world application of tech in that in that universe.

1408
01:10:40,800 --> 01:10:43,280
Speaker 4: It's funny you say Eternal Sunshine because like, so, I

1409
01:10:43,320 --> 01:10:44,840
Speaker 4: do really like that movie. But the first time I

1410
01:10:44,880 --> 01:10:47,519
Speaker 4: watched it, I was like actively a grand student in

1411
01:10:47,560 --> 01:10:50,360
Speaker 4: a neuroscience lab, and I was like, it doesn't work

1412
01:10:50,439 --> 01:10:51,840
Speaker 4: like that, Like, oh.

1413
01:10:51,720 --> 01:10:52,920
Speaker 2: No, shit, it doesn't work that way.

1414
01:10:53,000 --> 01:10:56,479
Speaker 3: Well, I haven't seen it, so maybe we'll do an episode.

1415
01:10:56,560 --> 01:10:58,400
Speaker 2: O way, Okay, you have to see it.

1416
01:10:58,479 --> 01:11:01,560
Speaker 4: But I h favorite teching movie. I'm gonna go with

1417
01:11:01,680 --> 01:11:02,479
Speaker 4: Terminator two.

1418
01:11:03,000 --> 01:11:04,160
Speaker 2: Oh that's a good one.

1419
01:11:04,520 --> 01:11:06,840
Speaker 4: I don't know how y'all just like left that sitting

1420
01:11:06,880 --> 01:11:07,240
Speaker 4: out there.

1421
01:11:07,400 --> 01:11:09,559
Speaker 2: I actually still have you to see Terminator too.

1422
01:11:09,720 --> 01:11:11,040
Speaker 4: Oh wow, you should watch it.

1423
01:11:11,080 --> 01:11:14,519
Speaker 2: I saw, I did watch the first one recently, So.

1424
01:11:15,400 --> 01:11:20,080
Speaker 4: I mean it's like genre defining and it's just like

1425
01:11:20,120 --> 01:11:22,960
Speaker 4: a really good movie. It's really fun, action packed.

1426
01:11:23,520 --> 01:11:23,640
Speaker 6: Uh.

1427
01:11:25,200 --> 01:11:27,599
Speaker 4: And also I think it's that some of those like

1428
01:11:27,960 --> 01:11:30,120
Speaker 4: themes that Joey was talking about with the Iron Man

1429
01:11:30,320 --> 01:11:36,160
Speaker 4: of uh, like military industrial complex, Uh, some of the

1430
01:11:36,360 --> 01:11:43,320
Speaker 4: like more nightmare scary scenarios of AI. You know, it

1431
01:11:43,360 --> 01:11:47,759
Speaker 4: feels surprisingly relevant. And also it deals with time travel,

1432
01:11:47,840 --> 01:11:51,000
Speaker 4: which is just a personal favorite topic of mine. Like

1433
01:11:51,479 --> 01:11:54,639
Speaker 4: pretty much any movie that involves time travel, I'm gonna

1434
01:11:54,640 --> 01:11:55,400
Speaker 4: watch and enjoy.

1435
01:11:56,080 --> 01:12:00,559
Speaker 1: Also, the entire like all of humanity is saying by

1436
01:12:01,080 --> 01:12:03,479
Speaker 1: that kid who played Buttneck on Salute your Shorts, the

1437
01:12:03,600 --> 01:12:07,880
Speaker 1: like Redhead kid by knowing instinctively how lie to the cops?

1438
01:12:07,920 --> 01:12:09,840
Speaker 2: Where it's like have you seen this kid? No? I

1439
01:12:09,880 --> 01:12:10,519
Speaker 2: don't know him.

1440
01:12:10,920 --> 01:12:14,360
Speaker 1: You no, Like thank God for lying to the police.

1441
01:12:15,320 --> 01:12:17,439
Speaker 4: All right. So the final question in the lightning round,

1442
01:12:17,760 --> 01:12:20,200
Speaker 4: h Scarlet put us up to this, so we have

1443
01:12:20,280 --> 01:12:24,080
Speaker 4: to do it. Uh. It's a popular game that people

1444
01:12:24,200 --> 01:12:28,040
Speaker 4: probably know because we are broadcasting. We're gonna call it

1445
01:12:28,360 --> 01:12:32,680
Speaker 4: fuck Mary Exile. So we list three people. One of

1446
01:12:32,720 --> 01:12:34,000
Speaker 4: them you have to fuck the other one you have

1447
01:12:34,040 --> 01:12:36,679
Speaker 4: to marry, and then the other one just gets exiled somewhere,

1448
01:12:36,720 --> 01:12:38,559
Speaker 4: maybe to Mars. I don't know, but you know.

1449
01:12:38,520 --> 01:12:40,679
Speaker 2: The implication of what's happening.

1450
01:12:40,960 --> 01:12:47,800
Speaker 4: You know the implication. So Dennis, I mean, Joey must

1451
01:12:47,880 --> 01:12:49,000
Speaker 4: be okay.

1452
01:12:51,640 --> 01:12:53,559
Speaker 3: No, I can't even come up with you with another

1453
01:12:53,680 --> 01:12:56,240
Speaker 3: character in that because the Dennis is the worst. Subjectively,

1454
01:12:57,439 --> 01:13:01,160
Speaker 3: I think I'm more of a Charlie and I'm a I.

1455
01:13:04,200 --> 01:13:04,519
Speaker 2: Thank you.

1456
01:13:07,439 --> 01:13:09,479
Speaker 4: Uh, that's a question for their day.

1457
01:13:09,479 --> 01:13:14,559
Speaker 2: Which characters character? Yeah, yeah, I'm Frank.

1458
01:13:16,560 --> 01:13:23,280
Speaker 4: Yes, can confirm Bridget is Frank. Uh, all right, So Joey,

1459
01:13:23,479 --> 01:13:27,760
Speaker 4: you are up. Musk, Zuckerberg, Besos fuck Merry exile.

1460
01:13:28,520 --> 01:13:30,760
Speaker 2: Exile Musk, fuck that.

1461
01:13:31,000 --> 01:13:35,320
Speaker 3: I'm sorry, he I they're all objectively bad.

1462
01:13:35,400 --> 01:13:36,200
Speaker 2: But here's the thing.

1463
01:13:36,320 --> 01:13:38,880
Speaker 3: There's something about Elon Musk that I know that if

1464
01:13:38,920 --> 01:13:41,280
Speaker 3: I had to be in a room with him for

1465
01:13:41,320 --> 01:13:44,679
Speaker 3: more than like ten seconds, like hands would be thrown.

1466
01:13:45,400 --> 01:13:48,720
Speaker 3: This is not illegal. I'm not legally saying this is

1467
01:13:48,760 --> 01:13:51,120
Speaker 3: what I would do. However, hands would be thrown and

1468
01:13:51,160 --> 01:13:58,040
Speaker 3: things would be happening. Whatever Elon Musk exiled Bezos, I

1469
01:13:58,040 --> 01:14:01,599
Speaker 3: would marry him because you know what I saw, what his.

1470
01:14:01,560 --> 01:14:04,479
Speaker 2: Ex wife got and the and the divorce. I feel

1471
01:14:04,479 --> 01:14:09,120
Speaker 2: like he I could figure out a prenup that would work.

1472
01:14:09,400 --> 01:14:13,520
Speaker 3: Uh, it pays exactly Soccerberg.

1473
01:14:15,200 --> 01:14:19,839
Speaker 2: I guess he's the buck because you know what, I.

1474
01:14:18,600 --> 01:14:23,120
Speaker 3: If it's if it's Jesse Eisenberg as Soccerberg perfect.

1475
01:14:22,800 --> 01:14:25,880
Speaker 4: You can just close your eyes and pretend exactly thank

1476
01:14:25,920 --> 01:14:27,320
Speaker 4: you for your candor thank you.

1477
01:14:27,680 --> 01:14:28,840
Speaker 2: Who do you got, Mike?

1478
01:14:28,920 --> 01:14:33,200
Speaker 4: I'm I I know, yeah, I mean, I think I'm

1479
01:14:33,200 --> 01:14:36,120
Speaker 4: actually gonna go with the same set as Joey. Uh

1480
01:14:36,360 --> 01:14:38,760
Speaker 4: must cast to get out of there, just exile him.

1481
01:14:39,000 --> 01:14:45,040
Speaker 4: He wants to go to Mars any Uh, Bezos would

1482
01:14:45,320 --> 01:14:49,320
Speaker 4: probably marry just because he seems like the least psychopathic

1483
01:14:49,360 --> 01:14:51,720
Speaker 4: of them all. Maybe that makes him the most psychopathic.

1484
01:14:51,800 --> 01:14:55,040
Speaker 4: I don't know, but like, I feel you could have

1485
01:14:55,280 --> 01:14:58,320
Speaker 4: an enjoyable evening with Bezos in a way that would

1486
01:14:58,360 --> 01:15:01,360
Speaker 4: just not be possible with the other. And then that

1487
01:15:01,439 --> 01:15:06,240
Speaker 4: leaves me banging Zuckerberg, which like I'm definitely not excited about.

1488
01:15:07,880 --> 01:15:09,240
Speaker 4: But he does like work out a lot.

1489
01:15:09,320 --> 01:15:15,200
Speaker 1: I guess, so I'm stuck too. I love that exiling Musk.

1490
01:15:15,520 --> 01:15:17,320
Speaker 1: That's an easy one for all of us who're like,

1491
01:15:17,360 --> 01:15:18,120
Speaker 1: get him out of here.

1492
01:15:18,240 --> 01:15:20,800
Speaker 3: None of us want to have any sexual relations with

1493
01:15:20,880 --> 01:15:21,559
Speaker 3: Elon Musk.

1494
01:15:22,080 --> 01:15:22,240
Speaker 2: All.

1495
01:15:23,120 --> 01:15:25,600
Speaker 4: There was a I think a poll on X the

1496
01:15:25,640 --> 01:15:30,160
Speaker 4: other night that like, you're sitting next to Elon Muskin,

1497
01:15:30,240 --> 01:15:32,559
Speaker 4: you can say three words, what are your top three words?

1498
01:15:32,760 --> 01:15:35,920
Speaker 4: And the top choice was kill yourself? Now, oh, I

1499
01:15:35,960 --> 01:15:39,120
Speaker 4: saw that. I saw that, which is like pretty mean

1500
01:15:39,240 --> 01:15:42,519
Speaker 4: and like he should not kill himself, but like that's.

1501
01:15:42,600 --> 01:15:45,800
Speaker 2: Goddamn, never tell anybody to kill himself. But also if

1502
01:15:45,840 --> 01:15:46,839
Speaker 2: you're in anyone.

1503
01:15:47,080 --> 01:15:51,320
Speaker 1: I mean, I will say I there's not even part

1504
01:15:51,479 --> 01:15:53,680
Speaker 1: Like I was like, well, is it is there a

1505
01:15:53,840 --> 01:15:57,400
Speaker 1: because like you don't have to like somebody or like

1506
01:15:57,520 --> 01:16:00,760
Speaker 1: enjoy somebody's company to be in just died in what

1507
01:16:00,960 --> 01:16:03,439
Speaker 1: sex with them would be like? And I keep asking myself,

1508
01:16:03,840 --> 01:16:07,320
Speaker 1: is there any is there any reality? Unfortunately for me,

1509
01:16:07,680 --> 01:16:11,240
Speaker 1: I mean maybe maybe that's just me. Maybe that's just.

1510
01:16:11,240 --> 01:16:13,559
Speaker 2: Me to have any interests in somebody that want to

1511
01:16:13,560 --> 01:16:15,840
Speaker 2: have sex with the todd go on.

1512
01:16:16,920 --> 01:16:20,320
Speaker 1: Maybe I'm maybe yeah, maybe I'm alone in this and

1513
01:16:20,360 --> 01:16:22,719
Speaker 1: if if I am, I'll own it. But I keep wondering,

1514
01:16:22,800 --> 01:16:24,880
Speaker 1: so like can I see that ever being the case

1515
01:16:24,920 --> 01:16:28,160
Speaker 1: with Musk I can't even I can't even picture I

1516
01:16:28,200 --> 01:16:31,000
Speaker 1: can't even like, no part of me is even curious,

1517
01:16:31,040 --> 01:16:32,720
Speaker 1: even like a grotesque curiosity.

1518
01:16:32,960 --> 01:16:33,880
Speaker 2: Nothing I don't like.

1519
01:16:33,920 --> 01:16:36,479
Speaker 4: I can't even imagine, like doing drugs with him would

1520
01:16:36,479 --> 01:16:36,880
Speaker 4: be fun.

1521
01:16:37,120 --> 01:16:41,640
Speaker 2: Now crimes girl, are you okay? Please? So Musk, we

1522
01:16:41,720 --> 01:16:46,000
Speaker 2: have to get out of there. It's between marrying Bezos

1523
01:16:46,439 --> 01:16:52,200
Speaker 2: or Zuckerberg or or fucking them. Let me think. Bezos

1524
01:16:52,240 --> 01:16:54,400
Speaker 2: I think treats his wife pretty well.

1525
01:16:54,360 --> 01:16:57,120
Speaker 1: Like I think. I think he sent her in a space.

1526
01:16:57,439 --> 01:17:01,439
Speaker 1: He bought her Vogue allegedly there he's buying her the

1527
01:17:01,479 --> 01:17:01,960
Speaker 1: met ball.

1528
01:17:03,040 --> 01:17:04,600
Speaker 2: I've seen the emails.

1529
01:17:04,160 --> 01:17:07,360
Speaker 1: He wrote to her that are like a live girl girl,

1530
01:17:07,479 --> 01:17:10,760
Speaker 1: you like, like, I guess, seem being married to him,

1531
01:17:11,000 --> 01:17:12,559
Speaker 1: So I guess, But I don't want to have sex

1532
01:17:12,560 --> 01:17:13,480
Speaker 1: with Mark Zuckerberg.

1533
01:17:13,800 --> 01:17:16,640
Speaker 4: He's also sloppy seconds for me and Joey at this

1534
01:17:16,680 --> 01:17:19,520
Speaker 4: point too. Coming in for the scraps.

1535
01:17:19,920 --> 01:17:20,759
Speaker 2: I could pay.

1536
01:17:20,680 --> 01:17:23,880
Speaker 1: Classic Frank, classic Frank. Yeah, you know what, fuck it,

1537
01:17:23,960 --> 01:17:26,840
Speaker 1: I'll go Zuckerberg. I'll go Zuckerberg. I'll be third in

1538
01:17:26,920 --> 01:17:30,360
Speaker 1: line for zuck picture Jessy Eisenberg.

1539
01:17:32,080 --> 01:17:35,840
Speaker 4: So sorry, listeners, listeners, if you are throwing up from

1540
01:17:35,840 --> 01:17:40,760
Speaker 4: this segment, you can thank Scarlett tell Us, which yeah,

1541
01:17:41,640 --> 01:17:46,519
Speaker 4: Philadelphia character. Yes, he is your commil and also which

1542
01:17:46,520 --> 01:17:47,519
Speaker 4: one is all of us?

1543
01:17:47,920 --> 01:17:48,160
Speaker 2: Yeah?

1544
01:17:48,360 --> 01:17:51,840
Speaker 1: Let us know in the Spotify comments your fuck fuck

1545
01:17:52,000 --> 01:17:54,800
Speaker 1: Merry exile, and which always study character you are?

1546
01:17:55,120 --> 01:18:01,840
Speaker 2: I am Frank Joey Is Let's go, oh who am I?

1547
01:18:01,920 --> 01:18:05,599
Speaker 2: Because I think you might be Mac Mac?

1548
01:18:06,720 --> 01:18:10,240
Speaker 4: That feels like a particularly poor fit.

1549
01:18:11,560 --> 01:18:16,479
Speaker 2: We are. Is there a better sitcom? It could be

1550
01:18:16,560 --> 01:18:19,120
Speaker 2: like New Girl or something. Oh, I don't watch that.

1551
01:18:21,960 --> 01:18:25,959
Speaker 1: You're talking about community community, Yeah, I'm I'm I'm somewhere

1552
01:18:26,000 --> 01:18:28,080
Speaker 1: between Abed and Troy.

1553
01:18:28,960 --> 01:18:32,400
Speaker 2: Yeah, I'm somewhere between Abed and Troy. Same uh huh.

1554
01:18:32,560 --> 01:18:35,720
Speaker 3: Yeah. If you're listening to the show, you are probably

1555
01:18:36,680 --> 01:18:39,200
Speaker 3: you're like, I identify somewhere.

1556
01:18:38,880 --> 01:18:41,360
Speaker 2: As like either a Troy or an Abed in the middle.

1557
01:18:41,560 --> 01:18:43,080
Speaker 2: You know, I completely agree.

1558
01:18:43,760 --> 01:18:46,840
Speaker 4: Not a lot of su tun it into their Who's

1559
01:18:46,840 --> 01:18:47,200
Speaker 4: to say?

1560
01:18:47,360 --> 01:18:50,560
Speaker 2: Who's to say?

1561
01:18:48,840 --> 01:18:56,880
Speaker 3: All right, So now we are closing out Bridgin and Mike.

1562
01:18:56,960 --> 01:19:00,479
Speaker 3: I have a question what is your And this is

1563
01:19:00,479 --> 01:19:02,519
Speaker 3: a little bit broad, but if you could have a

1564
01:19:02,760 --> 01:19:08,680
Speaker 3: tech prediction for twenty twenty six, something's gonna happen, what

1565
01:19:08,720 --> 01:19:09,160
Speaker 3: would it be?

1566
01:19:11,000 --> 01:19:12,720
Speaker 2: And it could be anything? If you're like I think

1567
01:19:12,760 --> 01:19:14,920
Speaker 2: they're gonna make a movie that's.

1568
01:19:14,760 --> 01:19:21,800
Speaker 3: All AI and all okay, Leonardo DiCaprio, that's I don't

1569
01:19:21,840 --> 01:19:21,920
Speaker 3: know it.

1570
01:19:22,080 --> 01:19:22,280
Speaker 2: Yeah.

1571
01:19:22,560 --> 01:19:25,040
Speaker 1: I think that the vibes on TikTok are gonna get

1572
01:19:25,400 --> 01:19:29,160
Speaker 1: weird and not so good when the deal goes through

1573
01:19:29,560 --> 01:19:30,880
Speaker 1: for American ownership.

1574
01:19:31,160 --> 01:19:32,439
Speaker 2: I also think all the.

1575
01:19:32,439 --> 01:19:34,760
Speaker 1: Little like things that we all get fed up on

1576
01:19:34,800 --> 01:19:36,080
Speaker 1: that we talk about on the show all the time,

1577
01:19:36,120 --> 01:19:39,320
Speaker 1: things like, you know, dynamic or predictive pricing, things like

1578
01:19:39,680 --> 01:19:41,720
Speaker 1: you know, like oh, when you have a flight and

1579
01:19:41,920 --> 01:19:44,000
Speaker 1: they screw you over to the airport, they don't longer

1580
01:19:44,080 --> 01:19:46,160
Speaker 1: have to give you money. I think I think the

1581
01:19:46,160 --> 01:19:48,400
Speaker 1: consumer is rising up. I think that the consumer has

1582
01:19:48,400 --> 01:19:50,519
Speaker 1: had enough the consumer. We are fed up.

1583
01:19:51,320 --> 01:19:52,000
Speaker 2: I think we are.

1584
01:19:52,439 --> 01:19:55,280
Speaker 1: I think anybody can plainly see that we are all

1585
01:19:55,320 --> 01:19:57,120
Speaker 1: being screwed over. And I think that this is something

1586
01:19:57,160 --> 01:20:00,880
Speaker 1: that has vast like transpartisans and support. I think that

1587
01:20:00,960 --> 01:20:04,320
Speaker 1: no matter where you are ideologically, nobody likes getting screwed over.

1588
01:20:04,680 --> 01:20:06,880
Speaker 1: And I think that the amount of ways that we're

1589
01:20:06,880 --> 01:20:09,439
Speaker 1: all getting screwed over is growing every goddamn day, and

1590
01:20:09,479 --> 01:20:11,080
Speaker 1: so I think that we are going to start seeing

1591
01:20:11,880 --> 01:20:15,120
Speaker 1: more it become a more popular thing that people consumers

1592
01:20:15,160 --> 01:20:18,640
Speaker 1: are rising up against really just the use of technology

1593
01:20:18,760 --> 01:20:22,479
Speaker 1: to siphon every dime. We have to make some rich

1594
01:20:22,520 --> 01:20:25,080
Speaker 1: guy richer. That's my hope, But I also think that

1595
01:20:25,120 --> 01:20:26,519
Speaker 1: might be happening in twenty twenty six.

1596
01:20:27,040 --> 01:20:33,760
Speaker 4: Love it. I am going to predict that we in

1597
01:20:33,800 --> 01:20:37,240
Speaker 4: twenty twenty six, we will see the AI hype bubble

1598
01:20:39,000 --> 01:20:41,840
Speaker 4: start to burst, And I think it's gonna burst in

1599
01:20:42,040 --> 01:20:46,840
Speaker 4: like unusual ways, Like I don't think all of a

1600
01:20:46,880 --> 01:20:49,280
Speaker 4: sudden one day, Invidious stock is going to drop to

1601
01:20:49,400 --> 01:20:52,559
Speaker 4: zero and like nobody's gonna ever use AI again, Like

1602
01:20:52,600 --> 01:20:54,640
Speaker 4: obviously I don't think it's gonna be like that, But

1603
01:20:55,160 --> 01:21:00,639
Speaker 4: I think we're already seeing people, the p of people

1604
01:21:00,640 --> 01:21:07,160
Speaker 4: pushing back against AI gaining traction and consensus forming that

1605
01:21:08,200 --> 01:21:16,759
Speaker 4: actually audiences and workers do not want AI slop shoved

1606
01:21:16,760 --> 01:21:22,680
Speaker 4: to them from like every screen that is possible, and

1607
01:21:23,000 --> 01:21:25,280
Speaker 4: in fact, there are a lot of things that people

1608
01:21:25,479 --> 01:21:30,479
Speaker 4: are trying to force AI into our lives to do

1609
01:21:30,920 --> 01:21:36,080
Speaker 4: that it's just like really categorically bad at doing. And

1610
01:21:36,120 --> 01:21:39,360
Speaker 4: so I'm I guess optimistic that in twenty twenty six

1611
01:21:40,760 --> 01:21:46,360
Speaker 4: we will see that like absurd hype really start to

1612
01:21:47,160 --> 01:21:52,400
Speaker 4: tamp down and course correct in some kind.

1613
01:21:52,200 --> 01:21:54,000
Speaker 2: Of way, I hope.

1614
01:21:54,080 --> 01:21:56,599
Speaker 1: So, I mean that kind of speaks to my prediction,

1615
01:21:56,760 --> 01:22:00,000
Speaker 1: and I think I think shit has to course correct.

1616
01:22:00,479 --> 01:22:01,920
Speaker 2: Everybody hates where we're going.

1617
01:22:04,040 --> 01:22:07,840
Speaker 3: Yeah, yeah, I was gonna say, I mean mine was

1618
01:22:07,880 --> 01:22:10,439
Speaker 3: going to be which adding on to that, I think

1619
01:22:10,520 --> 01:22:11,680
Speaker 3: the AI.

1620
01:22:13,520 --> 01:22:17,560
Speaker 2: Entertainment industry emphasis specifically.

1621
01:22:19,400 --> 01:22:22,880
Speaker 3: My hope again, my hope who's the disabled will actually

1622
01:22:22,880 --> 01:22:25,240
Speaker 3: happen is that that's gonna just like fall apart, because

1623
01:22:25,240 --> 01:22:27,200
Speaker 3: I feel like that's something recently that I see that

1624
01:22:27,240 --> 01:22:29,880
Speaker 3: I'm like, it makes me so sad to see, like

1625
01:22:30,560 --> 01:22:34,040
Speaker 3: this is something that is such a like beautiful expression

1626
01:22:34,040 --> 01:22:37,040
Speaker 3: of like creative output and then and and like yet

1627
01:22:37,320 --> 01:22:41,479
Speaker 3: we are turning into computers or whatever. It's there's creatives

1628
01:22:41,479 --> 01:22:43,679
Speaker 3: that I really love, who I've really respected for years

1629
01:22:43,680 --> 01:22:45,920
Speaker 3: and an how are like, actually AI is great and

1630
01:22:45,960 --> 01:22:49,000
Speaker 3: I'm like, this is really disappointing to see.

1631
01:22:49,439 --> 01:22:52,040
Speaker 2: Uh So I don't know that's yeah, no, I agree

1632
01:22:52,080 --> 01:22:52,680
Speaker 2: with all of you.

1633
01:22:54,360 --> 01:23:01,080
Speaker 3: I My hope my prediction is just that, you know,

1634
01:23:01,200 --> 01:23:03,680
Speaker 3: it's interesting. I feel like this whole decade has kind

1635
01:23:03,680 --> 01:23:08,120
Speaker 3: of been a whole like people like young people are

1636
01:23:08,200 --> 01:23:12,800
Speaker 3: rejecting all of these new technological advances there are more

1637
01:23:12,920 --> 01:23:15,720
Speaker 3: like analog methods, and I think there is going to

1638
01:23:15,760 --> 01:23:17,400
Speaker 3: be a continuation of that, Like I do.

1639
01:23:17,520 --> 01:23:18,920
Speaker 2: I do really think there is going to be a

1640
01:23:18,960 --> 01:23:19,720
Speaker 2: continuation of that.

1641
01:23:20,320 --> 01:23:23,920
Speaker 3: I have a like disposalle camera that I've been using

1642
01:23:24,360 --> 01:23:26,080
Speaker 3: that I was like I with friends last night that

1643
01:23:26,120 --> 01:23:29,840
Speaker 3: I was taking pictures with for Thanksgiving this past month.

1644
01:23:30,240 --> 01:23:32,000
Speaker 2: I had it out with some cousins and.

1645
01:23:31,960 --> 01:23:34,360
Speaker 3: They were like, oh my god, like wait, I heard

1646
01:23:34,400 --> 01:23:36,200
Speaker 3: that was like a thing with this, like like the

1647
01:23:36,320 --> 01:23:39,240
Speaker 3: young people are taking photos with the analog cameras. Again,

1648
01:23:39,320 --> 01:23:41,599
Speaker 3: I'm like yeah, because like literally I don't have any

1649
01:23:41,600 --> 01:23:43,800
Speaker 3: physical photos to like me and my friends. And that

1650
01:23:43,920 --> 01:23:46,519
Speaker 3: was something recently that like had motivated me to be

1651
01:23:46,640 --> 01:23:49,000
Speaker 3: like I want to bring this camera out. I want

1652
01:23:49,040 --> 01:23:49,960
Speaker 3: to get these photos.

1653
01:23:50,600 --> 01:23:51,680
Speaker 2: Uh.

1654
01:23:51,800 --> 01:23:55,960
Speaker 3: But yeah, I think there is We're at a weird point.

1655
01:23:56,080 --> 01:23:58,519
Speaker 3: We're at a weird point and all this where it's

1656
01:23:58,600 --> 01:24:00,679
Speaker 3: like I really do hope there are certain things where

1657
01:24:00,680 --> 01:24:03,559
Speaker 3: it's like, yes, technology is a tool. It helps us

1658
01:24:03,840 --> 01:24:06,280
Speaker 3: deal with all these things that we do need to

1659
01:24:06,320 --> 01:24:09,439
Speaker 3: deal with. But also when it comes to art, when

1660
01:24:09,479 --> 01:24:16,160
Speaker 3: it comes to music, photography, visual art, we're gonna have

1661
01:24:16,200 --> 01:24:19,200
Speaker 3: a sort of researches of people wanting to do these

1662
01:24:19,200 --> 01:24:24,120
Speaker 3: like analog hands on. Thanks so we'll see we'll see

1663
01:24:24,760 --> 01:24:30,000
Speaker 3: what beautiful visions for the future of our shared tech landscape.

1664
01:24:30,520 --> 01:24:33,160
Speaker 1: Mike, Joey, thank you for this. Was we took some

1665
01:24:33,960 --> 01:24:37,000
Speaker 1: this is a wild one. Let us know what you

1666
01:24:37,080 --> 01:24:39,920
Speaker 1: all thought about this. We have more emails.

1667
01:24:39,439 --> 01:24:41,000
Speaker 2: To come, so yeah.

1668
01:24:41,160 --> 01:24:44,240
Speaker 1: Thanks to YouTube for taking this sort of walk down

1669
01:24:44,280 --> 01:24:47,559
Speaker 1: memory laying with us, and thanks everyone for listening.

1670
01:24:47,960 --> 01:24:49,599
Speaker 2: Happy New Year, I'll talk to you soon.

1671
01:24:49,800 --> 01:24:50,920
Speaker 4: Happy New Year, everybody.

1672
01:24:51,040 --> 01:24:51,960
Speaker 2: Happy New Year.

1673
01:24:56,920 --> 01:24:59,040
Speaker 1: If you're looking for ways to support the show, check

1674
01:24:59,040 --> 01:25:03,120
Speaker 1: out our workstore tangody dot com slash store. Got a

1675
01:25:03,160 --> 01:25:05,280
Speaker 1: story about an interesting thing in tech, or just want

1676
01:25:05,280 --> 01:25:07,240
Speaker 1: to say hi, You can reach us at Hello at

1677
01:25:07,240 --> 01:25:09,960
Speaker 1: tangody dot com. You can also find transcripts for today's

1678
01:25:10,000 --> 01:25:12,400
Speaker 1: episode at tenggody dot com. There Are No Girls on

1679
01:25:12,439 --> 01:25:14,800
Speaker 1: the Internet was created by me Bridget tod. It's a

1680
01:25:14,800 --> 01:25:18,439
Speaker 1: production of iHeartRadio and Unboss Creative, edited by Joey pat

1681
01:25:19,080 --> 01:25:22,080
Speaker 1: Jonathan Strickland is our executive producer. Tari Harrison is our

1682
01:25:22,120 --> 01:25:25,599
Speaker 1: producer and sound engineer. Michael Almado is our contributing producer.

1683
01:25:25,840 --> 01:25:27,000
Speaker 2: I'm your host. Bridget Todd.

1684
01:25:27,360 --> 01:25:29,080
Speaker 1: If you want to help us grow, rate and review

1685
01:25:29,160 --> 01:25:32,760
Speaker 1: us on Apple podcasts. For more podcasts from iHeartRadio, check

1686
01:25:32,760 --> 01:25:35,120
Speaker 1: out the iHeartRadio app, Apple Podcasts, or wherever you get

1687
01:25:35,120 --> 01:25:35,880
Speaker 1: your podcasts.