Cambridge Analytica, Part I (with Kevin Roose and Casey Newton)

Kevin Roose and Casey Newton are High-Tech Savants. The co-hosts of the Hard Fork Podcast were on the front lines of the Facebook Data Scandal, and today they help Ed break down just how much of your data (yes, you dear listener!) was leaked and misused for political purposes. Find out what laws Cambridge Analytica broke in today's tech-heavy SNAFU. Don't forget to subscribe to the SNAFU YouTube channel: www.youtube.com/@SNAFUPod Buy the SNAFU book: www.snafu-book.com http://www.snafu-book.com/ See omnystudio.com/listener https://omnystudio.com/listener for privacy information.

• 0:01Speaker 00

  In some very real ways, Cambridge Analytica changed my life.

• 0:03Speaker 01

  Casey is the only person in America who benefited from the Cambridge Analytica scandal. He's like, "This was great for me."

• 0:20Speaker 02

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• 2:15Speaker 06

  Welcome to Snafu, the podcast about history's greatest screw ups. I'm your host, Ed Helms, and each episode, as you know, I cover an enormous screw up from history to see what we can learn from humanity's biggest mistakes. My guests today are truly two of like, just the most awesome people. Truly, I'm so excited. We have Kevin Roos, who is an award winning tech columnist for the New York Times, frequently covering Silicon Valley, social media and tech developments. He's also the author of several books, including The AGI Chronicles, The Inside Story of the Race to Create an Artificial Superintelligence, releasing later this year. Welcome, Kevin Roos.

• 3:00Speaker 01

  Thank you.

• 3:01Speaker 06

  And we also have not just Kevin, we also have Casey Newton, who is the founder and editor of Platformer, a publication about the intersection of democracy and tech, and was previously a senior editor at The Verge. Together, these two come together in a podcasting Voltron as the podcast Hard Fork, which is brilliant. It's hugely popular. It is incredibly successful. It is a New York Times podcast, and it is about the rapidly changing tech world. And somehow, it's incredibly grounded and informative, even when these things feel dark and scary. And it's also insanely funny and entertaining. Welcome, Casey and Kevin.

• 3:42Speaker 00

  Thank you, Ed. It's great to be here. Thank you for those kind words. And I'm sorry Kevin's bio is so long. We're trying to cut that down a little.

• 3:48Speaker 01

  I just keep adding fake things to it. Olympic gold medalist, Nobel Prize winner.

• 3:56Speaker 06

  That's all good. I think, I think anyone can claim a Nobel at this point. What is the, I'm just so curious, as a, as a fan of Hard Fork, like, and I'm sure you get asked this a lot, but were you guys friends before Hard Fork? Or did you sort of come together? Were you, was this sort of like a more of a business venture that, and then, because you do have the dynamic of people who seem to just have known each other a long time. It's a very easy vibe.

• 4:24Speaker 00

  I think that the answer is that we were friends who have become much closer friends since we started doing the show. Like Kevin and I knew each other from San Francisco tech reporting circles. We would see each other all over town as we were, you know, covering this Google event, that Apple event. But both of us really wanted to start a podcast. And when we looked around, and the truth is, both of us tried very hard to find someone else to do the show with, and we just kept coming back to each other. We were just kept coming back like, I think this is honestly the only person I could imagine doing this with. And like, almost five years later, since we started having that conversation, like, I feel exactly the same way. He's the only one for me.

• 4:59Speaker 01

  Oh, it's a charade. We actually hate each other. This is just a sort of Kabuki theater bit we do.

• 5:05Speaker 00

  Yeah. This is the first time we've talked outside of a Hard Fork taping in several years.

• 5:11Speaker 06

  Oh, well, you're putting on a good show. I'm definitely buying it. I think one of the reasons Hard Fork works for me, just as a fan, is that I just trust you guys. I feel like you're incredibly well informed, but you also have this uncanny ability to stay calm and steady when things feel so terrifying. And I'm just wondering, as a non-super tech person, I just feel so confused so much. And you guys are such a steady, calming force. How do you do that? Like, how do you? You're in the middle of it. It would seem like you would just be running around with your hair on fire all the time.

• 5:46Speaker 00

  I mean, I think both of us are optimists by nature. We're both people who have observed that, like, for the most part, technology has been good for people. Like, we're not people who wish that we could go back to an agrarian economy and sort of do subsistence farming. Like, I like having an iPad, you know? And so we want to believe that as uncertain and scary as the world often is, we are going to muddle through somehow. And so, you know, while we pay a lot of attention to the many, many things that are going wrong, the snafus, if you will, we also think there's like some pretty cool stuff happening in the world, and we like pointing that out whenever we can.

• 6:24Speaker 01

  I think we try to be skeptical without being cynical.

• 6:29Speaker 06

  Great.

• 6:29Speaker 01

  Would be the way I would put it. You know, I think we try to be reporters and question authority and the official narratives, but we're also not sort of knee jerk, reflexively

• 6:43Speaker 01

  cynical about the fact that some of this technology is quite good and improving in ways that should make us both excited and fearful. So that's the balance we try to strike. We try to just be really honest. Some weeks, we're really terrified and you can hear that in the show. Some weeks, we're more excited and hopefully you could hear that, too.

• 7:00Speaker 06

  Well, that is very well said, and I love the distinction between skepticism and cynicism. And I feel like that's not a distinction that is made often enough and sometimes in our own guts. Like, I know I cross over. I like to think I'm just a sort of healthy skeptic, but sometimes that cynicism creeps in and, boy, does it get dark. Oh, boy. But that's why you're here. That's why Hard Fork is there to uplift all of us. And it's why I am so thrilled to have you both on today. I picked a doozy of a snafu to discuss, and it's one that you both know inside and out, which is kind of interesting because that's a little bit of a flip of our typical format.

• 7:45Speaker 06

  Usually, I'm telling the guest a snafu that they may or may not know anything about. And either way, it's a surprise, whatever the story is. And in that way, I'm sort of the professor, they're the student. But in this case, this is a story that you both deeply reported on at the time it was happening, and you are deeply well informed about. So I am very much the student. I'm excited to, I'll still be the narrative anchor. I'm going to kind of walk us through the story, but I'm so eager to learn from you guys and hear from you the sort of details and color that we just ordinarily wouldn't get in an episode like this. So, thank you for being here, and we are about to dive into the story of Cambridge Analytica.

• 8:36Speaker 06

  Right off the bat, guys, what does that conjure in you? Tension, excitement, humor? What? What is that?

• 8:44Speaker 00

  It makes me honestly a little bit nostalgic. Cambridge Analytica was honestly really important in my life. I had started writing a newsletter just a few months before that scandal. And I was mostly at the time, writing about the backlash to Facebook that had begun after the 26th US presidential election. And my newsletter was getting, you know, a little traction here, a little traction there. And then Cambridge Analytica happened, and all of a sudden, it felt like, to some people, the biggest story in the world. And so, my newsletter grew. It wound up enabling me to like, quit my job, start a podcast. So like, in some very real ways, Cambridge Analytica changed my life.

• 9:18Speaker 01

  Casey is the only person in America who benefited from the Cambridge Analytica scandal. He's like, this was great for me.

• 9:24Speaker 06

  I love it.

• 9:28Speaker 01

  I have distant memories. I have the memory of a goldfish, so I forget things that I reported about last week. But when you say the words, I am filled with a kind of, yeah, mid 2010s nostalgia. I started thinking about the Harlem Shake, you know, and other, the Ice Bucket Challenge.

• 9:47Speaker 06

  Yes, exactly.

• 9:48Speaker 01

  And sort of other phenomena from that era.

• 9:50Speaker 06

  Of course. Well, just to give the audience a little bit of grounding, the Cambridge Analytica data harvesting scandal of 2018 was, is considered one of the most massive and possibly worst data misuse cases in history. This was eight years ago, or more. No, like, what? It was 2014, just 12 years ago? What year are we in?

• 10:15Speaker 00

  Well, so this actually gets to a really interesting and important thing.

• 10:18Speaker 06

  2018, yes. Like, where do you start it?

• 10:20Speaker 00

  Yeah, so, one of the reasons why Cambridge Analytica wound up being a really weird scandal was that most of the details were known years before it turned into this conflagration. And it was only in the aftermath of Trump's election that a lot of Americans said, wait, what exactly was going on? And then it blew up.

• 10:39Speaker 06

  Oh, boy. All right, let's dive in. To kick off our snafu, we're going to travel back in time, like we were saying, to the mid 2010s. So just to help reset your culture clocks, Obama was in his second term, Russia has annexed Crimea, everyone's freaking out about Ebola. In the tech world, Apple Watches and other kinds of wearables are on the rise. Um, yeah, as Kevin mentioned, the ice bucket challenge, we were all pouring ice water on our heads. And Instagram was primarily just photos of eggs benedict and sunsets, the good old days. Um, AI still felt like sci fi back then. Chat GPT wasn't even a blip. We were

• 11:17Speaker 06

  young, optimistic, and really, maybe a little too casual about clicking "I agree" on terms and conditions that no one read. How naive we were. It was a better time. Now, while we were happily posting memes and baby photos, we didn't even think to worry about what was happening to all the data that we were putting out into social media, or what someone could possibly do with it. But I'm kind of getting ahead of myself. Let's start with something innocent. Facebook quiz apps. Do you remember these? The harmless time wasters, like, what is your ice cream IQ? Or what carb are you emotionally?

• 11:58Speaker 00

  Which Harry Potter house are you in?

• 12:01Speaker 06

  Exactly. Which Harry Potter house? Um, did you take any of these quizzes? Do you remember any results?

• 12:07Speaker 00

  I remember that I was, I was all of the carbs, actually. It turned out that I identified equally with all of them. Yeah.

• 12:14Speaker 06

  Do we know any, what, what, was anyone a Gryffindor?

• 12:18Speaker 00

  I feel like Kevin is definitely a Slytherin. That's such a hufflepuff thing to say.

• 12:26Speaker 06

  That's a burn, too.

• 12:27Speaker 00

  No, Kevin loves to scheme.

• 12:29Speaker 06

  I took one and I, it turns out I was, it was like, "Which bagel are you?" And I'm an "everything bagel," which I think was supposed to be flattering, but I don't like everything bagels. I think they're kinda gross. So, all these quizzes, they seemed kinda innocent and fun, but at least one in particular, we now know, was quite nefarious. And this was an app called "This Is Your Digital Life." Seems harmless enough, and it claimed to be for academic research. "This Is Your Digital Life" was a personality quiz produced by a data scientist named Alexander Kogan and his company, Global Science Research, which, right away, I just don't trust. Global Science Research. It's, uh, there's too much going on there.

• 13:14Speaker 00

  I think that's the same company from the alien movies.

• 13:16Speaker 06

  Exactly.

• 13:17Speaker 00

  You know?

• 13:18Speaker 06

  Yeah. Paul Reiser is an executive, and he's just, he's a little smarmy. Weird vibes. So, this was in 2014, and here's where it starts getting icky. It wasn't just collecting your answers, it was also quietly scooping up data on your Facebook friends, who definitely did not sign up for that. So, thanks to a handy Facebook API loophole, the app could access information on jobs, education, location, relationship status, and liked pages. So, while you were figuring out which pasta shape matched your vibe, this app was building a surprisingly detailed dossier on you, your psychology, and that of your entire digital entourage.

• 14:01Speaker 06

  Question: Do you think that the average American at that time had any sense of how this kind of personal information that everyone was sharing just exhaustively could be turned against them? Or were we just high on digital narcissism?

• 14:22Speaker 00

  No, I mean, Americans are very interesting in that they will say that privacy is very important to them, but they will give up their privacy for almost anything, right? It's like, they will tell you, you know, that they don't want to, you know, put the name of their children online, but if it got them 10% off at Ross Dress for Less, they will absolutely give you all that and more. So, companies are always sort of doing this weird dance where they're trying to get you to reveal as much as they possibly can without it accidentally blowing up in their face.

• 14:52Speaker 01

  Well, and this was also an era that was called sort of the Open Graph era of Facebook. Basically, they were trying to turn Facebook from an app where you would go and, you know, stalk your crushes from college or whatever, to a platform where other apps could build things. There were apps like Farmville that you could play inside Facebook. You could use Facebook to log into Spotify or any other number of services. And that was part of this quiz push, was like, you could build things on top of Facebook, and then Facebook would actually send some of that data to the developers of the quizzes.

• 15:35Speaker 01

  This was the same protocol, the same process that they used to connect people with Farmville Games and Spotify.

• 15:42Speaker 06

  The best-case use of that data would just be for that app to reach more users? Or, at this point, what's the reason for being just so give and take with this data?

• 15:56Speaker 00

  So, Facebook used to have this very permissive, what they call an API, an application programming interface. It's essentially just a piece of software that lets other pieces of software talk to each other. And there was a time when Facebook invested really heavily in that because they wanted, essentially, every other software to connect whatever they were building to Facebook. Facebook thought, this is the way that we are going to grow and take over the world, is essentially, everything runs through this. And the way that Facebook was able to attract so many of those people to its platforms was by saying, "We will give you data that you can't get." Anywhere else, right? There aren't a lot of other places where you can go if you're a legitimate researcher, a shady researcher, somebody who's making a mobile game and immediately

• 16:40Speaker 00

  get not just my name and my email address and my phone number, but also at the time, the names of all of my friends and their phone numbers and their email addresses. So for people like the ones who wound up building the app that led to Cambridge Analytica, this was a goldmine. It was an absolute bonanza and it really benefited Facebook until it didn't.

• 17:00Speaker 06

  And do you think we've gotten, just back to that initial question about how, you know, we share information online? Have we gotten any better at this? Or, I mean, Casey, I love your analogy. If we get a discount on something, we're just like, yeah, take whatever, whatever you want. Here's, here's my mother's maiden name. But are we just that lazy? Like we're just, our brains are just wired for heuristics? Like we just want the shortcuts everywhere?

• 17:27Speaker 00

  I think there have been some major changes and you can see it when you log on to social media, right? You used to log on to Facebook and Instagram and you see your friends and family. Now you see a clip from a podcast you've never heard of, right? And that's, you know, has several causes behind it, but one of the big ones is that Americans are sharing less. The whole bargain that they struck with Facebook of, hey, I'll give you all my information in exchange for you keeping up on the divorces of my high school classmates. That bargain doesn't feel like that's as good anymore. And so all the real sharing is happening in these private group chats and all the public stuff is kind of more, you know, creator content and, you know, celebrities and all of that. So in that respect, I really do think things have changed.

• 18:07Speaker 00

  Now, at the same time, can I get you to give up information if I give you something of relatively low value? Yes, I think that is still broadly the case across, you know, many different dimensions.

• 18:18Speaker 01

  Well, and I also think like AI has become the sort of next frontier of this because people are sharing all kinds of stuff with chatbots. People are having therapy sessions. They're confessing their crimes. They're like, people are doing, people are having these conversations that are very intimate in some cases. And I don't think they know or particularly care what's happening to that data on the other end.

• 18:45Speaker 06

  Wow. Yeah, we, I don't, I don't know. I, I just, I've gotten much more anxious about this over the last few years.

• 18:52Speaker 01

  What kinds of crimes are you doing, Ed?

• 18:55Speaker 06

  Oh, my gosh. Well, I, I mean, the stuff I've already told to ChatGPT, it's all, that's all just in the murder category.

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• 21:54Speaker 06

  All right, let's get back into the story. So the app we're talking about, this was collecting all this data. And according to Facebook's rules, you're not allowed to repurpose this data in any way, but Kogan was. He was selling this data to a little political consulting firm in the UK called Cambridge Analytica. In fact, it turns out Cambridge Analytica had actually paid Kogan to create the app in the first place. So what is Cambridge Analytica? Well, founded in 2013, the company's mission was to take mountains of online data from potential voters and turn it into political leverage. The playbook borrowed a page from the US military's idea of psyops and applied it to elections using targeted ads and so forth. They referred to this as quote psychographic messaging.

• 22:39Speaker 06

  This is so Orwellian, like it's, it just sounds like Big Brother hired an ad agency to come up with these terms.

• 22:47Speaker 01

  It does make me wonder whether if all of the things in this scandal had had like different names, it would have, like Cambridge Analytica just sounds spooky. Psychographic messaging just sounds spooky. It's like if they had been called like political hot trends 101, would it have been a scandal? I don't know.

• 23:07Speaker 06

  I'm not sure that one would have grabbed hold, Kevin, but

• 23:12Speaker 06

  no, but you're right. And global science research is part of that, too.

• 23:16Speaker 00

  And I think it's important to say, as we start to get into this, looking back, I think many of the claims that were made by all of the players here were just wildly overstated, right? It is both true that Americans were very, very concerned about this psychographic targeting that was, you know, going on during the election. It's also true that it almost certainly had nothing to do with the outcome of the election.

• 23:39Speaker 06

  Right. We'll get to that. We'll get to, don't get ahead of me.

• 23:43Speaker 00

  I'm sorry.

• 23:44Speaker 06

  Jeez.

• 23:45Speaker 01

  He's always doing this. You just have to cut off his microphone.

• 23:47Speaker 06

  Okay. Good to know. We'll just cut Casey out of this podcast. I think we can do that. We have we have the technology. Or we'll just create an AI Casey that's way more compliant and just easier. Back to Cambridge Analytica. Running the show was CEO Alexander Nix. There was also, of course, Steve Bannon, who you may know as Trump's former chief strategist and general architect of chaos. Bannon was one of the founders of Cambridge Analytica and later its VP. Now, bankrolling the whole operation were hedge fund billionaires, Robert Mercer and his daughter Rebecca, longtime backers of conservative causes. They were also the

• 24:28Speaker 06

  founders and part owners of Breitbart News, where Bannon was executive chairman for several years. So using the data from Cogan's app, Cambridge Analytica put together robust psychological profiles and personality scores for Facebook users. They then matched these profiles with US voter records and voila, they now had a custom data set designed to predict, target, and potentially sway people's votes. Now, despite only about 270,000 people downloading this app and using it, the API loophole at Facebook allowed Cambridge Analytica to mine

• 25:05Speaker 06

  data from 87 million people. Holy shit. Holy shit. Who bears the responsibility here? Like, is it, is it the users for sharing the data? Is it the bad actors collecting and manipulating? Is it the platforms? Like, or all of, or is it just an unholy toxic three-way?

• 25:26Speaker 00

  I think it is a bit of a toxic three-way. You know, like, I imagine that you, Ed, and most of your listeners have had the experience of you install an app on your phone and it asks you, "Do you want to share your contacts with this app?" For developers, that can be a very effective way of finding other customers. If you're trying to grow a social network, that can help to grow a social network. And if you think that some social networks are good, maybe there is some value there. But it's also true, like, if you're one of the people whose information is being shared, like, arguably, it's kind of being shared without your consent by, like, one of your friends, and it's being used in ways that, like, you have no real control over.

• 26:06Speaker 00

  And so, I do think that was bad, and it is why, you know, that practice has been dramatically curtailed in more recent times.

• 26:14Speaker 06

  Amen. All right, well, it's about to get real. Cut to 2016. The American presidential primaries are approaching, and there were a couple of big-name politicians who caught wind of this Cambridge Analytica spicy operation and said, "Give me some of that." One of them, of course, was the Ted Cruz campaign, which, on the advice of the Mercers, or perhaps the insistence, it's not quite clear, the Mercers were one of the campaign's biggest donors, the Cruz campaign paid a cool $5.8 million for Cambridge Analytica's services. This did not work out well. Basically, Cambridge Analytica scammed the campaign. They pitched a soon-to-be-finished software platform called Ripon, named after the Wisconsin

• 26:58Speaker 06

  town where the Republican Party was born, meant to be an all-in-one command center for the campaign. And there was just one issue: that software didn't exist. There was nothing there. All of the money was just going towards trying to build the software and not actually implementing it. The campaign was understandably furious, but firing them outright would upset the Mercers, so instead, they went with the least dramatic option: just kind of a slow fade-out, just kind of gradually sidelining the firm. It's just, it's funny to me how entire institutions revert to full-on middle-school conflict resolution.

• 27:36Speaker 06

  Just slowly ghosting. Cruz's campaign fizzled out, as we all know, and Cambridge Analytica did what any determined contractor does after a breakup. They found a new client. Enter Donald Trump. In the middle of what was widely considered a long shot run for the Republican nomination, at the time, his digital operation was basically nonexistent. So Cambridge Analytica saw an opening and they moved fast, pitching themselves as the high-tech edge the campaign needed. Before long, they were brought on to handle all of the digital responsibilities for the campaign. And from there, they got to work shaping what voters saw online. The strategy was simple in concept and unnerving in practice.

• 28:16Speaker 06

  They'd figure out what worried you, what scared you, and then feed you content that leaned into those concerns while positioning Trump as the solution. So basically, anxiety and uncertainty custom tailored just for you. Just a spigot of fear. I don't know, it feels like a horror movie. It's how cynical is this?

• 28:40Speaker 00

  I mean, it's so cynical, but also like this just is how we have built our social networks. They're optimized for engagement. So whatever gets you to open the app more, to spend more time there, to do more things in the app, that's what you'll see. And it turns out that if you scare and upset people, they look at the app more. So like that kind of brutal calculus is one of the reasons why we're in this mess we're in today.

• 29:07Speaker 06

  This is the first place that I've seen or heard about fear and terror being like a deliberate effort on the part of a campaign, of a social media campaign. And yet, we have heard a lot about how algorithms have sort of naturally steered things in that direction. So which is it? Or what's the bigger force at work here, do you think? Is it the built-in programming? Or is it like bad actors?

• 29:36Speaker 00

  So I mean, like, negative political ads have existed for a really long time. You can go back to like, the Daisy ad, and you know, do you really want this guy's finger on the button and, you know, vote for him and we're all gonna die in a nuclear holocaust. So, that kind of stuff has a proud tradition in American politics. I think where Cambridge Analytica felt really different was that was this suggestion that they could essentially micro-target and add to your particular fears and neuroses, and they would manipulate you into voting for somebody without you even understanding what was happening to you, right?

• 30:13Speaker 06

  Right, right.

• 30:13Speaker 00

  So, and, you know, they could do this at like, a massive scale, but, you know, because the vast majority of Americans were on Facebook, they could just sort of reach all of those people instantaneously in a way that they would not have even been able to do with a TV ad.

• 30:25Speaker 01

  Well, I think there's some additional nuance to add here, which is that it's not clear that what Cambridge Analytica was offering to do actually worked, right?

• 30:34Speaker 06

  For sure.

• 30:34Speaker 01

  If it worked really well, President Ted Cruz would have been elected.

• 30:38Speaker 06

  You're absolutely right.

• 30:40Speaker 01

  So this may have just been a sales pitch that they were giving. I think it is also true simultaneously that the Trump campaign appears to have done a very good job of using Facebook as a way of getting voters to engage with whatever they were sharing, to inspire people to go to the polls. They ran a very sophisticated, essentially, marketing operation on Facebook. But it's not clear to me that they did that, like, using the tools and techniques that Cambridge Analytica gave them, rather than just the advertising and marketing tools that are available through Facebook's own ad platform.

• 31:16Speaker 06

  Sure. And also, the incredible instincts of Donald Trump, right? Like, his just unbelievable ability to tap into cultural tides of anxiety. And his humor, like, the way that his, I think his undeniable charm was just feeling so, so fresh and kind of unbelievable to people at this time.

• 31:42Speaker 01

  I think he's like a human newsfeed algorithm. He just, you can sort of see him as he's giving a speech. He's just like, sort of testing out stuff, and if it gets a laugh, or people get excited about it, he like, does it again. And if people don't seem to respond, he doesn't do it again. He's sort of like, running the A/B test in real time on his audience.

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• 34:52Speaker 06

  As we all know, Trump won in 2016, leaving a lot of people wondering, how the heck did he pull off one of the most surprising upsets in US political history? Now, obviously, the answer to that is a very complex constellation of cultural and political factors, but that analysis got a lot more complicated in March of 2018, when Cambridge Analytica ex-employee Christopher Wiley went full whistleblower and shared a cache of documents that immediately exploded across world headlines in The Guardian, The Observer, The New York Times, and many more. This was absolutely nuclear. Here's a few choice quotes from Wiley, and it is important, Kevin, you made a great

• 35:37Speaker 06

  point, and Casey, you've hinted at it too already, which is, which is that the effectiveness of Cambridge Analytica is debated and debatable, but what we're speaking to in this moment, I think, is more just their intent, like what they were selling on the assumption that they weren't selling a scam, but that they were selling the intention and the hope that they could execute on these things. So here are some things that Christopher Wiley, former employee of Cambridge Analytica, was saying, quote, "We exploited Facebook to harvest millions of people's profiles and built models to exploit what we knew about them and target their inner demons. That was the basis the entire company was built on." Wiley also said of Cambridge Analytica leadership, quote, "Rules don't matter for them.

• 36:22Speaker 06

  For them, this is a war, and it's all fair." And here's one more, because this guy really has a way with words. Wiley told The Guardian that Cambridge Analytica's operation was, quote, "Steve Bannon's psychological warfare mindfuck tool."

• 36:40Speaker 06

  Which is, I mean, it's pretty great.

• 36:42Speaker 01

  The guy gives good quote, as they say in our business.

• 36:45Speaker 06

  Gives good quote.

• 36:45Speaker 01

  Yeah.

• 36:46Speaker 06

  This is March of 2018. Take me back to this moment for you guys. What was it? What was it like? This, this story falls in your laps. You both wind up becoming like very important reporters in this whole affair. And also, given the context that you mentioned earlier, Casey, that, that a lot of this wasn't necessarily a surprise. What made this moment so tectonic?

• 37:10Speaker 00

  Yeah. So my first thought was like, oh, like people, people want to talk about Cambridge Analytica because I had covered it a little bit at around the time that Facebook had first closed its API to doing exactly this sort of thing. You know, the, the company decided to shut down its platform in part over privacy concerns, right? Because like years before Cambridge Analytica happened, Facebook was getting flack for how easily it was making it for developers to collect massive amounts of data on people. And Facebook's like competitive priorities changed. And so they sort of shut it down. So when people started talking about Cambridge Analytica again, I was like, oh, like I'm, I'm sort of surprised this is becoming a thing. But I think it's really important to remember

• 37:52Speaker 00

  that in March of 2018, Americans, some significant portion of them, were still asking themselves, how did Donald Trump get elected? Like you cannot overstate the degree to which, to some healthy chunk of the country, it all felt like a fluke. And people were searching for an explanation that would make it make sense that the United States had elected Donald Trump. And so there was a real appetite for some narrative that could come along and explain how this guy was able to get into the Oval Office.

• 38:23Speaker 06

  Very, very good point. What did it feel like to you, Kevin?

• 38:27Speaker 01

  So I was trying to remember my own, like I, I was not one of the sort of main reporters at the New York Times who was doing this story. But I did end up interviewing Mark Zuckerberg about this. And I remember about that interview that we got a call, my colleague Sheer Franklin, I got a call that was basically like, Mark Zuckerberg is available to speak to you about this in 20 minutes.

• 38:53Speaker 06

  And this is right after, this is like just a couple of days after this story broke, right?

• 38:58Speaker 01

  This was one of the first times he had sort of addressed this. And I was like in the middle of something. Shira was in the middle of something. Neither of us had expected or prepared for this. And we had 20 minutes to prepare for this very important interview. And I just remember feeling very stressed about that. And what was so interesting to me was that he was obviously very defensive. He understood, as Zuckerberg did, that this was going to be a big political liability for him because people were very mad about Facebook and its role in the 2016 election. And they, you know, even the day after the election, people were raising questions about whether Donald Trump's victory had been sort of Facebook's fault or whether Facebook had

• 39:43Speaker 01

  been primarily responsible for it. So he was clearly on the defensive. He made a bunch of points about how they were restricting access to this data. They were going to do a full forensic audit of Cambridge Analytica to figure out what had happened. And he sort of said that they regretted not having gone after Cambridge Analytica harder and this app, this quiz app that had collected all this data. And he said, you know, we wish we had done more to make sure that they had actually deleted the data when they told they did.

• 40:16Speaker 06

  His team alerted the New York Times that he could talk in five minutes. Is that how that went down?

• 40:20Speaker 01

  I think it was 20 minutes, but it felt like five.

• 40:23Speaker 06

  Yeah. And that's just, that's just a power move to put you on your heels, right? And like.

• 40:27Speaker 00

  Yeah. And Kevin, if I remember correctly, had to cut his lunch short and he was like super mad. He's like, you want to get dessert? And then he couldn't get dessert. And it was a whole thing.

• 40:36Speaker 01

  Yeah, I was like, he can call me in 45 minutes.

• 40:39Speaker 06

  Yeah.

• 40:39Speaker 01

  I didn't say that.

• 40:40Speaker 06

  All right. I think that's a good place to hit pause and let's pick it up in the next episode. Thanks so much, guys. Snafu is a production of iHeart Podcasts and Snafu Media, a partnership between Film Nation Entertainment and Pacific Electric Picture Company. Post-production and creative support from Good Egg Audio. Our executive producers are me, Ed Helms, Mike Falbo, Glenn Basner, Andy Kim, and Dylan Fagan. This episode was produced by Alyssa Martino and Tori Smith. Our managing producer is Carl Nellis. Our video editor is Jared Smith. Technical direction and engineering from Nick Dooley. Additional story editing from Carl Nellis. Our creative executive is Brett Harris.

• 41:23Speaker 06

  Logo and branding by Matt Gosson and The Collected Works. Legal review from Dan Welsh, Megan Halson, and Caroline Johnson. Special thanks to Isaac Dunham, Adam Horn, Lane Klein, and everyone at iHeart Podcasts, but especially Will Pearson, Carrie Lieberman, and Nikki Ator. While I have you, don't forget to pick up a copy of my book, Snafu: The Definitive Guide to History's Greatest Screw-Ups. It's available now from any book retailer. Just go to snafu-book.com. Thanks for listening and see you next week.

• 42:07Speaker 12

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