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Speaker 1: Coolso Media. Hi everyone, Jamie here. We're taking a week

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Speaker 1: off at cool Zone for the holiday, So this week

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Speaker 1: is going to be a rerun one of the very

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Speaker 1: early episodes of sixteenth Minute on the Dress. I just

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Speaker 1: wanted to say a few things at the top. We

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Speaker 1: will be back next week with I'm thrilled to report

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Speaker 1: because I just did the interview on an interview with

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Speaker 1: the guy from the Wicked Witch of the West, she

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Speaker 1: came down in a bubble Bro video Matt Pacerro. That'll

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Speaker 1: be out next week, followed by our three part series

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Speaker 1: on the Mani Sphere. Thank you so much to everyone

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Speaker 1: who reached out to everyone in the LA area who

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Speaker 1: has been kind enough to come out to my solo show.

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Speaker 1: There is a bonus show that has been announced that

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Speaker 1: will be happening on November twenty ninth at the Lyric

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Speaker 1: Hyperion Theater. We're going to be doing one extra workshop

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Speaker 1: of the show. So if you weren't able to get

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Speaker 1: tickets because all the other shows sold out, feel free

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Speaker 1: to come out this week. Feel free to come out

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Speaker 1: on Friday to the show. That's November twenty ninths. And finally,

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Speaker 1: because Thanksgiving, as I hope you know is a crock

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Speaker 1: of shit. I wanted to encourage everyone in joining me

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Speaker 1: this week in donating and contributing to the Native Women's

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Speaker 1: collective and nonprofit that nurtures the health and safety of

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Speaker 1: Native women in the US. So if you're interested, the

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Speaker 1: link is below, and with that, please enjoy this re

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Speaker 1: release of our episode on the Dress. See you next week. Clickbait.

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Speaker 1: If I had to define it, clickbait is a combination

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Speaker 1: of fake news and a freak show. It was a

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Speaker 1: sign of the declining state of reliable journalism in the

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Speaker 1: Western world and an early symptom of where American journalism

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Speaker 1: finds itself. As I record this, major newsrooms are shuttering

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Speaker 1: or vastly reduced during an election year, and most major

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Speaker 1: newspapers are owned by billionaires who resist criticism, resulting in

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Speaker 1: the remaining papers running on people pleasing fumes, setting cocourage

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Speaker 1: their readers to turn their heads from massive human atrocity.

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Speaker 1: Ten years ago, things were bad, but not as bad,

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Speaker 1: which is something people in the present always say. Ten

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Speaker 1: years from now, we'll be pining for the salad days

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Speaker 1: of twenty twenty four as we enlist our third gradiers

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Speaker 1: in the Water Wars but for now it's true. The

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Speaker 1: clickbait culture of the mid twenty tens was alarming, it

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Speaker 1: worse annoying at best, but it didn't feel existential in

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Speaker 1: quite the same way. The word clickbait was a runner

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Speaker 1: up for the Oxford Dictionary Word of the Year in

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Speaker 1: twenty fourteen, tied with normcore and man's plain. And if

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Speaker 1: there's a more twenty fourteen sentence than that, I am

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Speaker 1: not aware of it. Here are some major headlines you

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Speaker 1: could find at this time. What were in Hillary's emails?

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Speaker 1: We have some guesses. The gritty Power Rangers reboot with

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Speaker 1: James Vanderbeek is the stuff of nightmares. Thirteen unconventional things

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Speaker 1: to do with your Gallantine this year you know garbage

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Speaker 1: and can say I'm being mean because these are headlines

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Speaker 1: I wrote. Come with me if you dare to. Twenty

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Speaker 1: fifteen The Big Short Steve Jobs, the movie the Boring One,

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Speaker 1: not the hilarious Ashton Kutcher one, fifty Shades of Gray.

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Speaker 1: We're at peak, justin Bieber peak, Fettiwop, the year of

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Speaker 1: hotline bling and Hamilton. Obama is rounding out his second term.

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Speaker 1: It's the year he allows an airstrike on a children's

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Speaker 1: hospital in Afghanistan. Gay marriage will be legal across the

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Speaker 1: US this June, and ten days after that, a dumb

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Speaker 1: bitch named Donald Trump will go down and escalator in

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Speaker 1: New York and announce he's wonning for president. I have

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Speaker 1: managed to graduate from college as semester early, and in

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Speaker 1: fighting for my life at my first proper writing job

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Speaker 1: at the Boston Globe. My job, as will become relevant

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Speaker 1: to this story, is writing click bait. Or that's not

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Speaker 1: totally right, because yes, I reported to the Boston Globe building.

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Speaker 1: I ate my grilled Jesus among them, but very rarely

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Speaker 1: was I writing actual news. For the most part, I

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Speaker 1: was creating hashtag clickbait content, very little of which required

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Speaker 1: original reporting. While I technically worked for the Globe and

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Speaker 1: was in their newsroom, I was practically two steps removed.

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Speaker 1: Boston dot Com was the Globe's hyperlocal sister site, and

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Speaker 1: a now defunct vertical called Bdcwire was their clickbait site.

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Speaker 1: I was one of three writers at BDC Wire, populating

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Speaker 1: the site with stories as if there were ten writers,

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Speaker 1: and in twenty fifteen I worked two full time jobs,

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Speaker 1: first at this now defunct website as well as co

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Speaker 1: managing a now defunct improv theater and Cards on the Table.

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Speaker 1: I was fired from The Globe not six months later

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Speaker 1: for refusing to take down a tweet about comm I

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Speaker 1: don't know, you're only twenty two months. I'm getting distracted.

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Speaker 1: Early twenty fifteen, I did. We'd get to do some

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Speaker 1: original reporting here and there, but my main gig was

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Speaker 1: sourcing viral news and rephrasing my sources with citations that

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Speaker 1: sites like these would adorably and deceptively call hat tips.

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Speaker 1: And I'd love to tell you what more of these

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Speaker 1: stories were, but as any journalist who started working in

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Speaker 1: the age of the Internet knows, almost none of it

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Speaker 1: is available now without the assistance of the Internet Archive.

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Speaker 1: BDC Wire is gone, along with those articles I wrote,

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Speaker 1: like ten reasons Chris Evans being from Massachusetts is the

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Speaker 1: one reason not to end at all, or whatever I

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Speaker 1: was reading on today's Internet, Bdcwire never existed, So just

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Speaker 1: a reminder you are listening to a future piece of

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Speaker 1: lost media. But in the mid twenty tens, a lot

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Speaker 1: of writers got their start the same way I did

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Speaker 1: at this time, including probably writers you like now, from

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Speaker 1: young gen xers to elderly zoomers. We were tasked with

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Speaker 1: regurgitating stories that social media cared about and regurgitating them

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Speaker 1: to make them seem like actual news. We weren't making

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Speaker 1: shit up like tabloids, but there was a sense that

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Speaker 1: one writer was vomiting into another writer's mouth, and so

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Speaker 1: on and so on to maximize site traffic and profit.

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Speaker 1: We the writers never got paid equitably, but for places

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Speaker 1: like The Boston Globe and other major news organizations who

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Speaker 1: were hemorrhaging money due to the inability to adapt to

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Speaker 1: the Internet when the moment counted, these clickbait sister sites

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Speaker 1: became a temporary attempt at increasing cash flow, or, as

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Speaker 1: I knew it, tricking a group of twenty two year

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Speaker 1: olds into thinking they were real writers in exchange for

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Speaker 1: bad pay and a content mentality. So basically, I was

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Speaker 1: working for a regional ripoff of early BuzzFeed. And to

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Speaker 1: be clear, I am not conflating BuzzFeed the website with

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Speaker 1: BuzzFeed News, which is a Pulitzer winning and recently tragically

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Speaker 1: shuttered news division. Nor am I saying that working at

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Speaker 1: a BuzzFeed content mill was bad or even uncreative. I mean,

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Speaker 1: I think that my BBC wire magnum opus. I saw

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Speaker 1: Shrek the Musical five times colon. This is my story

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Speaker 1: fucking ripped, not that you can read it anywhere. What's

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Speaker 1: interesting is that this regurgitation media strategy, inspired by BuzzFeed

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Speaker 1: combing the Internet to fill their website full of clickable,

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Speaker 1: eccentric hashtag content, often legitimize Internet characters of the day

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Speaker 1: as legitimate news figures, and this was never more true

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Speaker 1: than in the mid twenty tents. A quick brief on BuzzFeed.

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Speaker 1: At this time, the company had been around since two

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Speaker 1: thousand and six, and its legitimate news arm, BuzzFeed News,

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Speaker 1: wouldn't be launched until a year later in twenty sixteen.

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Speaker 1: Founder Jonah Peretti had made BuzzFeed an algorithmic project from

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Speaker 1: the start. In a twenty thirteen profile of Paretti in

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Speaker 1: New York Magazine, early BuzzFeed is described as Peretti's quote

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Speaker 1: out algorithm to call stories from around the web that

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Speaker 1: were showing stirring the virality. In return for functioning as

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Speaker 1: a sort of early warning system, BuzzFeed persuaded partner sites

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Speaker 1: to install programming code that allowed the company to monitor

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Speaker 1: their traffic. Like a lot of social media we discussed today.

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Speaker 1: Peretti's original project begun while he was working at the

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Speaker 1: similarly click minded Huffington Post, was collecting a shitload of

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Speaker 1: data at best. He wanted to know what people were

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Speaker 1: interested in. If I'm being cynical, he wanted to sell

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Speaker 1: it back to us in an easy to consume package,

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Speaker 1: and we were happy to do it. By twenty fifteen,

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Speaker 1: BuzzFeed had grown exponentially and started creating original content in

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Speaker 1: addition to their bread and Butter, which was both curating

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Speaker 1: and rephrasing viral stories from other corners of the Internet

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Speaker 1: to drive traffic, and one thousand different quizzes on which

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Speaker 1: ice cream flavor you were based on your mental illness

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Speaker 1: diagnosis something like that took them all, no judgment, min

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Speaker 1: chocolate chip, OCD, bipolar whatever. Much of early BuzzFeed was

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Speaker 1: extremely goofy and what I think is now sort of

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Speaker 1: associated as being an embarrassingly millennial thing, but there was

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Speaker 1: no shortage of talent there. Quinta Brentson produced a lot

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Speaker 1: of her early viral stuff at BuzzFeed, and many people

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Speaker 1: in their writing and performance stable ended up bailing on

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Speaker 1: BuzzFeed because they were treated like mill workers and not

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Speaker 1: artists think comedians and writers like Gabe Dunn and Alison

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Speaker 1: Raskin think. Super successful YouTubers like Sophia and Nigard think

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Speaker 1: whether you love them or you hate them for cheating

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Speaker 1: on their wives, the try guys, But regardless of the

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Speaker 1: level of talent, there's no point in denying it. A

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Speaker 1: lot of early BuzzFeed was rehashed stuff, either sent in

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Speaker 1: by users or gently lifted by a fleet of young,

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Speaker 1: aspiring writers like myself to proliferate a sticky story that

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Speaker 1: someone else had posted online for free all ready. The

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Speaker 1: goal show it to a wider audience with some light

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Speaker 1: commentary and yield a massive profit for Daddy BuzzFeed and

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Speaker 1: one of BuzzFeed's greatest main character cosigns in its history

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Speaker 1: came on February twenty sixth, twenty fifteen, a day that

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Speaker 1: launched two huge viral stories. One was about a pair

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Speaker 1: of lamas that escaped in an Arizona retirement home.

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Speaker 2: In Sun City. Today, this may have been the very

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Speaker 2: definition of the Wild West. A slow, sometimes high speed

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Speaker 2: pursuit of two lamas on the loose, breaking away from

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Speaker 2: their owners, at times from each other, seizing their moment

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Speaker 2: and their shot at freedom, And.

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Speaker 1: The other one is one whose impact is still almost

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Speaker 1: bafflingly still enduring today.

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Speaker 3: The dress.

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Speaker 1: Your sixteenth minute starts now sixty.

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Speaker 4: Six.

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Speaker 1: The dress. It's a potent and memorable piece of Internet lore.

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Speaker 1: One where your perception mattered was this dress, which was

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Speaker 1: first posted by Scottish mother of the bride, Cecilia Bleestale,

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Speaker 1: in this weird, blown out photo from a designer outlet

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Speaker 1: in England. Was this dress blue and black? Or was

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Speaker 1: it white and gold? It was blue and black, And

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Speaker 1: I knew that right away, because I'm perfect and I've

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Speaker 1: never made a mistake. And even though it sounds old timey,

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Speaker 1: I mean, after all, we're talking about an optical illusion

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Speaker 1: that resulted from an objectively shitty phone camera. It's kind

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Speaker 1: of hard to overstate what a sensation the dress became.

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Speaker 1: I remember this day so clearly because this story broke

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Speaker 1: my second week working as a professional writer and as

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Speaker 1: a kid who'd been brought in to write clickbait. It

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Speaker 1: was like a gorgeous gift had descended from space. As

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Speaker 1: I was reflecting, I wanted to make sure I wasn't

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Speaker 1: fluffing the memory in my mind, so I reached out

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Speaker 1: to my buddy Kevin Slain, who was one of the

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Speaker 1: other three writers working overtime to create hashtag content on

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Speaker 1: BDC Wire to be read by hashtag nobody for hashtag

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Speaker 1: seventy hours a week, and he remembered this day really

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Speaker 1: clearly too.

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Speaker 4: My name is Kevin Slain, and I am a staff

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Speaker 4: writer at The Boston Globe covering entertainment and culture and

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Speaker 4: what's up? Not much, Jamie, how are you?

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Speaker 5: I am good after all these years.

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Speaker 4: I'm good, real throwback talking to you today about this day.

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Speaker 5: About I know about this historic day that is over

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Speaker 5: nine years ago now, which feels not great, Okay. So

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Speaker 5: I just wanted to go because I feel like I

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Speaker 5: was writing out like how I imagine this day. I

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Speaker 5: think it was like, certainly in my first month working

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Speaker 5: at BDC wire, do you remember the dress day in

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Speaker 5: our little corner?

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Speaker 4: So I remember what I did that day, and at

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Speaker 4: least in my case, we're talking about Thursday, which was

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Speaker 4: kind of like the dress dropped at night, you know.

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Speaker 4: It was the wave the day went for me was

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Speaker 4: I was at work. I wrote a story about the Lamas,

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Speaker 4: which was the big I remember Idi, a predecessor to

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Speaker 4: the dress I dreamed some lamas.

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Speaker 1: I can't find it on the way back, miss, but

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Speaker 1: I was like, okay, okay, Lama's first Lamas are the story.

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Speaker 4: I had to go back through my Twitter archive and

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Speaker 4: I found that I tweeted out the story that I

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Speaker 4: wrote about the lamas. Thank GOHI was just you know,

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Speaker 4: our house style at the time, lots of gifts, lots

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Speaker 4: of old text, just you know, us trying to be BuzzFeed.

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Speaker 3: I guess, yeah.

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Speaker 4: But anyway, so I did that, and then a bunch

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Speaker 4: of us went to a happy hour at the Banshee,

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Speaker 4: which was just where a lot of us went after work,

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Speaker 4: and I proceeded to get really drunk and sing a

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Speaker 4: lot of karaoke, and at some point someone pulled out

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Speaker 4: their phone and started showing it to everyone, being like,

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Speaker 4: check this out. This dress thing is crazy. And I

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Speaker 4: reacted to it the way that I think I did

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Speaker 4: to a lot of that stuff for the time, because

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Speaker 4: this was like our first media job. And I just

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Speaker 4: felt simultaneously like enthralled by the conversation but also repulsed,

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Speaker 4: and I felt, you know, probably undeservedly above it all.

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Speaker 4: And so the thing was that back then they really

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Speaker 4: had like a flat hierarchy in terms of like who

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Speaker 4: could say what, and everyone would just send all staff

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Speaker 4: emails all the time. And I remember pulling out my

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Speaker 4: phone and looking and seeing that our old homepage had

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Speaker 4: like three stories on the dress right on the top,

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Speaker 4: and there was like an active email chain going on

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Speaker 4: about this, and me, very drunk, just was like, this

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Speaker 4: is ridiculous. I can't believe we have three stories on

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Speaker 4: the dress on the homepage. And whoever did that got like,

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Speaker 4: you know, offended that I said that rightfully.

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Speaker 1: So well, I mean that's a lot. I didn't remember

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Speaker 1: there being three stories. But that also makes sense because

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Speaker 1: there were like three different verticals sort of all like

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Speaker 1: going to the same place, and we were all trying

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Speaker 1: to get clicks on the same thing that we were

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Speaker 1: all sort of ripping off.

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Speaker 5: For a BuzzFeed. It was just like weird. It was

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Speaker 5: a weird time, It really was.

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Speaker 4: And I even went and then looked at the like

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Speaker 4: the next day I looked in the wayback machine. It

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Speaker 4: was even more of that. It was like the night

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Speaker 4: producer who wrote like a short little thing, and then

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Speaker 4: our old boss who I won't name, wrote this like

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Speaker 4: very ridiculous in his own voice style post, and then

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Speaker 4: someone else wrote like their take on the dress, and

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Speaker 4: then another of our old bosses then asked John Henry

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Speaker 4: to weigh in about the dress. And there's a video

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Speaker 4: I can't find of him talking about the dress, which

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Speaker 4: I wish I could find, because I think that.

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Speaker 5: What I wish we had the John Henry futage.

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Speaker 4: That's uninged, right, like, who needed that?

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Speaker 5: Well, thank you, thank you for reminiscing with me. This

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Speaker 5: was beautiful.

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Speaker 4: Yes, it's weird to think about now, and I know

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Speaker 4: it's objectively not true. It was a totally different time

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Speaker 4: and you can't help but look back at it fondly,

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Speaker 4: despite the fact that I was hating myself through the

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Speaker 4: entire portion of it.

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Speaker 1: Thanks so much to Kevin, who is a real writer

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Speaker 1: for the Boston Globe and has been for years. So

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Speaker 1: this day was genuinely a huge day for news on

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Speaker 1: and about the Internet. The FCC had just voted to

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Speaker 1: classify Internet service providers as public utilities, effectively creating net neutrality,

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Speaker 1: but the dress was indisputably the main character. Here's the

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Speaker 1: cliff notes of what happened in February twenty fifteen. A

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Speaker 1: Scottish couple was preparing for their wedding and the bride's

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Speaker 1: mother texted her daughter a photo of the dress she

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Speaker 1: was considering wearing the dress. It's not a great picture,

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Speaker 1: but it is a very mid twenty ten's mother of

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Speaker 1: the bride dress. There is this little cropped jacket, some

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Speaker 1: color blocking, unnecessary lace elements. But the color that was

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Speaker 1: the question. The bride, Grace posted the photo of the

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Speaker 1: dress to her Facebook and explained the dilemma. Her mom

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Speaker 1: assured her that the dress was blue with black lace,

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Speaker 1: but Grace was seeing it as white with gold lace,

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Speaker 1: so she posted the question to her Facebook so her

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Speaker 1: friends could weigh in, and a week long debate was sparked.

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Speaker 1: So the dress first became a main character in her

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Speaker 1: small community in colin Say, Scotland. Then the wedding happened

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Speaker 1: and Grace's mom wore the dress. It was a topic

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Speaker 1: of discussion at the wedding too, and it's actually members

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Speaker 1: of the wedding band that take the dress from a

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Speaker 1: local phenomenon into a global one. Singer and guitarist Caitlyn McNeil,

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Speaker 1: who was a close friend of the couples, said of

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Speaker 1: the dress, iurl we forgot about it until we saw

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Speaker 1: it at the wedding which the mother of the bride

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Speaker 1: was wearing, and it was obviously blue and black. In

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Speaker 1: any other timeline, this would be a footnote that Grace's

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Speaker 1: mom would half remember when giving the dress to Goodwill

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Speaker 1: a decade later. But this was a time on the

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Speaker 1: Internet where viral stories were social currency, and Katelyn McNeil

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Speaker 1: had taken up the mantle of the dress. It was

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Speaker 1: her who ended up posing what would become the viral

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Speaker 1: seed that would take this story global. On her tumbler,

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Speaker 1: the post attached to a picture of the dress said, guys,

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Speaker 1: please help me. Is this dress white or gold or

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Speaker 1: blue and black? Me and my friends can't agree and

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Speaker 1: we are freaking the fuck out. I can't handle this.

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Speaker 1: It got about five thousand notes, and if you aren't

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Speaker 1: tumbler literate, that was a lot of interaction on the

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Speaker 1: platform for the time. And here's where BuzzFeed comes in,

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Speaker 1: As the legend goes BuzzFeed writer Kate's Holderness was running

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Speaker 1: the BuzzFeed tumbler at that time and was tasked with

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Speaker 1: what a lot of writers were back then, finding popular

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Speaker 1: garbage to amplify. But this was not petty content theft.

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Speaker 1: Katelyn McNeil was writing so high on the dress fumes

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Speaker 1: that she sent Holderness her post saying, BuzzFeed, please help.

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Speaker 1: I posted a picture of this dress. It's the last

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Speaker 1: post on my tumbler, okay, and some people see it

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Speaker 1: blue and some people see it white. Can you explain

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Speaker 1: because we are going crazy? Holderness replied, holy crap, it's

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Speaker 1: blue and black. I don't understand. I made a poll,

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Speaker 1: and she links to what she posted off of Caitlin

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Speaker 1: McNeil's tip. A classic BuzzFeed post published in the early evening.

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Speaker 1: As Kevin correctly recalled, the post was simply titled what

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Speaker 1: color is this dress? There was a poll to vote

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Speaker 1: black and blue or white and gold. The post started

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Speaker 1: doing well right away, but pretty much everything on BuzzFeed

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Speaker 1: at that time did. It was after folks left for

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Speaker 1: work that things went nuts. The dress was literally an

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Speaker 1: overnight success. When the BuzzFeed team returned the next morning,

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Speaker 1: Holderness's post had reached eight hundred and forty thousand views

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Speaker 1: per minute. At its peak, it had broken BuzzFeed's traffic record,

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Speaker 1: becoming its most successful post of all time, and once

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Speaker 1: the BuzzFeed post took off. The dress became a popular

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Speaker 1: subject of discussion on virtually every social media platform at

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Speaker 1: the time, but Twitter tends to be the thing that

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Speaker 1: people still talk about these days. Facebook is for moms

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Speaker 1: and creepy cousins, but in twenty fifteen, it was Twitter

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Speaker 1: where famous people ruined their own lives by weighing in

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Speaker 1: like some freaky plebeians just like us. It was right

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Speaker 1: before celebrities all realized in Unison that they needed their

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Speaker 1: own social media managers, and so you could be pretty

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Speaker 1: sure that it was the actual Justin Bieber saying.

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Speaker 3: And for everyone asking, I see blue and black.

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Speaker 1: And it was the real Taylor Swift when she said,

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Speaker 1: I don't understand this odd dress debate, and I feel

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Speaker 1: like it's a trick somehow. I'm confused and scared. Ps

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Speaker 1: it's obviously blue and black, or Mindy kaaling with one

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Speaker 1: of the most twenty fifteen tweets of all time, the

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Speaker 1: dress is worse than the Sony hack to me, Beyonce

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Speaker 1: said nothing. This is all a little pedestrian For Beyonce,

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Speaker 1: BuzzFeed was at the top of their game, and so

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Speaker 1: of course made more content about the dress. Twenty four

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Speaker 1: hours after the first post about the dress went live

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Speaker 1: on the site, nine out of ten trending BuzzFeed posts

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Speaker 1: were about the same dress. They were fucking relentless. Why

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Speaker 1: are people seeing different colors in that damn dress? The

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00:22:06,200 --> 00:22:08,280
Speaker 1: dress is blue and black, says the person who saw

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Speaker 1: it in person. This second photo of the dress definitely

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Speaker 1: proves that the dress is blue and black. What the

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00:22:13,760 --> 00:22:16,440
Speaker 1: dress color you see says about you? And the one

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Speaker 1: post that wasn't about the dress, here's the first picture

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00:22:20,280 --> 00:22:25,200
Speaker 1: of Eddie Redmain as transgender painter Lily elba Oh twenty fifteen.

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Speaker 1: And don't forget at this time, BuzzFeed's video vertical was

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00:22:29,040 --> 00:22:32,760
Speaker 1: also really popular on YouTube, and that was also going

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00:22:32,840 --> 00:22:34,760
Speaker 1: nuts with traffic from the dress.

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Speaker 2: You are seen white and gold.

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Speaker 4: Where are you looking at?

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Speaker 1: No, you're kidding, you heard correctly, that's Quinta Brunson. I

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Speaker 1: just think that's really funny. So, yes, the dress is

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00:22:47,320 --> 00:22:50,520
Speaker 1: a goofy sensation, and it even trickles down to lowly

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Speaker 1: worm regional BuzzFeed ripoff writer Jamie Loftus. But keep in

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Speaker 1: mind BuzzFeed is a business, and people with any monetary

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00:22:58,560 --> 00:23:02,160
Speaker 1: stock in BuzzFeed were doing donuts in their Mercedes about

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Speaker 1: this fucking story. There was even this bizarre essay by

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Speaker 1: then editor in chief Ben Smith, saying that the dress

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00:23:08,160 --> 00:23:11,479
Speaker 1: phenomenon was this sign of BuzzFeed's power.

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00:23:12,400 --> 00:23:16,400
Speaker 3: He said, the explosion of Kate's holderness is post about

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00:23:16,400 --> 00:23:18,639
Speaker 3: the dress White and Gold, by the way, is a

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Speaker 3: reminder that while we now do so many more things,

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00:23:21,600 --> 00:23:25,159
Speaker 3: we've never moved away from our roots. Hindeed, we launched

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00:23:25,200 --> 00:23:27,720
Speaker 3: the acute or Not app yesterday.

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Speaker 1: Sir, your underpaid employee reblogged a Tumblr post, but by

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Speaker 1: all means keep talking. This post in particular is so

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00:23:34,920 --> 00:23:38,000
Speaker 1: weird to reflect on now. It sounds so certain that

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00:23:38,119 --> 00:23:41,240
Speaker 1: BuzzFeed will be the vanguard of what makes something special

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00:23:41,280 --> 00:23:43,520
Speaker 1: on the Internet, and that a post like the dress

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00:23:43,800 --> 00:23:45,520
Speaker 1: is all a part of the game of five D

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Speaker 1: chess that BuzzFeed is playing, and that they're the reason

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00:23:48,880 --> 00:23:52,920
Speaker 1: that the dress succeeded. Smith continued, we are interested most

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00:23:52,960 --> 00:23:55,520
Speaker 1: of all in what a story does, not just in

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Speaker 1: how many people read it, but in what effect it

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00:23:57,800 --> 00:24:01,080
Speaker 1: has on their lives and on the world. Kate's post

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00:24:01,200 --> 00:24:04,080
Speaker 1: delighted people and connected them to steal an idea from

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00:24:04,160 --> 00:24:07,439
Speaker 1: z Frank, Its power was less in the encapsulated item

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00:24:07,480 --> 00:24:10,399
Speaker 1: itself than in the network around it. That's true of

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00:24:10,440 --> 00:24:13,240
Speaker 1: a brilliant piece of entertainment. It's true of a recipe

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00:24:13,320 --> 00:24:17,560
Speaker 1: or a DIY suggestion. Meanwhile, BuzzFeed is getting millions and

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00:24:17,640 --> 00:24:21,000
Speaker 1: millions of impressions from this story, one that Kaitlyn McNeil

414
00:24:21,200 --> 00:24:24,480
Speaker 1: literally handed to them. But it's BuzzFeed that keeps the

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00:24:24,520 --> 00:24:27,640
Speaker 1: profits from the engagement. At a time where impressions were

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Speaker 1: what defined your success and your advertising profits, as is

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00:24:31,920 --> 00:24:35,080
Speaker 1: so common in these stories, it was like everyone was

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00:24:35,119 --> 00:24:39,080
Speaker 1: benefiting from the dress story, except, of course, anyone involved

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00:24:39,119 --> 00:24:41,720
Speaker 1: in the actual story. It didn't take long for completely

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00:24:41,800 --> 00:24:45,040
Speaker 1: unrelated businesses to start commenting on the dress. To capitalize

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00:24:45,040 --> 00:24:47,520
Speaker 1: on the trend, Pizza Hut posts a picture of a

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00:24:47,520 --> 00:24:50,680
Speaker 1: shitty pizza with the caption It's white and gold. Two

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00:24:50,760 --> 00:24:53,280
Speaker 1: newscasters wear the dress on air as a bit The

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00:24:53,359 --> 00:24:57,960
Speaker 1: original dress on a website called Roman Originals sells out immediately.

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00:24:58,720 --> 00:25:02,320
Speaker 1: Brandon Silverman, the the former CEO of social media monitoring

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00:25:02,359 --> 00:25:06,000
Speaker 1: site crowd Tangled, said this when asked about the range

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00:25:06,000 --> 00:25:09,280
Speaker 1: of institutions that wanted in on this story. This is

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00:25:09,320 --> 00:25:12,320
Speaker 1: from a twenty sixteen retrospective on the Day of the

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00:25:12,440 --> 00:25:16,879
Speaker 1: Lama and the Dress from twenty sixteen, written for where

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Speaker 1: Else BuzzFeed, Silverman says.

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00:25:19,560 --> 00:25:22,720
Speaker 6: This, We've seen other stories go viral, but the sheer

432
00:25:22,840 --> 00:25:25,320
Speaker 6: diversity of outlets that picked it up and we're talking

433
00:25:25,359 --> 00:25:28,520
Speaker 6: about it was unlike anything we had ever seen. Everyone

434
00:25:28,520 --> 00:25:32,080
Speaker 6: from QVC to Warnerbros. To local public libraries to Red

435
00:25:32,119 --> 00:25:34,360
Speaker 6: Cross affiliates were all posting links to it on their

436
00:25:34,359 --> 00:25:37,400
Speaker 6: social accounts. That kind of diversity and who's sharing story

437
00:25:37,480 --> 00:25:40,879
Speaker 6: pretty much never happens, and certainly never to that degree.

438
00:25:41,320 --> 00:25:44,800
Speaker 1: And of course, no Internet main character would be complete

439
00:25:45,080 --> 00:25:48,359
Speaker 1: without the backlash, which, in the case of the Dress

440
00:25:48,600 --> 00:25:51,280
Speaker 1: came in the form of people bemoaning that this story

441
00:25:51,560 --> 00:25:54,919
Speaker 1: had overshadowed more important news from the same day. And

442
00:25:54,960 --> 00:25:58,120
Speaker 1: even this mentality feels a little bit dated now. Yes,

443
00:25:58,240 --> 00:26:00,680
Speaker 1: it's important to discuss the other new news of the day,

444
00:26:00,800 --> 00:26:04,640
Speaker 1: but favoring something goofy and meaningless over hard news wasn't

445
00:26:04,720 --> 00:26:08,199
Speaker 1: something that started in twenty fifteen. Although that said, I

446
00:26:08,240 --> 00:26:10,360
Speaker 1: do think there's a case for saying that the success

447
00:26:10,400 --> 00:26:13,320
Speaker 1: of posts like the Dress tells people in tech developing

448
00:26:13,320 --> 00:26:16,640
Speaker 1: social media algorithms at this time what kind of stories

449
00:26:16,680 --> 00:26:19,600
Speaker 1: are distracting for people, leading to an era of the

450
00:26:19,680 --> 00:26:25,240
Speaker 1: algorithm favoring engagement driven posts over carefully reported news. To

451
00:26:25,280 --> 00:26:27,560
Speaker 1: talk about what made the dress special in terms of

452
00:26:27,600 --> 00:26:30,320
Speaker 1: what it said about where social media was picking its

453
00:26:30,320 --> 00:26:32,920
Speaker 1: main characters at this time, I turned to a writer

454
00:26:33,000 --> 00:26:36,040
Speaker 1: who has spent her career writing about the Internet, often

455
00:26:36,080 --> 00:26:39,320
Speaker 1: meaning the Internet turns on her. Taylor Lorenz released her

456
00:26:39,320 --> 00:26:43,359
Speaker 1: book Extremely Online, The Untold Story of Fame, Influence and

457
00:26:43,440 --> 00:26:46,040
Speaker 1: Power on the Internet last year, taking a look at

458
00:26:46,040 --> 00:26:50,120
Speaker 1: the short and eventful history of online influencers, including a

459
00:26:50,160 --> 00:26:53,199
Speaker 1: fair number of characters of the day, and yes, the

460
00:26:53,280 --> 00:26:56,120
Speaker 1: dress herself. We caught up on Zoom about this very

461
00:26:56,160 --> 00:26:58,200
Speaker 1: particular moment in Internet history.

462
00:26:58,960 --> 00:27:01,920
Speaker 7: I'm Taylor Lorenz and I'm the author of Extremely Online,

463
00:27:01,960 --> 00:27:05,200
Speaker 7: The Untold Story of Fame, Influence, and Power on the Internet.

464
00:27:05,520 --> 00:27:07,800
Speaker 1: This has been your beat for some time. How did

465
00:27:07,840 --> 00:27:11,360
Speaker 1: you become the person to talk to about the Internet.

466
00:27:11,960 --> 00:27:15,919
Speaker 7: Yeah, well, I'm like peak millennial. I graduated directly into

467
00:27:16,040 --> 00:27:19,440
Speaker 7: the procession the two thousand and eight financial crisis, and

468
00:27:19,920 --> 00:27:23,280
Speaker 7: I had had like random internships in college and summer jobs,

469
00:27:23,359 --> 00:27:25,560
Speaker 7: but I didn't really know what I was doing, and

470
00:27:26,040 --> 00:27:28,840
Speaker 7: so I was working retail food service. I worked for

471
00:27:28,840 --> 00:27:31,639
Speaker 7: a messenger company, I was babysitting, was I worked at

472
00:27:31,680 --> 00:27:34,920
Speaker 7: a call center for a while. I was just kind

473
00:27:34,920 --> 00:27:38,280
Speaker 7: of making money and I discovered Tumblr, which back in

474
00:27:38,280 --> 00:27:42,159
Speaker 7: two thousand and nine was ascended as a social platform,

475
00:27:42,400 --> 00:27:44,399
Speaker 7: and that was kind of my gateway into blogging, and

476
00:27:44,440 --> 00:27:48,399
Speaker 7: I just started blogging about stuff. At the time, I

477
00:27:48,480 --> 00:27:51,959
Speaker 7: was really against the mainstream media because they were writing

478
00:27:52,000 --> 00:27:55,040
Speaker 7: really stupid things about tech and millennials and it was

479
00:27:55,080 --> 00:27:58,040
Speaker 7: making me mad, and so I would just go on

480
00:27:58,359 --> 00:28:02,640
Speaker 7: my blogs and ran about whatever I felt like ranting about.

481
00:28:02,680 --> 00:28:06,480
Speaker 7: I was really inspired by this woman, Katie Natopoulos, who yes,

482
00:28:07,240 --> 00:28:10,360
Speaker 7: she was blogging back then too, and she had this website.

483
00:28:10,400 --> 00:28:12,719
Speaker 7: She had all these funny like blogs and sites, and

484
00:28:13,440 --> 00:28:15,639
Speaker 7: she seemed to be like the only person that I

485
00:28:15,720 --> 00:28:18,119
Speaker 7: thought was. She was like a couple years older than

486
00:28:18,119 --> 00:28:20,399
Speaker 7: me and seemed really cool, and I just thought, I'm

487
00:28:20,400 --> 00:28:22,040
Speaker 7: going to try to write about the Internet, but like

488
00:28:22,080 --> 00:28:24,720
Speaker 7: from the perspective of somebody that actually uses it.

489
00:28:25,320 --> 00:28:29,679
Speaker 1: There are stories that feel or my feeling at first

490
00:28:29,720 --> 00:28:33,879
Speaker 1: was it feels very connected to a certain type of

491
00:28:33,920 --> 00:28:39,000
Speaker 1: platform or like a certain era in social media. When

492
00:28:39,040 --> 00:28:41,960
Speaker 1: I was reading extremely online, I was like, oh, right,

493
00:28:42,000 --> 00:28:44,920
Speaker 1: the dress was kind of this cross platform success story.

494
00:28:45,960 --> 00:28:48,400
Speaker 1: Could you impact that a little for me of like

495
00:28:48,920 --> 00:28:53,360
Speaker 1: how the original story and then BuzzFeed kind of had

496
00:28:53,880 --> 00:28:56,520
Speaker 1: a mutual role in this story success. Yeah.

497
00:28:56,840 --> 00:29:00,400
Speaker 7: Well, just to kind of like explain the landscape throughout

498
00:29:00,400 --> 00:29:04,000
Speaker 7: the early to mid twenty tens, you had this explosion

499
00:29:04,040 --> 00:29:08,400
Speaker 7: of digital media sites spurred by VC funding, you know, BuzzFeed,

500
00:29:08,560 --> 00:29:10,760
Speaker 7: Mike dot Com, Race to Work, Mashable, Like, there were

501
00:29:10,800 --> 00:29:13,960
Speaker 7: all these like digital media sites, and the primary way

502
00:29:13,960 --> 00:29:16,880
Speaker 7: that they were gaining traffic was going into sort of

503
00:29:17,240 --> 00:29:19,760
Speaker 7: what were then the depths of the Internet, mostly Tumblr

504
00:29:19,760 --> 00:29:22,880
Speaker 7: and Reddit, getting the most viral content off those platforms

505
00:29:23,040 --> 00:29:25,120
Speaker 7: and repackaging it on the website. Because that was an

506
00:29:25,120 --> 00:29:28,480
Speaker 7: era when not a lot of people were going and

507
00:29:28,520 --> 00:29:30,040
Speaker 7: spending a lot of time and getting their news and

508
00:29:30,080 --> 00:29:34,520
Speaker 7: information and entertainment from social media directly itself. It wasn't

509
00:29:34,520 --> 00:29:36,560
Speaker 7: as widely adopted. People didn't know how to navigate the

510
00:29:36,600 --> 00:29:40,320
Speaker 7: Internet yet, so Buzzheed would just sort of like mine

511
00:29:40,480 --> 00:29:43,480
Speaker 7: this content. Kates was working at BuzzFeed at the time,

512
00:29:44,240 --> 00:29:47,360
Speaker 7: found a Tumblr post about the dress and was like, wow,

513
00:29:47,440 --> 00:29:49,960
Speaker 7: this is kind of crazy. It was getting a little

514
00:29:49,960 --> 00:29:52,040
Speaker 7: bit of traction on Tumblr, and she thought, let me

515
00:29:52,080 --> 00:29:55,560
Speaker 7: post it on the BuzzFeed website, because that's kind of

516
00:29:55,600 --> 00:29:57,560
Speaker 7: again the business model at the time was finding what

517
00:29:57,600 --> 00:29:59,400
Speaker 7: did while on Tumblr and then bringing it to this

518
00:29:59,440 --> 00:30:02,280
Speaker 7: wider audience, the BuzzFeed, And of course she publishes it

519
00:30:02,320 --> 00:30:05,400
Speaker 7: on BuzzFeed and it just goes insane.

520
00:30:05,760 --> 00:30:06,520
Speaker 1: A bunch of other.

521
00:30:06,400 --> 00:30:09,240
Speaker 7: Places immediately published their own versions of that story, but

522
00:30:09,760 --> 00:30:13,080
Speaker 7: BuzzFeed got like all the upside kind of from it,

523
00:30:13,120 --> 00:30:14,720
Speaker 7: Like they got all the traffic they were able to

524
00:30:14,720 --> 00:30:20,160
Speaker 7: monetize through ads on that article page. Like right, nobody

525
00:30:20,240 --> 00:30:23,360
Speaker 7: was picking through as much to the original Tumblr that day.

526
00:30:24,000 --> 00:30:26,360
Speaker 1: I was cruising the wayback machine and I was like,

527
00:30:26,600 --> 00:30:30,360
Speaker 1: this is what I think of as like peak BuzzFeed.

528
00:30:31,160 --> 00:30:36,160
Speaker 1: How did they get there? Like what made BuzzFeed special

529
00:30:36,360 --> 00:30:39,680
Speaker 1: or early to this kind of content mining.

530
00:30:40,160 --> 00:30:43,040
Speaker 7: BuzzFeed was one of the first true sort of like

531
00:30:43,160 --> 00:30:46,880
Speaker 7: digital media companies of that wave. There was this idea

532
00:30:47,320 --> 00:30:50,640
Speaker 7: in the two thousands. It's really spurred by the rise

533
00:30:50,640 --> 00:30:55,920
Speaker 7: of blogging, that you could build digital media platforms and

534
00:30:56,120 --> 00:30:58,960
Speaker 7: capture digital media ad dollars. There's all this money moving

535
00:30:58,960 --> 00:31:03,480
Speaker 7: from traditional advertise to digital advertising. The traditional advertising had

536
00:31:03,480 --> 00:31:06,840
Speaker 7: been with newspapers and traditional media, and so the thinking

537
00:31:07,160 --> 00:31:09,400
Speaker 7: was back then was all those traditional ad dollars are

538
00:31:09,440 --> 00:31:13,920
Speaker 7: going to go to the digital version of the news

539
00:31:14,000 --> 00:31:17,520
Speaker 7: media that the advertisers were advertising with. So there was

540
00:31:17,560 --> 00:31:20,520
Speaker 7: this website like vox and you know, other sites were

541
00:31:20,560 --> 00:31:24,160
Speaker 7: sort of created to capture those ad dollars. Obviously that

542
00:31:24,240 --> 00:31:26,640
Speaker 7: didn't happen. The money actually ended up going to Facebook

543
00:31:26,680 --> 00:31:28,920
Speaker 7: and Google directly, which is why that whole crop of

544
00:31:28,920 --> 00:31:31,320
Speaker 7: digital media companies died pretty much or like as a

545
00:31:31,320 --> 00:31:34,280
Speaker 7: shell of themselves. But traffic was the most important thing.

546
00:31:34,320 --> 00:31:37,120
Speaker 7: Traffic was so important because the more views you got,

547
00:31:37,120 --> 00:31:41,440
Speaker 7: the more digital like display ads you know we're seeing,

548
00:31:41,480 --> 00:31:44,840
Speaker 7: the more money the platform would make. And this is

549
00:31:44,840 --> 00:31:47,960
Speaker 7: when a lot of platforms, including Facebook, were prioritizing link posts.

550
00:31:48,000 --> 00:31:50,240
Speaker 7: They hadn't pivoted to video yet. There wasn't a lot

551
00:31:50,240 --> 00:31:53,200
Speaker 7: of multimedia because the Internet speeds weren't there yet, so

552
00:31:53,200 --> 00:31:56,240
Speaker 7: it would make the sites really slow and clunky to load.

553
00:31:56,760 --> 00:32:00,480
Speaker 7: Instagram was barely had video at that time, so links

554
00:32:00,480 --> 00:32:03,000
Speaker 7: were really kaying and if you could create a very

555
00:32:03,000 --> 00:32:06,840
Speaker 7: shareable link, you could get tons of traffic. Therefore the

556
00:32:06,880 --> 00:32:08,920
Speaker 7: company would make tons of money. And BuzzFeed was just

557
00:32:09,040 --> 00:32:13,000
Speaker 7: expert at this because BuzzFeed realized very early that Internet

558
00:32:13,080 --> 00:32:15,440
Speaker 7: users at that time didn't want to go through Reddit.

559
00:32:15,680 --> 00:32:19,200
Speaker 7: You have to remember this was pre algorithmic feeds. Algorithmic

560
00:32:19,240 --> 00:32:21,680
Speaker 7: feeds were not really a thing back then. I think

561
00:32:21,680 --> 00:32:25,720
Speaker 7: Twitter only rolled out their algorithmicfeed in twenty sixteen twenty fifteen.

562
00:32:26,040 --> 00:32:29,000
Speaker 7: It was really like the Internet was very manual, and

563
00:32:29,080 --> 00:32:32,440
Speaker 7: so if people went on a platform, they couldn't especially

564
00:32:32,440 --> 00:32:35,920
Speaker 7: Tumblr at that time was completely reverse chronological, right, so

565
00:32:36,280 --> 00:32:38,880
Speaker 7: if you went on the platform, it was hard to

566
00:32:38,960 --> 00:32:43,400
Speaker 7: kind of find the most interesting viral content. So you

567
00:32:43,600 --> 00:32:46,760
Speaker 7: relied on this intermediaries like BuzzFeed to go into these

568
00:32:46,760 --> 00:32:49,720
Speaker 7: platforms scrape out the most engaging content and presented to

569
00:32:49,760 --> 00:32:52,320
Speaker 7: you all in one place. On this case too, I

570
00:32:52,320 --> 00:32:55,080
Speaker 7: think it's really interesting that the dress post it was

571
00:32:55,160 --> 00:32:58,520
Speaker 7: posted on a Tumblr that was like a fan tumbler

572
00:32:58,560 --> 00:33:00,760
Speaker 7: for this girl, Sarah White show White ChIL. I always

573
00:33:00,840 --> 00:33:04,080
Speaker 7: mispronounce her name, even though yes Lovely who was like

574
00:33:04,120 --> 00:33:07,480
Speaker 7: a YouTuber manager. So it was just like the chances

575
00:33:07,520 --> 00:33:11,000
Speaker 7: of somebody finding that Normally, yes, it was getting reblogged

576
00:33:11,040 --> 00:33:13,560
Speaker 7: on Tumblr, but BuzzFeed was really like the amplifier.

577
00:33:13,680 --> 00:33:17,920
Speaker 1: Basically Thanks so much to Taylor, and check out Extremely

578
00:33:18,040 --> 00:33:21,160
Speaker 1: Online in stores now, and we'll be right back with

579
00:33:21,280 --> 00:33:24,400
Speaker 1: another interview about why the success of the dress marked

580
00:33:24,440 --> 00:33:27,280
Speaker 1: the beginning of the end for dumb fun on the internet.

581
00:33:37,720 --> 00:33:40,240
Speaker 1: Welcome back to sixteenth minute. I am the author of

582
00:33:40,280 --> 00:33:44,320
Speaker 1: the twenty fifteen post was SNL's isis sketch too offensive?

583
00:33:45,120 --> 00:33:47,640
Speaker 1: As fascinated as I am about how the dress went

584
00:33:47,760 --> 00:33:51,040
Speaker 1: viral and what now feels like an almost old fashioned way,

585
00:33:51,320 --> 00:33:53,760
Speaker 1: I wanted to take a second to do my due diligence.

586
00:33:54,360 --> 00:33:57,960
Speaker 1: Why were people seeing this dress as two different color schemes?

587
00:33:58,560 --> 00:34:02,360
Speaker 1: This was a major subject clickbait from clickbait at the time,

588
00:34:03,000 --> 00:34:06,120
Speaker 1: most notably a Wired piece published the day after that

589
00:34:06,320 --> 00:34:09,279
Speaker 1: ended up racking up over thirty two million views. In

590
00:34:09,400 --> 00:34:13,680
Speaker 1: that piece, writer Adam Rodgers asked professor Bevill Conway, who

591
00:34:13,719 --> 00:34:16,800
Speaker 1: studied color and vision at Wellesley College, to comment, and

592
00:34:16,880 --> 00:34:19,680
Speaker 1: Professor Conway said that it was some combination of the

593
00:34:19,840 --> 00:34:23,160
Speaker 1: varying ways in which people perceive light, and that the

594
00:34:23,239 --> 00:34:26,440
Speaker 1: picture was just shitty quality and really blown out. Here's

595
00:34:26,480 --> 00:34:30,319
Speaker 1: his fancy science explanation. Your visual system is looking at

596
00:34:30,360 --> 00:34:33,360
Speaker 1: this thing, and you're trying to discount the chromatic bias

597
00:34:33,480 --> 00:34:36,959
Speaker 1: of the daylight axis. People either discount the blue side,

598
00:34:37,200 --> 00:34:39,080
Speaker 1: in which case they end up seeing white and gold,

599
00:34:39,560 --> 00:34:42,239
Speaker 1: or discount the gold side, in which case they end

600
00:34:42,320 --> 00:34:45,040
Speaker 1: up with blue and black. This also connects to the

601
00:34:45,239 --> 00:34:48,880
Speaker 1: maddening feeling of the dress switching colors before your eyes,

602
00:34:49,239 --> 00:34:51,799
Speaker 1: like Quinta yelled about in the BuzzFeed video. So if

603
00:34:51,840 --> 00:34:54,640
Speaker 1: you were a neuroscientist with a focus on vision, and

604
00:34:54,840 --> 00:34:57,640
Speaker 1: I know you're not, this actually prompted a pretty rich

605
00:34:57,719 --> 00:35:01,920
Speaker 1: scientific discussion. The Journal of Vision dedicated a whole issue

606
00:35:02,040 --> 00:35:05,880
Speaker 1: to the dress with some pretty interesting findings. They spoke

607
00:35:05,920 --> 00:35:09,040
Speaker 1: to fourteen hundred p respondents, with fifty seven percent seeing

608
00:35:09,080 --> 00:35:12,880
Speaker 1: black and blue, eleven percent black and brown, thirty percent

609
00:35:13,000 --> 00:35:17,240
Speaker 1: white and gold, and two percent. Other tests included showing

610
00:35:17,280 --> 00:35:19,839
Speaker 1: the dress in artificial yellow and blue light to see

611
00:35:19,880 --> 00:35:22,560
Speaker 1: if that's shifted by us, and a study from Pascal

612
00:35:22,680 --> 00:35:26,000
Speaker 1: Wallash showed the really interesting trend that people who woke

613
00:35:26,120 --> 00:35:28,440
Speaker 1: up early were more likely to see the dress as

614
00:35:28,480 --> 00:35:31,000
Speaker 1: white and gold, and people who went out at night

615
00:35:31,120 --> 00:35:34,040
Speaker 1: moore were likely to see black and blue. And I'll

616
00:35:34,080 --> 00:35:36,680
Speaker 1: admit reading about why your brain makes you see the

617
00:35:36,760 --> 00:35:39,400
Speaker 1: dress as one thing or the other is really really interesting,

618
00:35:39,640 --> 00:35:41,960
Speaker 1: even when what's being explained to you is a pretty

619
00:35:42,000 --> 00:35:45,640
Speaker 1: straightforward optical illusion. And even though as I'm writing this

620
00:35:45,760 --> 00:35:49,880
Speaker 1: episode this only happened about nine years ago, it feels

621
00:35:49,960 --> 00:35:52,839
Speaker 1: like it's longer. It reminds me of a targeted ad

622
00:35:52,880 --> 00:35:55,520
Speaker 1: I got for a T shirt sold by ClickHole, which,

623
00:35:55,640 --> 00:35:58,160
Speaker 1: if you're not familiar, is a spinoff of the Onion

624
00:35:58,280 --> 00:36:03,800
Speaker 1: that specifically satirized clickbait. The shirt says the Internet nineteen

625
00:36:03,840 --> 00:36:06,759
Speaker 1: eighty three to twenty fourteen, and it gets at this

626
00:36:06,880 --> 00:36:10,440
Speaker 1: feeling I'm having that shortly after the dress, the Internet

627
00:36:10,560 --> 00:36:14,200
Speaker 1: became less fun. Of course, this is coming from a

628
00:36:14,360 --> 00:36:17,840
Speaker 1: very Western, privileged perspective, but it's pretty commonly held that

629
00:36:18,000 --> 00:36:20,480
Speaker 1: in the US, around the time that the twenty sixteen

630
00:36:20,520 --> 00:36:24,759
Speaker 1: election cycle began, social media became less fun. Let's not

631
00:36:24,880 --> 00:36:27,080
Speaker 1: to say it was a cakewalk before. There are many

632
00:36:27,160 --> 00:36:30,319
Speaker 1: stories of discrimination and harassment that took place here, many

633
00:36:30,400 --> 00:36:32,439
Speaker 1: of which I'll cover on this show. But I'm trying

634
00:36:32,480 --> 00:36:36,480
Speaker 1: to get at the ratio of fun stories to existentially

635
00:36:36,600 --> 00:36:40,400
Speaker 1: terrifying stories, the ratio of hey, what color is this?

636
00:36:40,880 --> 00:36:45,520
Speaker 1: To bigoted conspiracy theories in the mainstream. The dress kind

637
00:36:45,560 --> 00:36:47,879
Speaker 1: of feels like the end of an era. Early twenty

638
00:36:48,000 --> 00:36:52,080
Speaker 1: fifteen wasn't an Internet that wasn't poisoned with hate, but

639
00:36:52,200 --> 00:36:55,920
Speaker 1: it felt like an Internet whose hate didn't poison everything,

640
00:36:56,640 --> 00:36:59,839
Speaker 1: and less than a year later that didn't really feel true.

641
00:37:00,360 --> 00:37:02,680
Speaker 1: I didn't speak to anyone involved in the original dress

642
00:37:02,680 --> 00:37:05,160
Speaker 1: story for reasons I'll get to, but I wanted to

643
00:37:05,239 --> 00:37:08,359
Speaker 1: better understand how the Internet shifted in the year after

644
00:37:08,440 --> 00:37:10,480
Speaker 1: the dress to bring us to the kind of viral

645
00:37:10,560 --> 00:37:13,680
Speaker 1: stories we were seeing in twenty sixteen. Just a year later.

646
00:37:14,040 --> 00:37:16,919
Speaker 1: For Perspective, their Ringers round up of twenty sixteen viral

647
00:37:17,000 --> 00:37:21,080
Speaker 1: stories included some classics like Chewbacco Mom, but also just

648
00:37:21,200 --> 00:37:25,640
Speaker 1: the word Nazism. So yeah, there was a mainstream shift

649
00:37:25,719 --> 00:37:28,080
Speaker 1: that had taken place. And this was for a reason,

650
00:37:28,400 --> 00:37:31,880
Speaker 1: not just because of the heightened bigoted extremism in the

651
00:37:31,920 --> 00:37:36,120
Speaker 1: Western world, but because of how our social networks were functioning.

652
00:37:36,440 --> 00:37:39,400
Speaker 1: It's something that BuzzFeed founder Jonah Peretti commented on as

653
00:37:39,480 --> 00:37:42,680
Speaker 1: recently as twenty nineteen, less than five years after the

654
00:37:42,760 --> 00:37:46,279
Speaker 1: dress story. In November twenty nineteen, he told Max Read

655
00:37:46,360 --> 00:37:48,520
Speaker 1: at Intelligencer, the dress was.

656
00:37:48,520 --> 00:37:51,480
Speaker 3: A kind of perfect thing to catch fire at that moment,

657
00:37:51,920 --> 00:37:54,960
Speaker 3: the Internet was less polarized and politicized, and it had

658
00:37:55,000 --> 00:37:57,840
Speaker 3: shifted to mobile fully, so people were looking at mobile

659
00:37:57,880 --> 00:38:01,279
Speaker 3: devices with the dress. You saw it on your phone

660
00:38:01,520 --> 00:38:03,799
Speaker 3: and you were with people. You could hold the phone

661
00:38:03,840 --> 00:38:06,520
Speaker 3: up and say what color is this. Plus, in the

662
00:38:06,560 --> 00:38:08,600
Speaker 3: early days of BuzzFeed, our traffic would die in the

663
00:38:08,680 --> 00:38:10,880
Speaker 3: evening because people would watch television or go out with

664
00:38:10,880 --> 00:38:15,080
Speaker 3: their friends. Now, with mobile, we see primetime for our

665
00:38:15,239 --> 00:38:18,960
Speaker 3: content as the same as primetime for television. People are

666
00:38:19,080 --> 00:38:21,719
Speaker 3: sharing content and looking at content later.

667
00:38:22,520 --> 00:38:24,640
Speaker 1: Keep in mind this is a quote from less than

668
00:38:24,719 --> 00:38:27,880
Speaker 1: half a decade later, but the difference between twenty fifteen

669
00:38:28,040 --> 00:38:31,080
Speaker 1: and twenty nineteen on the US Internet made it feel

670
00:38:31,200 --> 00:38:34,080
Speaker 1: like he was talking about twenty years ago. I mean,

671
00:38:34,200 --> 00:38:37,640
Speaker 1: hell on the Internet. Forty years passed between November twenty

672
00:38:37,760 --> 00:38:41,800
Speaker 1: nineteen and November twenty twenty, and since this interview, BuzzFeed

673
00:38:41,880 --> 00:38:44,640
Speaker 1: has changed even more. Paretti pulled the plug on his

674
00:38:44,760 --> 00:38:48,360
Speaker 1: Pulitzer winning news operation only seven years after it launched

675
00:38:48,560 --> 00:38:52,400
Speaker 1: in twenty twenty three, and is currently focused on rerouting

676
00:38:52,440 --> 00:38:59,000
Speaker 1: BuzzFeed to AI. Depressing, yes, but not surprising, because after all,

677
00:38:59,200 --> 00:39:02,400
Speaker 1: Paretti start the company to operate on algorithms with no

678
00:39:02,600 --> 00:39:06,080
Speaker 1: creative at all, and now he has robots instead of writers,

679
00:39:06,280 --> 00:39:09,359
Speaker 1: and the company is worth less than ever. I talked

680
00:39:09,360 --> 00:39:11,799
Speaker 1: to a second author who published a great book about

681
00:39:11,840 --> 00:39:15,400
Speaker 1: social media and full disclosure, he's also my best friend's boyfriend.

682
00:39:15,640 --> 00:39:17,800
Speaker 1: He's the best and pertinent to you. He has a

683
00:39:17,880 --> 00:39:21,560
Speaker 1: thorough knowledge on how social media algorithms have been forcibly

684
00:39:21,640 --> 00:39:24,760
Speaker 1: evolved and monetized to serve those that make them money,

685
00:39:25,160 --> 00:39:28,640
Speaker 1: not their users. Max Fisher currently co hosts Offline on

686
00:39:28,760 --> 00:39:31,680
Speaker 1: Crooked Media, and wrote about this very topic in twenty

687
00:39:31,719 --> 00:39:35,319
Speaker 1: twenty two's The Chaos Machine, The Inside Story of how

688
00:39:35,440 --> 00:39:39,320
Speaker 1: Social Media rewired our minds and our world. Here's some

689
00:39:39,440 --> 00:39:39,919
Speaker 1: of our talk.

690
00:39:41,640 --> 00:39:44,960
Speaker 8: My name is Max Fisher, and I'm a journalist and podcaster.

691
00:39:45,640 --> 00:39:47,880
Speaker 1: Because we're talking about the dress today is what is

692
00:39:48,120 --> 00:39:52,040
Speaker 1: your personal recollection of the dress? Saga? Were you you

693
00:39:52,120 --> 00:39:54,000
Speaker 1: were working in media at the time, right?

694
00:39:55,040 --> 00:39:57,400
Speaker 8: I Not only was say working in media, but I

695
00:39:57,600 --> 00:39:59,880
Speaker 8: was working not at BuzzFeed, but at Fox dot com,

696
00:40:00,000 --> 00:40:04,719
Speaker 8: which was a fellow kind of web you know, new journalism,

697
00:40:05,680 --> 00:40:08,920
Speaker 8: left leaning startup that was trying to chase audience on

698
00:40:09,080 --> 00:40:12,040
Speaker 8: social media. So it felt very much kind of in

699
00:40:12,400 --> 00:40:15,080
Speaker 8: our wheelhouse. It was something that we were all really

700
00:40:15,120 --> 00:40:17,399
Speaker 8: excited about. Wow, look a post can get this much

701
00:40:17,440 --> 00:40:20,560
Speaker 8: attention by you know, doing something that Facebook really likes

702
00:40:20,600 --> 00:40:23,560
Speaker 8: and that social media algorithms really like. And we were

703
00:40:23,600 --> 00:40:25,960
Speaker 8: trying to do not the dress exactly, but we were

704
00:40:26,000 --> 00:40:29,080
Speaker 8: trying to do like, you know, the policy Wonk version

705
00:40:29,239 --> 00:40:31,680
Speaker 8: of the dress every day. So we thought it was

706
00:40:31,800 --> 00:40:33,920
Speaker 8: like this amazing moment that we paid a lot of

707
00:40:33,960 --> 00:40:34,440
Speaker 8: attention to.

708
00:40:35,320 --> 00:40:38,480
Speaker 1: So I know that you've spent a lot of recent

709
00:40:38,600 --> 00:40:42,960
Speaker 1: years thinking about how our algorithms work, and you know

710
00:40:43,160 --> 00:40:46,399
Speaker 1: the implications of that. Were you thinking about this ten

711
00:40:46,520 --> 00:40:50,360
Speaker 1: years ago? What did that algorithm chasing look like?

712
00:40:51,760 --> 00:40:54,080
Speaker 8: I was thinking about it, But like a lot of

713
00:40:54,239 --> 00:40:57,360
Speaker 8: journalists I think of our generation, I thought of it

714
00:40:57,400 --> 00:40:59,560
Speaker 8: as just purely a good thing, as just a thing

715
00:40:59,560 --> 00:41:03,040
Speaker 8: where it's like, oh, if I write my piece that

716
00:41:03,120 --> 00:41:06,839
Speaker 8: I was going to write anyway on the Iran nuclear deal,

717
00:41:06,960 --> 00:41:09,319
Speaker 8: but I phrased the headline in a certain way, then

718
00:41:09,440 --> 00:41:12,480
Speaker 8: Facebook can deliver me, thanks to its algorithm, huge amounts

719
00:41:12,480 --> 00:41:14,719
Speaker 8: of traffic and eyeballs and people who want to read

720
00:41:14,719 --> 00:41:16,840
Speaker 8: the story. And that's great, and that's so nice that

721
00:41:16,960 --> 00:41:19,759
Speaker 8: social media can be there to help us reach a

722
00:41:19,880 --> 00:41:24,479
Speaker 8: larger audience. So I was aware of it, but thought

723
00:41:24,520 --> 00:41:27,799
Speaker 8: of it as kind of a relatively neutral force, like, sure,

724
00:41:27,840 --> 00:41:30,239
Speaker 8: maybe you play up certain emotions in your headlines and

725
00:41:30,280 --> 00:41:33,480
Speaker 8: certain ideas that you know are likely or to go viral,

726
00:41:33,640 --> 00:41:36,919
Speaker 8: but again maybe like a lot of people. It wasn't

727
00:41:37,000 --> 00:41:40,040
Speaker 8: really until after Trump was elected, like a year and

728
00:41:40,080 --> 00:41:41,840
Speaker 8: a half after that, that I started to think of

729
00:41:41,960 --> 00:41:44,480
Speaker 8: social media and social media algorithms as something that could

730
00:41:44,520 --> 00:41:47,080
Speaker 8: be bad. At this point, I really thought that they

731
00:41:47,080 --> 00:41:48,040
Speaker 8: were just a good thing.

732
00:41:48,400 --> 00:41:51,719
Speaker 1: And also just I think, certainly on my end, there

733
00:41:51,920 --> 00:41:55,720
Speaker 1: was a lack of thinking about how this algorithm chasing

734
00:41:56,440 --> 00:42:01,880
Speaker 1: translated to money, which in retrospect feel very naive of me,

735
00:42:02,320 --> 00:42:05,600
Speaker 1: but there was at the time. It seems like money

736
00:42:05,719 --> 00:42:09,080
Speaker 1: to be had from you know, taking these stories that

737
00:42:09,160 --> 00:42:12,400
Speaker 1: you would find on social media and then you know,

738
00:42:12,520 --> 00:42:17,000
Speaker 1: delivering them and making you know, question mark a shitload of.

739
00:42:17,000 --> 00:42:22,240
Speaker 8: Money, right, I mean, the idea for the web startups

740
00:42:22,280 --> 00:42:25,560
Speaker 8: of that era was that you will get so many

741
00:42:25,640 --> 00:42:28,239
Speaker 8: more eyeballs on social media, and then so many more

742
00:42:28,239 --> 00:42:30,080
Speaker 8: people will click through to your website and they will

743
00:42:30,120 --> 00:42:32,160
Speaker 8: see ads on your website, so then you will make

744
00:42:32,239 --> 00:42:35,640
Speaker 8: more money and we weren't thinking of it, and maybe

745
00:42:35,760 --> 00:42:39,680
Speaker 8: you guys were breaking it in to the Boston BuzzFeed.

746
00:42:39,280 --> 00:42:43,239
Speaker 1: But almost impossible to conceive that we were.

747
00:42:44,640 --> 00:42:47,960
Speaker 8: I mean, maybe this was idealistic, but we were thinking

748
00:42:48,040 --> 00:42:50,440
Speaker 8: of it as this will be great because it will

749
00:42:50,480 --> 00:42:53,200
Speaker 8: make journalism sustainable. Like, we were all veterans of the

750
00:42:53,200 --> 00:42:55,040
Speaker 8: two thousand and eight financial crisis, so we had all

751
00:42:55,080 --> 00:42:56,880
Speaker 8: lived through a time when there were no jobs to

752
00:42:56,960 --> 00:42:59,840
Speaker 8: be had because the industry was collapsing because the Internet

753
00:43:00,080 --> 00:43:03,440
Speaker 8: social media had taken all of the revenue that used

754
00:43:03,480 --> 00:43:06,759
Speaker 8: to go through classifieds. So the idea that, aha, now

755
00:43:06,800 --> 00:43:09,080
Speaker 8: we're going to leverage that same social media to get

756
00:43:09,080 --> 00:43:12,319
Speaker 8: all these ad impressions. We can have a sustainable business again,

757
00:43:12,840 --> 00:43:15,360
Speaker 8: and won't that be so great for like the future

758
00:43:15,680 --> 00:43:18,080
Speaker 8: of the industry. And like before I worked at Fox,

759
00:43:18,120 --> 00:43:19,840
Speaker 8: I worked at the Washington Post, and they'd loved the

760
00:43:19,960 --> 00:43:22,440
Speaker 8: idea that you would do the journalism you were going

761
00:43:22,520 --> 00:43:23,920
Speaker 8: to do anyway, but right in in a way that

762
00:43:24,000 --> 00:43:26,239
Speaker 8: will please algorithms, or right the headline in a way

763
00:43:26,280 --> 00:43:29,040
Speaker 8: that will please algorithms, so that we can make more

764
00:43:29,080 --> 00:43:32,040
Speaker 8: money and continue to pay for foreign correspondence. So it

765
00:43:32,120 --> 00:43:35,680
Speaker 8: is a very starry eyed era that boy has sure

766
00:43:35,719 --> 00:43:36,359
Speaker 8: not aged well.

767
00:43:36,800 --> 00:43:40,920
Speaker 1: Used a phrase that just feels very inherent to what

768
00:43:41,000 --> 00:43:44,000
Speaker 1: the dress was. You use a phrase the old algorithm.

769
00:43:44,680 --> 00:43:47,080
Speaker 1: What do you mean when you say the old algorithm?

770
00:43:47,840 --> 00:43:52,160
Speaker 8: Oh? Yeah, okay, So I think we all know that

771
00:43:53,120 --> 00:43:57,280
Speaker 8: algorithms are what drive everything and how you experience social media.

772
00:43:57,360 --> 00:44:00,800
Speaker 8: There are the programs on every platform that select what

773
00:44:00,920 --> 00:44:04,280
Speaker 8: you see the order you see it in, that choose

774
00:44:04,400 --> 00:44:08,920
Speaker 8: what kind of emotions to surface, what kind of like

775
00:44:09,160 --> 00:44:12,439
Speaker 8: political valance to surface for you. They're the absolute core

776
00:44:12,560 --> 00:44:15,520
Speaker 8: of the social media business model. The era before algorithms,

777
00:44:15,520 --> 00:44:18,080
Speaker 8: social media was a loser business that didn't make any money,

778
00:44:18,520 --> 00:44:20,920
Speaker 8: and people didn't spend that much time on like rimbor MySpace,

779
00:44:20,960 --> 00:44:22,760
Speaker 8: You didn't spend that much time on the site live journal.

780
00:44:23,280 --> 00:44:27,000
Speaker 8: After they developed algorithms, that is when people's time on

781
00:44:27,160 --> 00:44:32,920
Speaker 8: site exploded because they are so effective at making the

782
00:44:33,000 --> 00:44:36,120
Speaker 8: experience of being social media very engaging and addictive, and

783
00:44:36,200 --> 00:44:39,239
Speaker 8: that's what turned social media companies into huge businesses. So

784
00:44:39,400 --> 00:44:43,000
Speaker 8: for a long time, the way that those algorithms worked

785
00:44:43,200 --> 00:44:46,080
Speaker 8: from their first invention and like the end of the

786
00:44:46,160 --> 00:44:48,440
Speaker 8: two thousands, like Facebook kind of starts it in two

787
00:44:48,440 --> 00:44:50,360
Speaker 8: thousand and six with the Facebook news feed, but it

788
00:44:50,400 --> 00:44:53,359
Speaker 8: takes a while for their platforms to catch up up

789
00:44:54,000 --> 00:44:57,400
Speaker 8: through like the era of the dress, the way that

790
00:44:57,480 --> 00:45:01,800
Speaker 8: it worked, the old quote unquote old algorithm promoted whatever

791
00:45:02,520 --> 00:45:06,440
Speaker 8: content was. They tend to promote outbound links, like it

792
00:45:06,480 --> 00:45:09,919
Speaker 8: will promote a link to some other website or news site,

793
00:45:09,960 --> 00:45:14,120
Speaker 8: even if it's like a lollcat or something something off

794
00:45:14,200 --> 00:45:16,160
Speaker 8: the platform, and it would be whatever is the link

795
00:45:16,200 --> 00:45:19,520
Speaker 8: that people would click on the most. And what that

796
00:45:19,760 --> 00:45:24,720
Speaker 8: tended to privilege is if you remember like upworthy. Upworthy

797
00:45:24,880 --> 00:45:29,799
Speaker 8: was like a website that existed to create content specifically

798
00:45:29,880 --> 00:45:33,080
Speaker 8: to cater to like the old Facebook algorithm, because it

799
00:45:33,239 --> 00:45:35,799
Speaker 8: was like curiosity gaps or it was like you won't

800
00:45:35,840 --> 00:45:37,600
Speaker 8: believe what happened next, so you're like, oh, I guess

801
00:45:37,640 --> 00:45:39,239
Speaker 8: I'll click on that link, and then you click on

802
00:45:39,320 --> 00:45:42,080
Speaker 8: that link, and then Facebook or Twitter learns, okay, we

803
00:45:42,200 --> 00:45:43,920
Speaker 8: promote that link to a lot of people, they will

804
00:45:43,960 --> 00:45:47,600
Speaker 8: click on it. And the dress is kind of the

805
00:45:47,800 --> 00:45:51,680
Speaker 8: last gasp of that old algorithm because it is again

806
00:45:52,400 --> 00:45:54,719
Speaker 8: you see the link and the way that it displayed

807
00:45:54,920 --> 00:45:57,160
Speaker 8: on not just Facebook, although Facebook was the big one

808
00:45:57,200 --> 00:45:59,240
Speaker 8: at the time, but all of the platforms read it Twitter,

809
00:46:00,000 --> 00:46:02,640
Speaker 8: it would displays you would see a cutoff image of

810
00:46:02,800 --> 00:46:04,879
Speaker 8: the dress, and then you would see a headline about

811
00:46:04,920 --> 00:46:07,359
Speaker 8: people see it in different colors, So it really makes

812
00:46:07,400 --> 00:46:10,399
Speaker 8: you want to click. So everybody who saw this link

813
00:46:10,480 --> 00:46:12,160
Speaker 8: on their news feed you were like, oh, I have

814
00:46:12,320 --> 00:46:14,960
Speaker 8: to click through and figure out what color the dress is,

815
00:46:15,000 --> 00:46:17,720
Speaker 8: even if you only spend eight seconds on that post.

816
00:46:18,280 --> 00:46:21,200
Speaker 8: The algorithm learns that serves it to everyone on the

817
00:46:21,239 --> 00:46:24,560
Speaker 8: platforms because it creates these outbound links, and that is

818
00:46:24,560 --> 00:46:27,880
Speaker 8: when BuzzFeed starts to get you know, a million people

819
00:46:27,920 --> 00:46:29,480
Speaker 8: a minute or whatever the numbers were.

820
00:46:30,080 --> 00:46:30,680
Speaker 2: Looking at it.

821
00:46:31,360 --> 00:46:34,520
Speaker 1: A section of your book covers really thoroughly. Like twenty

822
00:46:34,640 --> 00:46:38,200
Speaker 1: fifteen is a really important year for this shift. So

823
00:46:38,440 --> 00:46:41,480
Speaker 1: the way that the algorithm looks in late February twenty

824
00:46:41,520 --> 00:46:44,200
Speaker 1: fifteen and at the end of the year seems pretty different.

825
00:46:44,640 --> 00:46:48,760
Speaker 1: What is changing with how algorithms are used on social

826
00:46:48,800 --> 00:46:50,279
Speaker 1: media throughout.

827
00:46:50,000 --> 00:46:53,680
Speaker 8: This era, So there's not like a moment of shift,

828
00:46:53,719 --> 00:46:55,640
Speaker 8: like they don't pull a big lever and go over

829
00:46:55,760 --> 00:46:59,440
Speaker 8: to new set of algorithms. But bummer, bummer, I know,

830
00:47:00,040 --> 00:47:03,480
Speaker 8: but over like twenty fourteen and twenty fifteen, the big

831
00:47:03,560 --> 00:47:07,320
Speaker 8: social media platforms make a bunch of incremental changes that

832
00:47:07,560 --> 00:47:11,840
Speaker 8: shift to a set of algorithms that just fundamentally privilege

833
00:47:11,840 --> 00:47:15,160
Speaker 8: a different set of things. The language that Facebook uses

834
00:47:15,239 --> 00:47:17,640
Speaker 8: for this, and they are kind of like leading the

835
00:47:17,760 --> 00:47:20,600
Speaker 8: charge at this point because they're still dominant way back

836
00:47:20,680 --> 00:47:23,239
Speaker 8: in this era, is that they want to start privileging

837
00:47:24,239 --> 00:47:28,719
Speaker 8: quote emotionally engaging interactions. And what that means is that

838
00:47:29,000 --> 00:47:31,319
Speaker 8: instead of pushing up to the top of your feed

839
00:47:31,840 --> 00:47:34,359
Speaker 8: whatever is the link to an outbound website that they

840
00:47:34,440 --> 00:47:36,759
Speaker 8: think you were likely is to click on, they want

841
00:47:36,840 --> 00:47:40,399
Speaker 8: to promote whatever content in your feed, whether that's a link,

842
00:47:40,760 --> 00:47:44,040
Speaker 8: or it's a discussion, or it's a Facebook group or

843
00:47:44,120 --> 00:47:46,919
Speaker 8: it's a photo that is going to generate the most

844
00:47:47,000 --> 00:47:49,360
Speaker 8: discussion on that post. And the reason they do that

845
00:47:49,520 --> 00:47:51,200
Speaker 8: is they want to keep you on the platforms because

846
00:47:51,200 --> 00:47:53,360
Speaker 8: if you click that outbound link, now you're on BuzzFeed,

847
00:47:53,719 --> 00:47:55,960
Speaker 8: and Facebook doesn't make any money from you spending time

848
00:47:56,000 --> 00:47:57,799
Speaker 8: on BuzzFeed. They want you to spend as much time

849
00:47:58,520 --> 00:48:01,520
Speaker 8: on Facebook in discussion whatever as they can. And they

850
00:48:01,560 --> 00:48:04,359
Speaker 8: frame this it's like, oh, we're going to start giving

851
00:48:04,400 --> 00:48:07,480
Speaker 8: you They call it like meaningful connections or like meaningful

852
00:48:07,600 --> 00:48:10,359
Speaker 8: interactions as if it's going to bring you, like all

853
00:48:10,440 --> 00:48:12,719
Speaker 8: sorts of love and friendship, but of course that is

854
00:48:12,840 --> 00:48:16,920
Speaker 8: not at all what it brings, because these algorithms are

855
00:48:17,160 --> 00:48:22,720
Speaker 8: incredibly ruthless in running billions of what are basically tests

856
00:48:23,160 --> 00:48:26,920
Speaker 8: like little social science experiments every single day. And what

857
00:48:27,080 --> 00:48:29,839
Speaker 8: is the exact kind of content that will get people

858
00:48:30,000 --> 00:48:33,640
Speaker 8: to engage in these quote unquote emotionally engaging interactions, not

859
00:48:33,800 --> 00:48:35,239
Speaker 8: just to spend time on the site, but also to

860
00:48:35,320 --> 00:48:37,680
Speaker 8: post back in the site in ways that we'll get

861
00:48:37,719 --> 00:48:40,640
Speaker 8: other people to spend time on the site. And like,

862
00:48:40,800 --> 00:48:44,279
Speaker 8: what is the content and the set of emotions that

863
00:48:44,360 --> 00:48:48,279
Speaker 8: are going to be most engaging. And like, you know,

864
00:48:48,560 --> 00:48:51,960
Speaker 8: as any any student of human nature will know, it's

865
00:48:52,120 --> 00:48:55,160
Speaker 8: not the nice stuff. It's not you know, here's your

866
00:48:55,200 --> 00:48:58,680
Speaker 8: friend's baby, you know, your cousin got a new job promotion,

867
00:48:58,960 --> 00:49:03,560
Speaker 8: your aunt had a great it's outrage primarily, and especially

868
00:49:03,680 --> 00:49:08,160
Speaker 8: moral outrage. And it's anything that expressed fear or hatred

869
00:49:08,400 --> 00:49:11,360
Speaker 8: or discussed with some sort of social outgroup. And that

870
00:49:11,480 --> 00:49:15,120
Speaker 8: might be you know, political partisans on the other side

871
00:49:15,200 --> 00:49:20,000
Speaker 8: that for a lot of people, that's racial groups, religious groups, immigrants,

872
00:49:20,840 --> 00:49:23,840
Speaker 8: anything that cultivates a sense of like there is a

873
00:49:24,000 --> 00:49:26,080
Speaker 8: social group out there that I don't like, and I

874
00:49:26,160 --> 00:49:28,239
Speaker 8: find them to be scary, or I find them to

875
00:49:28,320 --> 00:49:30,879
Speaker 8: be offensive and I want to rally my in group

876
00:49:30,960 --> 00:49:35,000
Speaker 8: against them. That is the thing that the algorithms, as

877
00:49:35,080 --> 00:49:37,600
Speaker 8: they are being introduced to all of these platforms over

878
00:49:37,640 --> 00:49:41,560
Speaker 8: twenty fourteen and twenty fifteen, learn to surface above all else.

879
00:49:41,719 --> 00:49:46,200
Speaker 8: And Facebook's own researchers are tracking all of this, and

880
00:49:46,239 --> 00:49:50,120
Speaker 8: they're finding both that this is enormously successful at making

881
00:49:50,160 --> 00:49:52,800
Speaker 8: people spend more time on the website, but also that

882
00:49:52,840 --> 00:49:57,279
Speaker 8: it's really bad for them. There's this paper that's kind

883
00:49:57,320 --> 00:49:59,960
Speaker 8: of the last gasp of when Facebook used to put

884
00:50:00,000 --> 00:50:02,920
Speaker 8: publish research into what their algorithm does with users. In

885
00:50:03,040 --> 00:50:06,880
Speaker 8: May twenty fifteen, Facebook's researchers, because they have accessed all

886
00:50:06,920 --> 00:50:11,440
Speaker 8: this data, published this paper warning that this change to

887
00:50:11,560 --> 00:50:14,880
Speaker 8: this new algorithm was sorting people into not just like

888
00:50:15,000 --> 00:50:19,960
Speaker 8: minded discussions, but within those discussions was consistently surfacing whatever

889
00:50:20,320 --> 00:50:24,320
Speaker 8: was the angriest or most emotional or most extreme viewpoint

890
00:50:24,400 --> 00:50:27,400
Speaker 8: that everybody agreed with, and that that created an effect

891
00:50:27,440 --> 00:50:31,399
Speaker 8: that was quote associated with adopting more extreme attitudes over

892
00:50:31,520 --> 00:50:35,360
Speaker 8: time and misperceiving facts about current events, which is a

893
00:50:36,360 --> 00:50:39,440
Speaker 8: somewhat euphemistic way of saying that people became more extreme

894
00:50:39,520 --> 00:50:43,640
Speaker 8: in whatever beliefs they already held, and that they became

895
00:50:43,880 --> 00:50:47,759
Speaker 8: likelier to believe misinformation or conspiracies, because of course, if

896
00:50:47,800 --> 00:50:51,560
Speaker 8: you already are angry about something, a conspiracy about it

897
00:50:51,680 --> 00:50:53,400
Speaker 8: will make you feel even angrier.

898
00:50:54,400 --> 00:50:54,560
Speaker 7: Right.

899
00:50:54,960 --> 00:50:58,960
Speaker 1: I was fascinated to read how that information was at

900
00:50:59,000 --> 00:51:04,200
Speaker 1: one point public, and I think, like how it feels

901
00:51:04,400 --> 00:51:07,239
Speaker 1: completely inconceivable that they would publish anything like that to

902
00:51:07,320 --> 00:51:10,319
Speaker 1: the public just five years later or even two years later.

903
00:51:11,040 --> 00:51:14,200
Speaker 1: And how you know it was? It was well known

904
00:51:14,360 --> 00:51:17,440
Speaker 1: internally and it seems like I mean you explained I

905
00:51:17,520 --> 00:51:21,600
Speaker 1: think inside and also outside of Facebook, the sort of attempted,

906
00:51:22,560 --> 00:51:24,719
Speaker 1: the attempts to blow the whistle on like hey, this

907
00:51:24,920 --> 00:51:28,680
Speaker 1: is really not good for us. So I mean, it's

908
00:51:29,160 --> 00:51:32,800
Speaker 1: of course like profit is why that happens. But I

909
00:51:34,160 --> 00:51:38,279
Speaker 1: at what point do these platforms sort of switch to

910
00:51:39,360 --> 00:51:40,520
Speaker 1: infinite growth?

911
00:51:41,000 --> 00:51:45,719
Speaker 8: So that had always been the business model since those

912
00:51:45,840 --> 00:51:48,160
Speaker 8: first days of the news feed back on the like

913
00:51:48,880 --> 00:51:53,680
Speaker 8: late two thousands, But what happens actually around the same time,

914
00:51:53,760 --> 00:51:57,360
Speaker 8: around twenty fourteen, is they start to realize that the

915
00:51:57,600 --> 00:52:01,800
Speaker 8: pool of human attention is and that's what they trade in.

916
00:52:02,000 --> 00:52:05,000
Speaker 8: That's their asset that they are chasing is seconds of

917
00:52:05,080 --> 00:52:06,880
Speaker 8: your day that you're spending on the platform, so they

918
00:52:06,920 --> 00:52:09,759
Speaker 8: can sell ads against it. And they realize around twenty

919
00:52:09,800 --> 00:52:14,359
Speaker 8: fourteen that they've kind of reached saturation collectively on how

920
00:52:14,480 --> 00:52:17,920
Speaker 8: much of that they hold. Where at this point people

921
00:52:18,000 --> 00:52:21,720
Speaker 8: spend As of twenty fourteen, people on average are spending

922
00:52:21,760 --> 00:52:24,640
Speaker 8: more time on social media platforms than they do interacting

923
00:52:24,719 --> 00:52:28,880
Speaker 8: with other people socially in real life, which is staggering.

924
00:52:29,000 --> 00:52:32,000
Speaker 8: And that gap, of course has only grown since. So

925
00:52:32,480 --> 00:52:35,759
Speaker 8: what they realize when they get to this point where

926
00:52:35,800 --> 00:52:38,120
Speaker 8: they realize, okay, we've kind of saturated the market for

927
00:52:38,160 --> 00:52:41,080
Speaker 8: how much human attention we can captures, they get into

928
00:52:41,200 --> 00:52:44,440
Speaker 8: this arms race with each other for who can hold

929
00:52:45,080 --> 00:52:47,520
Speaker 8: more of that attention. And that is when they go

930
00:52:47,760 --> 00:52:51,680
Speaker 8: from just having a existing business model of infinite growth

931
00:52:52,160 --> 00:52:56,719
Speaker 8: to needing to, like you said, take every step that

932
00:52:56,840 --> 00:52:59,920
Speaker 8: they can, no matter how extreme, to try to outcompete

933
00:53:00,120 --> 00:53:03,359
Speaker 8: each other for how much of that attention they hold.

934
00:53:03,440 --> 00:53:05,440
Speaker 8: And this is when all of the social media companies

935
00:53:05,440 --> 00:53:08,640
Speaker 8: again is around like twenty fourteen, twenty fifteen, higher up,

936
00:53:09,200 --> 00:53:12,400
Speaker 8: all of the big names and artificial intelligence. Like every

937
00:53:12,880 --> 00:53:16,160
Speaker 8: major European and American researcher at every big research university

938
00:53:16,200 --> 00:53:19,759
Speaker 8: suddenly works at Facebook, which is like that seems unsurprising

939
00:53:19,840 --> 00:53:22,160
Speaker 8: now because these are trillion dollar companies, but at the

940
00:53:22,320 --> 00:53:25,040
Speaker 8: time that was really shocking because this is just like

941
00:53:26,040 --> 00:53:28,680
Speaker 8: this was like Fancy or MySpace. This is just like

942
00:53:28,800 --> 00:53:31,920
Speaker 8: a weird little website, and all of a sudden, all

943
00:53:31,960 --> 00:53:35,040
Speaker 8: of these like rock stars of artificial intelligence work for

944
00:53:35,160 --> 00:53:37,480
Speaker 8: them because what they are doing is they are trying

945
00:53:37,560 --> 00:53:41,080
Speaker 8: to make the social media algorithms that govern what you

946
00:53:41,200 --> 00:53:44,400
Speaker 8: see as smart and as ruthless as possible. This is

947
00:53:44,480 --> 00:53:49,040
Speaker 8: when YouTube sets towards this big internal goal they have

948
00:53:49,320 --> 00:53:53,440
Speaker 8: for one billion hours of daily watch time, meaning that

949
00:53:53,520 --> 00:53:56,680
Speaker 8: everyone who uses YouTube will collectively watch one billion hours

950
00:53:56,760 --> 00:53:59,719
Speaker 8: of video every single day, which is ten times what

951
00:54:00,480 --> 00:54:03,040
Speaker 8: they had across the platform at the time they set

952
00:54:03,080 --> 00:54:07,480
Speaker 8: this goal. So they're starting to really design their business

953
00:54:07,560 --> 00:54:11,719
Speaker 8: models and their engineering around the idea that they need

954
00:54:11,880 --> 00:54:16,120
Speaker 8: to in order to survive drastically increase the stickiness and

955
00:54:16,200 --> 00:54:19,080
Speaker 8: addictiveness of being on their platform, which is when they

956
00:54:19,160 --> 00:54:21,120
Speaker 8: kind of start getting into all of these dark arts

957
00:54:21,360 --> 00:54:23,960
Speaker 8: of emotional and psychological manipulation.

958
00:54:25,760 --> 00:54:27,440
Speaker 1: It feels so clear now and at the time where

959
00:54:27,440 --> 00:54:28,480
Speaker 1: you're like, this is weird.

960
00:54:29,040 --> 00:54:30,160
Speaker 2: Why am I so upset on.

961
00:54:32,680 --> 00:54:35,640
Speaker 8: Well, the thing that I always think about that I

962
00:54:35,840 --> 00:54:38,880
Speaker 8: did not appreciate at the time. I didn't get its significance.

963
00:54:38,960 --> 00:54:41,839
Speaker 8: But looking back, I'm like, oh, okay, I see how

964
00:54:41,920 --> 00:54:45,320
Speaker 8: that was. Like a big watership moment is around twenty fifteen,

965
00:54:45,400 --> 00:54:49,480
Speaker 8: when gamer gait goes from being this thing that is

966
00:54:49,600 --> 00:54:54,239
Speaker 8: happening on the fringes of Reddit and the fringes of YouTube,

967
00:54:54,280 --> 00:54:57,400
Speaker 8: where it's like a bunch of like young white guys

968
00:54:57,440 --> 00:55:00,040
Speaker 8: are really mad about video games for some reason I

969
00:55:00,080 --> 00:55:02,680
Speaker 8: don't understand why, to all of a sudden it's completely

970
00:55:02,760 --> 00:55:05,120
Speaker 8: dominant on all of the social platforms, and it's the

971
00:55:05,400 --> 00:55:08,680
Speaker 8: like number one thing day after day on the platforms,

972
00:55:08,719 --> 00:55:12,600
Speaker 8: and all of these like weirdo gamer Gate characters like

973
00:55:12,760 --> 00:55:15,439
Speaker 8: Milo Gianopolis and Mike Cernovich, all of a sudden they're

974
00:55:15,440 --> 00:55:18,719
Speaker 8: like mainstream political figures. And that is we know now

975
00:55:18,800 --> 00:55:22,879
Speaker 8: in retrospect, because this is the time when social media

976
00:55:22,920 --> 00:55:27,520
Speaker 8: algorithms started to realize that stuff like gamer Gate was

977
00:55:27,640 --> 00:55:31,600
Speaker 8: going to be so so effective at increasing engagement. So

978
00:55:31,680 --> 00:55:34,359
Speaker 8: that's why when you go away from the social media

979
00:55:34,400 --> 00:55:37,080
Speaker 8: algorithms of the era of like the dress what you

980
00:55:37,200 --> 00:55:39,719
Speaker 8: get instead of the social media algorithms of gamer Gate,

981
00:55:39,840 --> 00:55:42,120
Speaker 8: which I would not consider a trade up.

982
00:55:42,760 --> 00:55:46,000
Speaker 1: This is also the time where which I feel like

983
00:55:46,040 --> 00:55:49,240
Speaker 1: ties right into the Milo stuff, where Breitbart really starts

984
00:55:49,840 --> 00:55:52,359
Speaker 1: to pop off, and it feels to me, i mean,

985
00:55:53,480 --> 00:55:59,560
Speaker 1: very diabolical match of the BuzzFeed model of like luring

986
00:55:59,600 --> 00:56:03,200
Speaker 1: people in with really splashy headlines. As we're like coming

987
00:56:03,280 --> 00:56:05,359
Speaker 1: out of this era of the Dress and things were

988
00:56:05,400 --> 00:56:10,919
Speaker 1: getting more politicized and engagement driven to you know, really

989
00:56:11,040 --> 00:56:15,160
Speaker 1: monetize and push outrage. What are the success stories and

990
00:56:15,280 --> 00:56:18,080
Speaker 1: how do they sort of shape what the new algorithm favors.

991
00:56:19,200 --> 00:56:20,839
Speaker 8: That's a great way to put it. I think you're

992
00:56:20,920 --> 00:56:26,120
Speaker 8: exactly right that if BuzzFeed and like upworthy were they

993
00:56:26,320 --> 00:56:29,920
Speaker 8: sites that embodied and benefited from the kind of pre

994
00:56:30,120 --> 00:56:35,160
Speaker 8: twenty fifteen social media ecosystem and algorithms, then the site

995
00:56:35,200 --> 00:56:38,480
Speaker 8: that embodies and most benefited from the post twenty fifteen

996
00:56:38,600 --> 00:56:42,080
Speaker 8: social media algorithms is definitely Brightbart. There was this huge

997
00:56:43,160 --> 00:56:46,160
Speaker 8: Harvard study or it was like led through Harvard, but

998
00:56:46,200 --> 00:56:48,680
Speaker 8: it was a ton of different scholars that came out

999
00:56:48,880 --> 00:56:52,439
Speaker 8: after the twenty sixteen election and was kind of trying

1000
00:56:52,480 --> 00:56:55,960
Speaker 8: to ask, like, Okay, what happened, what was the like

1001
00:56:56,120 --> 00:56:58,520
Speaker 8: something the internet played some role in the twenty sixteen election.

1002
00:56:58,640 --> 00:57:00,399
Speaker 8: Social media played some role, but we're I'm not quite

1003
00:57:00,400 --> 00:57:01,879
Speaker 8: sure what it is. So let's do like a big

1004
00:57:02,040 --> 00:57:06,920
Speaker 8: systemic investigation into what the social web looked like in

1005
00:57:06,960 --> 00:57:09,520
Speaker 8: the run up to the twenty sixteen election. And one

1006
00:57:09,520 --> 00:57:12,759
Speaker 8: of the big things they found is that from May

1007
00:57:13,040 --> 00:57:17,200
Speaker 8: twenty fifteen to November twenty sixteen, when the election was held,

1008
00:57:17,440 --> 00:57:19,400
Speaker 8: which is kind of the onset of that era of

1009
00:57:19,440 --> 00:57:24,040
Speaker 8: the new social media algorithms, Breitbart was the third most

1010
00:57:24,120 --> 00:57:28,240
Speaker 8: shared media outlet on all of social media, which is

1011
00:57:28,480 --> 00:57:32,960
Speaker 8: crazy when you know that Breitbart has like no staff,

1012
00:57:33,640 --> 00:57:36,480
Speaker 8: they have no budget. It's a terrible experience to be

1013
00:57:36,640 --> 00:57:40,120
Speaker 8: on their website. They don't produce very many articles. And

1014
00:57:40,360 --> 00:57:42,880
Speaker 8: before this algorithmic shift, they had been a teeny tiny

1015
00:57:42,920 --> 00:57:45,720
Speaker 8: little website with no readership. And there was like this

1016
00:57:45,880 --> 00:57:48,480
Speaker 8: kind of narrative that like, oh, yes, Steve Bannon, who's

1017
00:57:48,520 --> 00:57:50,960
Speaker 8: running Breitbart, is some like genius of the dark arts

1018
00:57:51,000 --> 00:57:52,880
Speaker 8: of the social web. And what we learned from this

1019
00:57:52,960 --> 00:57:55,280
Speaker 8: Harvard study and from a lot of subsequent investigations is

1020
00:57:55,320 --> 00:57:58,160
Speaker 8: that he was not. The people of Breitbart were not

1021
00:57:58,480 --> 00:58:03,160
Speaker 8: these geniuses. They were passive beneficiaries of the algorithms of

1022
00:58:03,200 --> 00:58:07,800
Speaker 8: Facebook and Twitter, basically plucking this website and similar websites

1023
00:58:07,840 --> 00:58:11,280
Speaker 8: out and pushing them in front of huge audiences of people.

1024
00:58:11,360 --> 00:58:15,920
Speaker 8: Like Breitbart got more audience and engagement on Facebook than

1025
00:58:16,080 --> 00:58:18,360
Speaker 8: Fox News did in the run up to the election,

1026
00:58:18,560 --> 00:58:21,280
Speaker 8: and Fox News is like a bajillion dollar company with

1027
00:58:21,440 --> 00:58:22,360
Speaker 8: hundreds of reporters.

1028
00:58:23,000 --> 00:58:25,560
Speaker 1: I mean, and certainly in the case of Breitbart, it

1029
00:58:25,680 --> 00:58:31,440
Speaker 1: was just saying shit and presenting it as news, and

1030
00:58:32,400 --> 00:58:36,560
Speaker 1: you know, like I wasn't saying fascistic shit, but there

1031
00:58:36,640 --> 00:58:38,360
Speaker 1: were times where I was just kind of saying shit,

1032
00:58:38,520 --> 00:58:40,720
Speaker 1: and they're like, and she's a reporter. I don't know,

1033
00:58:40,840 --> 00:58:43,960
Speaker 1: it's interesting to reflect on.

1034
00:58:45,080 --> 00:58:47,200
Speaker 8: Yeah, that's a really interesting point. I hadn't thought about

1035
00:58:47,240 --> 00:58:50,080
Speaker 8: that before. But you're right that this was kind of

1036
00:58:51,160 --> 00:58:53,760
Speaker 8: the first stage and a shift that now feels much

1037
00:58:53,800 --> 00:58:58,040
Speaker 8: more complete from getting your news from a news source

1038
00:58:58,360 --> 00:59:00,479
Speaker 8: to then you're getting your news from a new source

1039
00:59:00,560 --> 00:59:03,640
Speaker 8: repackaged for social media, So then you're getting your news

1040
00:59:03,680 --> 00:59:06,120
Speaker 8: from a news source that is saying shit. I now

1041
00:59:06,200 --> 00:59:08,040
Speaker 8: most of us get our news from people who are

1042
00:59:08,120 --> 00:59:10,920
Speaker 8: just saying shit on social media, and we kind of

1043
00:59:11,120 --> 00:59:14,840
Speaker 8: like trust or hope that the like viral posts that

1044
00:59:14,960 --> 00:59:18,560
Speaker 8: we're reading is at some point sourced from something real,

1045
00:59:19,040 --> 00:59:21,440
Speaker 8: and sometimes it is, and it's just spun in a

1046
00:59:21,480 --> 00:59:24,720
Speaker 8: way to like get more engagement on social media. But

1047
00:59:25,400 --> 00:59:27,760
Speaker 8: you know, it's just as possible that it's made up,

1048
00:59:28,040 --> 00:59:30,600
Speaker 8: or that it's exaggerated, or that it's out of context.

1049
00:59:31,120 --> 00:59:34,640
Speaker 8: So it is, in retrospect, like the start of a

1050
00:59:34,960 --> 00:59:39,600
Speaker 8: larger shift to the just saying shit era of media consumption,

1051
00:59:39,800 --> 00:59:42,800
Speaker 8: because on some level, you know, even though we do

1052
00:59:43,000 --> 00:59:47,400
Speaker 8: all care about getting accurate information from credible sources, our

1053
00:59:47,520 --> 00:59:52,080
Speaker 8: brains unfortunately are really really drawn to things that are

1054
00:59:53,240 --> 00:59:57,440
Speaker 8: emotionally satisfying or that delivered like outrage which feels very

1055
00:59:57,440 --> 00:59:59,880
Speaker 8: affirming to indulge in, or that deliver a sense of

1056
01:00:00,200 --> 01:00:04,440
Speaker 8: like moral righteousness or in group versus out group, and

1057
01:00:04,560 --> 01:00:08,320
Speaker 8: that can overpower that desire that we do also feel

1058
01:00:08,360 --> 01:00:11,240
Speaker 8: for real credible information, which is of course only gotten

1059
01:00:11,280 --> 01:00:12,320
Speaker 8: worse since twenty sixteen.

1060
01:00:13,200 --> 01:00:15,640
Speaker 1: Thanks so much to Max for speaking with me in

1061
01:00:15,760 --> 01:00:18,880
Speaker 1: full disclosure. His cat is so large now I have

1062
01:00:18,960 --> 01:00:22,120
Speaker 1: to be honest in the interest of contextualizing the dress

1063
01:00:22,240 --> 01:00:25,480
Speaker 1: in real time, I did leave something off about its

1064
01:00:25,600 --> 01:00:29,080
Speaker 1: longer future. To this day, there's an entire page about

1065
01:00:29,120 --> 01:00:32,560
Speaker 1: the dress on the Roman Original's website where it was manufactured,

1066
01:00:32,720 --> 01:00:36,520
Speaker 1: calling it the quote phenomenon that revealed differences in human

1067
01:00:36,640 --> 01:00:39,920
Speaker 1: color perception, which have been the subject of ongoing scientific

1068
01:00:40,000 --> 01:00:43,120
Speaker 1: investigation in neuroscience and vision science.

1069
01:00:43,720 --> 01:00:45,320
Speaker 5: I mean sure.

1070
01:00:46,000 --> 01:00:48,440
Speaker 1: And while some subjects on this show will require a

1071
01:00:48,520 --> 01:00:51,800
Speaker 1: bonk on the head to fully remember who is Chili nighbor,

1072
01:00:51,920 --> 01:00:55,040
Speaker 1: who is being dad sidebart, the mid character is so

1073
01:00:55,200 --> 01:00:59,720
Speaker 1: often insert name of food, insert type of person, whatever,

1074
01:01:00,120 --> 01:01:03,280
Speaker 1: but the dress rarely needs introduction if the person was

1075
01:01:03,400 --> 01:01:06,360
Speaker 1: online at the time. There were retrospectives of the dress

1076
01:01:06,400 --> 01:01:10,200
Speaker 1: story being written as recently as last year. When I'm

1077
01:01:10,240 --> 01:01:13,000
Speaker 1: building out episodes for this show, step one is to

1078
01:01:13,080 --> 01:01:15,600
Speaker 1: reach out to the main character themselves to see if

1079
01:01:15,600 --> 01:01:18,200
Speaker 1: they want to talk. After all, the dress was for

1080
01:01:18,320 --> 01:01:21,320
Speaker 1: someone's wedding, and the mom who wore the dress stated

1081
01:01:21,400 --> 01:01:24,160
Speaker 1: at the time of the incessant optical illusion that she

1082
01:01:24,400 --> 01:01:27,680
Speaker 1: was annoyed that she was being excluded from most news coverage.

1083
01:01:27,880 --> 01:01:31,520
Speaker 1: Cecilia and the married couple got the classic fifteen minutes

1084
01:01:31,600 --> 01:01:34,560
Speaker 1: treatment for this era, the married couple Grace and Keir

1085
01:01:34,920 --> 01:01:37,560
Speaker 1: and Cecilia and her partner Paul, were flown out to

1086
01:01:37,760 --> 01:01:40,120
Speaker 1: la to be on the Ellen Show, and the couple

1087
01:01:40,280 --> 01:01:43,800
Speaker 1: got a briefcase full of ten thousand American dollars. The

1088
01:01:43,920 --> 01:01:47,760
Speaker 1: mother and stepfather of the bride got underwear for some reason,

1089
01:01:48,200 --> 01:01:50,560
Speaker 1: half black and blue and half white and gold, and

1090
01:01:50,680 --> 01:01:54,280
Speaker 1: that was it, and Cecilia was pissed from a Guardian

1091
01:01:54,360 --> 01:01:55,880
Speaker 1: piece from late twenty fifteen.

1092
01:01:56,400 --> 01:01:57,880
Speaker 3: Should it be on display somewhere?

1093
01:01:58,000 --> 01:02:01,360
Speaker 1: Blaisdell wonders, should it be in a whatever? It still

1094
01:02:01,400 --> 01:02:04,840
Speaker 1: got sweaty marks on though, need the clean So nine

1095
01:02:04,960 --> 01:02:08,000
Speaker 1: years later, I wanted to see where everyone was, and

1096
01:02:08,120 --> 01:02:11,560
Speaker 1: that's where this story takes an especially dark turn. When

1097
01:02:11,560 --> 01:02:13,560
Speaker 1: I went to find out where that couple is now,

1098
01:02:14,080 --> 01:02:17,360
Speaker 1: I found this headline from July twenty twenty three. Man

1099
01:02:17,480 --> 01:02:21,360
Speaker 1: behind viral blue black dress illusion charged with trying to

1100
01:02:21,520 --> 01:02:24,440
Speaker 1: kill wife. I don't want to rehash it too heavily here,

1101
01:02:24,800 --> 01:02:28,840
Speaker 1: but the relationship had been tremendously abusive since before the

1102
01:02:28,960 --> 01:02:33,920
Speaker 1: dress and their marriage, culminating in husband Keir making repeated

1103
01:02:34,440 --> 01:02:38,240
Speaker 1: violent attempts on Grace's life isolating her from friends and

1104
01:02:38,360 --> 01:02:41,600
Speaker 1: family and attempting to murder her during the spring of

1105
01:02:41,680 --> 01:02:44,880
Speaker 1: twenty twenty two. He then went to court and denied

1106
01:02:44,960 --> 01:02:49,560
Speaker 1: all charges and most clickbait in twenty twenty three because yes,

1107
01:02:49,960 --> 01:02:53,080
Speaker 1: all of the same outlets reported on this story again

1108
01:02:53,560 --> 01:02:57,160
Speaker 1: made the somewhat lazy observation that the dress had previously

1109
01:02:57,280 --> 01:03:00,480
Speaker 1: been used in a domestic violence awareness camp pain in

1110
01:03:00,600 --> 01:03:04,120
Speaker 1: South Africa back in twenty fifteen, featuring a woman wearing

1111
01:03:04,200 --> 01:03:06,880
Speaker 1: the dress in white and gold while covered in black

1112
01:03:06,960 --> 01:03:09,560
Speaker 1: and blue bruises. Why is it so hard to see

1113
01:03:09,600 --> 01:03:12,400
Speaker 1: black and blue? The ad asked. I think this ad

1114
01:03:12,560 --> 01:03:15,760
Speaker 1: is very weird, even if the intention was well placed,

1115
01:03:16,160 --> 01:03:18,680
Speaker 1: and the wave of twenty twenty three press connecting it

1116
01:03:18,840 --> 01:03:22,080
Speaker 1: to the real life terror campaign taken out on Grace

1117
01:03:22,520 --> 01:03:26,080
Speaker 1: felt just as wrong because virtually all of those pieces,

1118
01:03:26,400 --> 01:03:30,000
Speaker 1: while sympathetic to her, ended in some tired version of

1119
01:03:30,560 --> 01:03:33,760
Speaker 1: By the way, the dress was black and blue and

1120
01:03:33,960 --> 01:03:36,880
Speaker 1: as of this month. In May twenty twenty four, I

1121
01:03:37,000 --> 01:03:39,960
Speaker 1: am recording this a month after we finished this episode.

1122
01:03:40,640 --> 01:03:44,480
Speaker 1: Kiir Johnston is being held in prison after pleading guilty

1123
01:03:44,840 --> 01:03:48,160
Speaker 1: to attacking and attempting to kill Grace back in twenty

1124
01:03:48,240 --> 01:03:51,720
Speaker 1: twenty two. At the time, Grace called and texted people

1125
01:03:51,800 --> 01:03:55,200
Speaker 1: for help after years of reporting abuse and said that

1126
01:03:55,280 --> 01:03:57,640
Speaker 1: her husband was trying to kill her after she was

1127
01:03:57,760 --> 01:04:02,360
Speaker 1: violently attacked, strangled, and was threatened with a knife. As

1128
01:04:02,400 --> 01:04:05,200
Speaker 1: of this recording, the case is ongoing, and we wish

1129
01:04:05,280 --> 01:04:09,160
Speaker 1: Grace nothing but peace and getting as far away from

1130
01:04:09,240 --> 01:04:13,240
Speaker 1: any of this fucking discourse as she needs to. And

1131
01:04:13,320 --> 01:04:15,840
Speaker 1: it's further proof that any Internet story on a long

1132
01:04:15,960 --> 01:04:19,200
Speaker 1: enough timeline begins to reflect the ugliness of the world

1133
01:04:19,480 --> 01:04:23,440
Speaker 1: that the Internet reflects and so often warps. Okay, cutting

1134
01:04:23,520 --> 01:04:27,160
Speaker 1: back into the original episode here, I'm sort of hesitant

1135
01:04:27,240 --> 01:04:29,880
Speaker 1: to say that there's a clear lesson to be learned

1136
01:04:29,920 --> 01:04:33,400
Speaker 1: from the saga of the dress, but it certainly encapsulates

1137
01:04:33,400 --> 01:04:37,080
Speaker 1: a moment in Internet history that feels ungo backable, and

1138
01:04:37,120 --> 01:04:39,640
Speaker 1: there's no better example of that than all the writers

1139
01:04:39,680 --> 01:04:42,120
Speaker 1: who were paid at the time to make it mean

1140
01:04:42,240 --> 01:04:46,600
Speaker 1: something outside of being an increasingly rare monocultural moment that

1141
01:04:46,800 --> 01:04:50,480
Speaker 1: swirled in normal people with tech profits and our attention.

1142
01:04:51,120 --> 01:04:54,800
Speaker 1: So the dress means something, but what exactly that is

1143
01:04:55,120 --> 01:04:58,280
Speaker 1: is a little elusive. Almost ten years on, I feel

1144
01:04:58,360 --> 01:05:00,919
Speaker 1: kind of nostalgic for a time where the Internet could

1145
01:05:01,040 --> 01:05:03,680
Speaker 1: unite over a neutral issue. But as a twenty two

1146
01:05:03,760 --> 01:05:06,240
Speaker 1: year old clickbait writer, I didn't even have the time

1147
01:05:06,320 --> 01:05:10,400
Speaker 1: to appreciate it because I needed to form an edgy, smart,

1148
01:05:10,520 --> 01:05:14,080
Speaker 1: adjacent opinion about it as quickly as possible. Here's a

1149
01:05:14,120 --> 01:05:16,640
Speaker 1: passage from a reaction to the dress and the Lama's

1150
01:05:16,680 --> 01:05:20,160
Speaker 1: success as stories on the heels of the net neutrality decision.

1151
01:05:20,640 --> 01:05:23,840
Speaker 1: The essay is called the open Internet will keep us

1152
01:05:23,880 --> 01:05:28,480
Speaker 1: stupid and happy. At this point, it's unfathomable to think

1153
01:05:28,520 --> 01:05:31,160
Speaker 1: of anything short of a gale force windstorm full of

1154
01:05:31,240 --> 01:05:34,960
Speaker 1: knives that could prevent the Internet from brimming with memes, gifts,

1155
01:05:35,040 --> 01:05:37,520
Speaker 1: and asenine materials from content farms.

1156
01:05:38,080 --> 01:05:38,280
Speaker 7: Hell.

1157
01:05:38,480 --> 01:05:40,560
Speaker 1: I used to write for a content farm in Boston,

1158
01:05:40,800 --> 01:05:44,000
Speaker 1: and yes, I have written an article called how Seth

1159
01:05:44,080 --> 01:05:46,480
Speaker 1: MacFarlane's A Million Ways to Die in the West can

1160
01:05:46,560 --> 01:05:49,040
Speaker 1: teach us about how to run our tech companies, and

1161
01:05:49,200 --> 01:05:53,080
Speaker 1: that is objectively gross. The Internet is stupid, but it

1162
01:05:53,200 --> 01:05:56,200
Speaker 1: was almost stupid and expensive. Thanks to the net neutrality

1163
01:05:56,280 --> 01:05:58,920
Speaker 1: vote passed yesterday, we won't need to worry about our

1164
01:05:59,000 --> 01:06:05,360
Speaker 1: access to lama and confusing dresses being hindered for now. Anyway, Yeah,

1165
01:06:05,440 --> 01:06:08,880
Speaker 1: I wrote this, and what the fuck was I talking about? Anyways?

1166
01:06:08,920 --> 01:06:11,560
Speaker 1: Good for her. I'm sure she'll never overthink anything again.

1167
01:06:13,520 --> 01:06:17,080
Speaker 1: Sixteenth Minute is a production of Cool Zone Media and iHeartRadio.

1168
01:06:17,520 --> 01:06:20,920
Speaker 1: It is written, hosted, and executive produced by me Jamie Loftus.

1169
01:06:21,080 --> 01:06:24,320
Speaker 1: Our other executive producers are Sophie Lichterman and Robert Evans,

1170
01:06:24,720 --> 01:06:28,320
Speaker 1: and our supervising producer and editor is Ian Johnson. Our

1171
01:06:28,360 --> 01:06:30,600
Speaker 1: theme song is by Sadie Dupui and I would like

1172
01:06:30,680 --> 01:06:34,200
Speaker 1: to thank all of the pets, Anderson the Dog, Mike, Kats,

1173
01:06:34,200 --> 01:06:36,720
Speaker 1: Flee and Casper, and my pet rock Bird, who will

1174
01:06:36,760 --> 01:06:38,400
Speaker 1: outlive us all. Bye e