“Wait,” he said, his eyes widening behind his black-rimmed glasses. “How many of these do we have?”
“What the fuck?” Bannon interjected with a look of annoyance at Nix’s disengagement with the project.
“We’re in the tens of millions now,” said Jucikas. “At this pace, we could get to 200 million by the end of the year with enough funding.”
“And we know literally everything about these people?” asked Nix.
“Yes,” I told him. “That’s the whole point.”
The light went on: This was the first time Nix truly understood what we were doing. He could not have been less interested in things like “data” and “algorithms,” but seeing actual people onscreen, knowing everything about them, had seized his imagination.
“Do we have their phone numbers?” Nix asked. I told him we did. And then, in one of those moments of weird brilliance he occasionally had, he reached for the speakerphone and asked for the number. As Jucikas relayed it to him, he punched in the number.
After a couple of rings, someone picked up. We heard a woman say “Hello?” and Nix, in his most posh accent, said, “Hello, ma’am. I’m terribly sorry to bother you, but I’m calling from the University of Cambridge. We are conducting a survey. Might I speak with Ms. Jenny Smith, please?” The woman confirmed that she was Jenny, and Nix started asking her questions based on what we knew from her data.
“Ms. Smith, I’d like to know, what is your opinion of the television show Game of Thrones?” Jenny raved about it—just as she had on Facebook. “Did you vote for Mitt Romney in the last election?” Jenny confirmed that she had. Nix asked whether her kids went to such-and-such elementary school, and Jenny confirmed that, too. When I looked over at Bannon, he had a huge grin on his face.
After Nix hung up with Jenny, Bannon said, “Let me do one!” We went around the room, all of us taking a turn. It was surreal to think that these people were sitting in their kitchen in Iowa or Oklahoma or Indiana, talking to a bunch of guys in London who were looking at satellite pictures of where they lived, family photos, all of their personal information. Looking back, it’s crazy to think that Bannon—who then was a total unknown, still more than a year away from gaining infamy as an adviser to Donald Trump—sat in our office calling random Americans to ask them personal questions. And people were more than happy to answer him.
We had done it. We had reconstructed tens of millions of Americans in silico, with potentially hundreds of millions more to come. This was an epic moment. I was proud that we had created something so powerful. I felt sure it was something that people would be talking about for decades.
CHAPTER 7
THE DARK TRIAD
-
By August 2014, just two months after we launched the app, Cambridge Analytica had collected the complete Facebook accounts of more than 87 million users, mostly from America. They soon exhausted the list of MTurk users and had to engage another company, Qualtrics, a survey platform based in Utah. Almost immediately, CA became one of their top clients and started receiving bags of Qualtrics-branded goodies. Jucikas would sashay around wearing an I QUALTRICS T-shirt under his otherwise perfectly tailored Savile Row suit, which everyone found both amusing and ridiculous. CA would get invoices sent from Provo, billing them each time for twenty thousand new users in their “Facebook Data Harvest Project.”
As soon as CA started collecting this Facebook data, executives from Palantir started making inquiries. Their interest was apparently piqued when they found out how much data the team was gathering—and that Facebook was just letting CA do it. The executives CA met with wanted to know how the project worked, and soon they approached our team about getting access to the data themselves.
Palantir was still doing work for the NSA and GCHQ. Staffers there told CA that working with Cambridge Analytica could potentially open an interesting legal loophole. At a meeting in the summer of 2014 at Palantir’s U.K. head office, in Soho Square, it was pointed out that government security agencies, along with contractors like Palantir, couldn’t legally mass-harvest personal data on American citizens, but—here’s the catch—polling companies, social networks, and private companies could. And despite the ban on directly surveilling Americans, I was told that U.S. intelligence agencies were nonetheless able to make use of information on American citizens that was “freely volunteered” by U.S. individuals or companies. After hearing this, Nix leaned in and said, “So you mean American polling companies…like us.” He grinned. I didn’t think anyone was actually being serious, but I soon realized that I underestimated everyone’s interest in accessing this data.
Some of the staff working at Palantir realized that Facebook had the potential to become the best discreet surveillance tool imaginable for the NSA—that is, if that data was “freely volunteered” by another entity. To be clear, these conversations were speculative, and it is unclear if Palantir itself was actually aware of the particulars of these discussions, or if the company received any CA data. The staff suggested to Nix that if Cambridge Analytica gave them access to the harvested data, they could then, at least in theory, legally pass it along to the NSA. In this vein, Nix told me we urgently needed to make an arrangement with staff at Palantir happen, “for the defense of our democracy.” But that, of course, was not why Nix gave them full access to the private data of hundreds of millions of American citizens. Nix’s dream, as he had confided in our very first meeting, was to become the “Palantir of propaganda.”
One lead data scientist from Palantir began making regular trips to the Cambridge Analytica office to work with the data science team on building profiling models. He was occasionally accompanied by colleagues, but the entire arrangement was kept secret from the rest of the CA teams—and perhaps Palantir itself. I can’t speculate about why, but the Palantir staff received Cambridge Analytica database logins and emails with fairly obvious pseudonyms like “Dr. Freddie Mac” (after the mortgage company that was bailed out by the federal government in the 2008 housing crisis). I do know that after Palantir data scientists started building their own Facebook harvesting apps and scrapers, Nix asked them to stay after hours to keep working on applications that could replicate the Facebook data Kogan was getting—without the need for Kogan. It was no longer simply Facebook apps that were being used. Cambridge Analytica began testing innocuous-looking browser extensions, such as calculators and calendars, that pulled access to the user’s Facebook session cookies, which in turn allowed the company to log in to Facebook as the target user to harvest their data and that of their friends. These extensions were all submitted—and approved—in the independent review processes of several popular Web browsers.
It wasn’t clear whether these Palantir executives were visiting CA officially or “unofficially,” and Palantir has since asserted that it was only a single staff member who worked at CA in a “personal capacity.” I honestly didn’t know who or what to believe at this point. As he often did with contractors on projects in Africa, Nix would bring to the office bags filled with U.S. currency and pay contractors in cash. As contractors would work, Nix would sit at his desk flicking through the green bills, counting them into small piles, each worth thousands of dollars. Sometimes contractors were given tens of thousands of dollars each week.
Many years before, Nix had been rejected by Britain’s foreign intelligence service, MI6. He often joked about it, saying it had happened because he wasn’t boring enough to blend into a crowd, but the rejection had obviously stung him. Now he almost didn’t care who got access to CA’s data; he would have shown it to anyone, just to hear how amazing he was.
* * *
—
BY LATE SPRING 2014, Mercer’s investment had spurred a hiring spree of psychologists, data scientists, and researchers. Nix brought on a new team of managers to organize the fast-growing research operations. Although I remained the titular director of research, the new operatio
ns managers were now given control over direct oversight and planning of this rapidly growing exercise. New projects seemed to pop up each day, and sometimes it was unclear how or why projects were being approved to go to field. I complained to Nix that I was losing track of who was doing what, but he didn’t see the problem. Nix simply couldn’t see beyond prestige and money. He told me that most people would be grateful to be given less responsibility and work to do but still allowed to keep their title.
At this point, I did start to feel weird about everything, but whenever I spoke with other people at the firm, we all managed to calm one another down and rationalize everything. Nix would talk about shady things, but that’s just who he was and no one took him seriously. And after Mercer installed Bannon, I overlooked or explained away things that, in hindsight, were obvious red flags. Bannon had his “niche” political interests, but Mercer seemed to be too serious a character to dabble in Bannon’s trashy political sideshows. The potential for our work to benefit Mercer’s financial interests made so much more sense as an explanation for why he would spend all this money on something so highly speculative. Mercer literally gave CA tens of millions of dollars before the firm had acquired any data or built any software in America. From any investor’s perspective, this would have been a high-risk seed capital investment. But CA also knew Mercer was not dumb or reckless, and he would have calculated the risk carefully. At the time, many on the team simply assumed that to justify taking such a high financial risk on our ideas, Mercer must have expected that the research had the chance of making tons of money at his hedge fund. In other words, the firm was not there to build an alt-right insurgency, it was there to help Mercer make money, and Nix’s conspicuous love of money reinforced everyone’s assumptions.
Of course, we know now that none of that happened. I don’t know what else to say other than I was more naïve than I thought I was at the time. Even though I had a great deal of experience for my age, I was only twenty-four and clearly still had a lot of learning to do. When I joined SCL, I was there to help the firm explore areas like counter-radicalization in order to help Britain, America, and their allies defend themselves against new threats emerging online. I began to get accustomed to the unusual environment of this line of work, which normalized a lot of things that would seem weird to a casual observer. Information operations is not your average nine-to-five desk job, and the people or situations you encounter are all a bit odd. And anytime someone would ask about the ethics of a surreptitious project in a far-off country, they would be mocked for their naïveté about how the rest of the world “really worked.”
It was the first time I was allowed to explore ideas without the constraints of petty internal politics or people snubbing an idea just because it had never been tried before. As much as Nix was a dick, he did give me a lot of leeway to try out new ideas. After Kogan joined, I had professors at the University of Cambridge constantly fawning over the groundbreaking potential that the project could have for advancing psychology and sociology, which made me feel like I was on a mission. And if their colleagues at universities like Harvard or Stanford were also getting interested in our work, I thought that surely we must be onto something. The institute that Kogan proposed really was an inspiring idea to me, and I saw how unlocking this data for researchers around the world could contribute so much value to so many fields. As corny as this might sound, it really felt like I was working on something important—not just for Mercer or the company, but for science. However, I let this feeling distract me to the point of allowing myself to excuse the inexcusable. I told myself that truly learning about society includes delving into uncomfortable questions about our darker sides. How could we understand racial bias, authoritarianism, or misogyny if we did not explore them? What I did not appreciate is the fine line between exploring something and actually creating it.
Bannon had assumed control of the company, and he was an ambitious and surprisingly sophisticated cultural warrior. He felt that the identity politics of Democrats, with their focus on racial or ethnic blocs of voters, was actually less powerful than that of Republicans, who often insisted that American identity went beyond skin color, religious preference, or gender. A white man living in a trailer park doesn’t see himself as a member of a privileged class, though others may see him that way just because he’s white. Every mind contains multitudes. And Bannon’s new job was to figure out how to target people accordingly.
I told Bannon that the most striking thing CA had noticed was how many Americans felt closeted—and not just gay people. This first came up in focus groups and later was confirmed in quantitative research done via online panels. Straight white men, particularly ones who were older, had grown up with a value set that granted them certain social privileges. Straight white men did not have to moderate their speech around women or people of color, because casual racism and misogyny were normalized behaviors. As social norms in America evolved, these privileges began to erode and many of these men were experiencing challenges to their behavior for the first time. At the workplace, “casual flirting” with female secretaries now imperiled your job, and talking about the “thugs” in the African American part of town could get you shunned by peers. These encounters were often uncomfortable and threatening to their identity as “regular men.”
Men who were not used to moderating their impulses, body language, and speech began to resent what they saw as the unfair mental and emotional labor it took to change and constantly correct how they presented in public. What I found interesting was how similar the discourse that emerged from these groups of angry straight men was to liberation discourse from gay communities. These men began to experience the burden of the closet, and they did not like the feeling of having to change who they felt they were in order to “pass” in society. Although there were very different reasons for the closeting of gays and the closeting of racists and misogynists, these straight white men nonetheless felt a subjective experience of oppression in their own minds. And they were ready to emerge from the closet and return to a time when America was great—for them.
“Think about it,” I said to Bannon. “The message at a Tea Party rally is the same as at a Gay Pride parade: Don’t tread on me! Let me be who I am!” Embittered conservatives felt like they couldn’t be “real men” anymore, because women wouldn’t date men who behaved the way men had behaved for millennia. They had to hide their true selves to please society—and they were pissed about it. In their minds, feminism had locked “real men” in the closet. It was humiliating, and Bannon knew that there was no force more powerful than a humiliated man. It was a state of mind he was eager to explore (and exploit).
The incel community, just coming to the fore when Cambridge Analytica was being established, was the kind of group he had in mind. Incels, or “involuntary celibates,” were men who felt ignored and chastised by a society—particularly women—that did not value average men anymore. An offshoot of the Men’s Rights Movement, the incel community was in part propelled by the increasing economic inequality depriving young millennial men from accessing the same kinds of well-paying jobs their fathers had. This economic deprivation was coupled with increasingly unattainable body image standards for men in conventional and social media (without the same public recognition of male body issues or gendered pressures as for women) and the growing importance placed on physical looks in a dating scene increasingly defined by swiping left or right on a split-second glance at a photo. And as women had become more economically independent, they could afford to be more selective about their partners. Deprived of good looks and a respectable paycheck, “average men” faced a hard reality of constant romantic rejection.
Some of these men began congregating on forums like 4chan, which grew into a repository of memes, weird fantasy fandoms, niche porn, pop culture, and the countercultural reactions of frustrated youth in an increasingly atomized society. In the early 2010s, nihilistic discussions began among youn
g men who were resigned to lives of loneliness. A new vocabulary emerged to describe their circumstances, including “betas” (inferior men), “alphas” (superior men), “vocels” (voluntary celibates), MGTOW (Men Going Their Own Way, walking away from women), “incels” (involuntary celibates), and “robots” (incels with Asperger’s).
Irrespective of the privileges afforded to them as straight white men, these groups lacked identity, direction, and a sense of self-worth and grabbed on to anything that instilled a feeling of belonging and solidarity. Self-defining as the “beta” males of society, many incels would talk about accepting the “black pill”—a moment of reckoning with what they believed were certain innate truths about sexual and romantic attraction. Forums would include topics such as “suicide fuel,” which were examples from their daily lives of rejection that reinforced their feelings of hopelessness and ugliness. For many incels, this angry desperation had morphed into extreme misogyny.
The doctrine of the black pill was bleak and rigid, stating that only physical looks matter to women, and that certain features, including race, fall into a hierarchy of sexual desirability. Incels would share graphs and observations signaling an innate advantage for white men, as women from all races would accept a white partner, and a strong disadvantage for Asian men. To be fat or poor or old or disabled or a person of color was to be a member of America’s most unwanted. Nonwhite incels would use terms like “JBW”—“just be white”—as a way of trying to explain or mitigate what they saw as their innate racial disadvantages. There was a surprising amount of open recognition of white privilege, but incel discourse would frame this privilege as part of the inherent racial superiority of white men, at least in the context of sexual selection.
Mindfuck Page 14