Targeted: My Inside Story of Cambridge Analytica and How Trump, Brexit and Facebook Broke Democracy. Brittany KaiserЧитать онлайн книгу.
work with contractors for an Israeli defense and intelligence firm, I heard the contractors boast about their firm doing everything from giving advance warning of attacks on their clients’ campaigns to digging up material that would be useful for counter-operations and opposition messaging. At first it seemed pretty benign to me, even clever and useful. The contractors’ firm was pitching clients similar to the SCL Group’s, even with some overlap, and the firm had worked in nearly as many elections as Alexander had. While SCL did not have internal counter-ops capacity, its work still had the feel of guerrilla warfare. The more I learned about each firm’s strategy, both appeared to be willing to do whatever was needed to win, and that gray area started to bother me. I had suggested SCL work with this firm, as I assumed that two companies working together could produce greater impact for clients, but I was quickly taken out of copy, per usual in Alexander’s practice, and not kept abreast of what was actually happening to achieve said results.
While trying to show value and close my first deal, I had introduced this Israeli firm to the Nigerians. I’m not sure what I expected to come of that, besides my looking more experienced than I was, but the results were not what I had imagined they would be. The Nigerian clients ended up hiring the Israeli operatives to work separately from SCL, and as I was later told, they sought to infiltrate the Muhammadu Buhari campaign and obtain insider information. They were successful in this and then passed information to SCL for use. The messaging that resulted discredited Buhari and incited fear, something I wasn’t privy to at the time, while Sam Patten was running the show on the ground. Ultimately, the contractors and SCL itself were not effective enough to turn the tide of the election in Goodluck Jonathan’s favor. To be fair, the campaign hadn’t even lasted a month, but, regardless, he lost spectacularly to Buhari—by 2.5 million votes. The election would become notorious because it was the first time a Nigerian incumbent president had been unseated and also because it was the most expensive campaign in the history of the African continent.
But what was of most concern to me at the time, when it came to ethics, was where the Nigerian money ended up. As I was to learn from Ceris, of the $1.8 million the Nigerian oil billionaire had paid SCL, the team had, in the short time it worked for the man, spent only $800,000, which meant the profit margin for SCL had been outrageous.
The rest of the money I had brought into the company, a cool $1 million, ended up being sheer profit for Alexander Nix. Given that normal markup for projects was 15–20 percent, this was a spectacularly high figure, in my opinion well outside of normal industry standards. It made me wary about pricing for clients in parts of the world where candidates were desperate to win at any cost. While taking high profits is of course legal, it was deeply unethical when Alexander had told the clients we ran out of money and would need more to keep the team on the ground until the delayed election date. I was sure we had more resources, but still, I was afraid to reveal to Alexander that I knew the markup, and the fact that I didn’t confront him on this haunted me.
Frankly, even some of SCL’s European contracts seemed less than aboveboard when I finally paid attention to the details. On a contract SCL had for the mayoral elections in Vilnius, Lithuania, someone in our company forged Alexander’s signature in order to expedite the closing of the deal. I later found out that the deal itself may even have been granted to us in contravention of a national law requiring that election work be publicly tendered and that we had already received notification that we’d “won” the tender before the end of the window of time during which public firms ought to have been able apply for the contract.
When Alexander discovered that his signature had been forged and that the contract wasn’t entirely kosher, he asked me to fire the person responsible, even though she was the wife of one of his friends from Eton. I did what he asked. Later, it would become clear that though he seemed to be punishing the employee for her behavior, what he was angriest about wasn’t the backroom dealing but the fact that she hadn’t collected SCL’s final payment from the political party in question. He made me chase the money and told me to forget about Sam in Nigeria: concentrate on our next paycheck.
All this had started to overwhelm me, and I was nervous that I was in over my head at SCL’s global helm. I began to look elsewhere in the firm for social projects for which I could use my expertise. I had so much to give and so much to learn about data, and I wasn’t going to let some rogue clients get the better of my strong will and put me off from finishing my PhD research.
On the positive side, I was learning that the most exciting innovations were happening in the United States, and that there were dozens of opportunities in America, most of which, thankfully, had nothing to do with the GOP. In Europe, Africa, and many nations around the globe, SCL was limited in its ability to use data because most countries’ data infrastructures were underdeveloped. At SCL, I’d been unable to work on contracts that both made use of our most innovative and exciting tools and that, I believed, involved our best practices.
Alexander had recently boasted of nearly closing a deal with the biggest charity in the United States, so I hopped onto that to help him close it. The work involved helping the nonprofit identify new donors, something that appealed to me greatly, as I had spent so many years in charity fund-raising that I couldn’t wait to learn a data-driven approach to helping new causes. On the political side, SCL was pitching ballot initiatives in favor of building water reservoirs and high-speed trains, public works projects that could really make a difference in peoples’ lives. The company was even moving into commercial advertising, selling everything from newspapers to cutting-edge health care products, an area I could dip into if my heart desired, Alexander told me.
I wanted to learn how analytics worked, and I wanted to do it where we could see, and measure, our achievements, and where people worked with transparency and honesty. I remembered my work with men like Barack Obama. He had been honorable and impeccably moral, and so had the people around him. The way they campaigned was ethical, involving no big-dollar donors and Barack had insisted on absolutely no negative campaigning, too. He would neither attack his Democratic rivals in the primaries nor go low on Republicans. I was nostalgic for a time when I’d experienced elections that ran according to not only rules and laws, but ethics and moral principles.
It seemed to me that my future at the company, if I were to have one, would be in the United States.
I told Alexander I wanted to learn the Cambridge Analytica pitch. And in choosing to do so, I was choosing to join that company, with all the bells and whistles attached.
I couldn’t wow Alexander with my own pitch without first meeting with Dr. Alex Tayler to learn about the data analytics behind Cambridge Analytica’s success. Tayler’s pitch was much more technical and much more involved in the nitty-gritty of the analytics process, but he showed me how Cambridge Analytica’s so-called secret sauce wasn’t one particular secret thing but really many things that set CA apart from our peers. As Alexander Nix often said, the secret sauce was more like a recipe of several ingredients. The ingredients were really baked into a kind of “cake,” he said.
Perhaps the most important first thing that made CA different from any other communications firm was the size of our database. The database, Tayler explained, was prodigious and unprecedented in depth and breadth, and was growing ever bigger by the day. We had come about it by buying and licensing all the personal information held on every American citizen. We bought that data from every vendor we could afford to pay—from Experian to Axiom to Infogroup. We bought data about Americans’ finances, where they bought things, how much they paid for them, where they went on vacation, what they read.
We matched this data to their political information (their voting habits, which were accessible publicly) and then matched all that again to their Facebook data (what topics they had “liked”). From Facebook alone, we had some 570 individual data points on users, and so, combining all this gave us some 5,000 data points on every single American over the age of eighteen—some 240 million people.
The special edge of the database, though, Tayler said, was our access to Facebook for messaging. We used the Facebook platform to reach the same people on whom we had compiled so much data.
What Alex told me helped bring into focus two events I’d experienced while at the SCL Group, the first when I’d just arrived.