Targeted. Brittany Kaiser
and scope, the largest, as far as he knew, anyone had ever assembled. The company’s monster databases held between two thousand and five thousand individual data points (pieces of personal information) on every individual in the United States over the age of eighteen. That amounted to some 240 million people.
Nix paused and looked at Chester’s friends and at me, as if to let the number sink in.
But merely having Big Data wasn’t the solution, he said. Knowing what to do with it was the key. That involved more scientific and precise ways of putting people into categories: “Democrat,” “environmentalist,” “optimist,” “activist,” and the like. And for years, the SCL Group, Cambridge Analytica’s parent company, had been identifying and sorting people using the most sophisticated method in behavioral psychology, which gave it the capability of turning what was otherwise just a mountain of information about the American populace into a gold mine.
Nix told us about his in-house army of data scientists and psychologists who had learned precisely how to know whom they wanted to message, what messaging to send them, and exactly where to reach them. He had hired the most brilliant data scientists in the world, people who could laser in on individuals wherever they were to be found (on their cell phones, computers, tablets, on television) and through any kind of medium you could imagine (from audio to social media), using “microtargeting.” Cambridge Analytica could isolate individuals and literally cause them to think, vote, and act differently from how they had before. It spent its clients’ money on communications that really worked, with measurable results, Nix said.
That, he said, is how Cambridge Analytica was going to win elections in America.
While Nix spoke, I glanced over at Chester, hoping to make eye contact in order to figure out what opinion he might have formed of Nix, but I wasn’t able to catch his attention. As for Chester’s friends, I could see from the looks on their faces that they were duly wowed as Nix went on about his American company.
Cambridge Analytica was filling an important niche in the market. It had been formed to meet pent-up, unmet demand. The Obama Democrats had dominated the digital communications space since 2007. The Republicans lagged sorely behind in technology innovation. After their crushing defeat in 2012, Cambridge Analytica had come along to level the playing field in a representative democracy by giving the Republicans the technology they lacked.
As for what Nix could do for Chester’s friends, whose country didn’t have Big Data, due to lack of internet penetration, SCL could get that started for them, and it could use social media to get their message out. Meanwhile, it could also do more traditional campaigning, everything from writing policy platforms and political manifestos to canvassing door-to-door to analyzing target audiences.
The men complimented Nix. I was well enough acquainted with the two by now, though, to see how his pitch had overwhelmed them. I knew their country hadn’t the infrastructure to carry out what Nix was planning to do in America, and his strategy didn’t sound particularly affordable, even to two men with reasonably deep pockets.
For my part, I was shocked at what Nix had shared—stunned, in fact. I’d never heard anything like it before. He’d described nothing less than using people’s personal information to influence them and, hence, to change economies and political systems around the world. He’d made it sound easy to sway voters to make irreversible decisions not against their will but, at the very least, against their usual judgment, and to change their habitual behavior.
At the same time, I admitted, if only to myself, that I was gobsmacked by his company’s capabilities. Since my first days in political campaigning, I had developed a special interest in the subject of Big Data analytics. I wasn’t a developer or a data scientist, but like other Millennials, I had been an early adopter of all sorts of technology and had lived a digital life from my earliest years. I was predisposed to see data as an integral part of my world, a given, at its worst benign and utilitarian, and at its best possibly transformative.
I myself had used data, even rudimentarily in elections. Aside from being an unpaid intern on Obama’s New Media team, I had volunteered for Howard Dean’s primary race four years earlier, and then both John Kerry’s presidential campaign, as well for both the DNC itself and Obama’s senatorial run. Even basic use of data to write emails to undecided voters on what they cared about was “revolutionary” at the time. Howard Dean’s campaign broke all existing fund-raising records by reaching people online for the first time.
My interest in data was coupled with my firsthand knowledge of revolutions. A lifelong bookworm, I’d been a student forever but had always engaged in the wider world. In fact, I had always felt that it was imperative for academics to find ways to spin the threads of the high-minded ideas they came up with in the ivory tower into cloth that was of real use to others.
Even though it involved a peaceful transfer of power, you could say that the Obama election was my first experience of a revolution. I had been a part of the spirited celebration in Chicago on the night Obama won his first presidential election, and that street party of millions felt like a political coup.
I’d also had the privilege, and had sometimes experienced the danger, of being on the ground in countries where revolutions were happening silently, had just broken out, or were about to. As an undergraduate, I studied for a year in Hong Kong, where I volunteered with activists shuttling refugees from North Korea via an underground railroad through China and out to safety. Immediately upon graduating from college, I spent time in parts of South Africa, where I worked on projects with former guerrilla strategists who’d helped overthrow apartheid. And in the aftermath of the Arab spring, I worked in post-Gaddafi Libya, and have continued to be interested and involved in independent diplomacy for that country for many years. I guess you could say I had the uncanny habit of putting myself in the middle of places during their most turbulent times.
I had also studied how data could be used for good, looking at how people empowered by it had used it to seek social justice, in some cases to expose corruption and bad actors. In 2011, I had written my master’s thesis using leaked government data from Wikileaks as my primary source material. The data showed what had happened during the Iraq War, exposing numerous cases of crimes against humanity.
From 2010 onward the “hacktivist” (i.e., activist hacker) Julian Assange, founder of the organization, had declared virtual war on those that had waged literal war on humanity by widely disseminating top secret and classified files that proved damning to the American government and the U.S. military. The data dump, called “The Iraq War Files,” prompted public discourse on protection of civil liberties and international human rights from abuses of power.
Now, as part of my PhD dissertation in diplomacy and human rights, and a continuation of my earlier work, I was going to combine my interest in Big Data with my experience of political turbulence, looking at how data could save lives. I was particularly interested in something called “preventive diplomacy.” The United Nations and nongovernmental organizations (NGOs) across the globe were looking for ways to use real-time data to prevent atrocities such as the genocide that occurred in Rwanda in 1994, where earlier action could have been taken if the data had been available to decision makers. “Preventive” data monitoring—of everything from the price of bread to the increased use of racial slurs on Twitter—could give peacekeeping organizations the information they needed to identify, monitor, and peacefully intervene in high-risk societies before conflicts escalated. The proper gathering and analysis of data could prevent human rights violations, war crimes, and even war itself.
Needless to say, I understood the implications of the capabilities Nix was alleging the SCL Group possessed. His talk of data, combined with his words about revolutions, left me unsettled about his intentions and the risks his methods might pose. This made me reluctant to share what I knew about data or what my experience with it was, and I was grateful that day in London to see that he was already wrapping up with Chester’s friends and preparing to leave.
Fortunately, Nix had paid me little attention. When he wasn’t talking about his company, we had chatted in general about my work on campaigns, but I was relieved he hadn’t picked my brain about anything specific to do with Obama’s New Media campaign, any of my