I must have dozed off, because the conductor’s announcement startled me: “Alight here for Cambridge!” It was October 2013, and I’d woken up that morning at 5:00 to make the 6:40 train out of London’s Victoria Station. Nix had booked me on the early one to save himself five pounds. I jumped out of my seat and accidentally knocked into the elderly lady beside me. She just glared, clutching her purse, as English people do. I was running out, looking back to say sorry, when I tripped. “Mind the gap!” Too late.
I stood up, only to realize that I’d somehow misplaced my wallet, and then watched in dread as the train slowly pulled out of the station. Ugh. Without cash or cards, I called Nix and asked him to book a prepaid taxi. “Walk there,” he said. “You should have been more careful.” I was too tired to argue, and he was clearly in a mood, so I did as Nix said—I walked, departing the station into the mist and drizzle of an early October morning. Cambridge was just starting to wake up.
With several hours to kill before my appointment, I meandered through Parker’s Piece, a small common green, as student-athletes began a morning practice against a backdrop of a church steeple peeking through the trees. From there, I walked through the town’s winding medieval stone streets, past small shops and the towering walls of England’s second-oldest university, dating back to the year 1209. After continuing to Thompson’s Lane, near the River Cam, I arrived at the small but clearly expensive Varsity Hotel.
Working with a military contractor, I met all sorts of bizarre characters, most of whom had a strong desire for “absolute discretion”—it wasn’t the least bit unusual to not know the full identity of a person before the first meeting. The day before, Nix had come into the office looking slightly agitated and walked immediately over to me, where he put both his hands on my desk and leaned into my face. “I need you to meet someone tomorrow in Cambridge,” he said. “I can’t get into his head, but I think you can.”
I asked who I’d be meeting.
“I’ll email you the details later.”
In this case, the extremely unhelpful instruction I got from Nix was simply to meet “Steve from America,” with no details beyond a request that I “bring data.”
I sat alone in the hotel lobby for an hour before texting Nix, asking for Steve’s number. He read the text but didn’t respond. After another fifteen minutes, this gruff character walked up and looked me over.
“You the guy?” he asked.
“Yeah, I am,” I replied. Based on the clients SCL normally had, I’d expected some government or agency type. Instead I found myself looking at a disheveled man wearing two collared shirts, as if he’d forgotten to take one off before putting the next one on. He was unshaven, with greasy hair and that layer of grime you get from a transatlantic flight. His eyes showed flecks of bright red that matched the web of rosacea on his skin. In all, the vibe he gave off fell somewhere between used-car salesman and madman. He looked tired or dazed; I assumed it was just jet lag.
The elevator was a classic English setup that barely had room for two, meaning I had to work hard not to touch this guy. I was wearing monochromatic Dries Van Noten—dark navy suit trousers with a matching overshirt that blended like an obliquely cut Maoist jumpsuit.
“You weren’t what I’d imagined,” he half joked. Yeah, you aren’t such a looker yourself, hun…
He was staying in a suite on the top floor. Save for the bold wallpaper on an accent wall, the décor was minimal and modernist, which made for a stark contrast with the panoramic view of the medieval city below. The absence of luggage seemed weird, but not worth dwelling on. Then I hesitated. Oh, wait, I’m alone in a posh hotel room with some old guy. I looked over at the king bed, then noticed a little bottle of hand lotion on the table next to it. Fuck, fuck, fuck—was Nix using me as bait?
I clutched my bag, hoping the laptop inside was heavy enough to land an effective blow. At that moment, Steve Bannon walked over to the large sofa adjacent to the bed and offered me a seat. To my extreme relief, he grabbed a chair for himself and asked if I wanted some water. As he sat down, his stomach spilled over his waistline.
“Nix tells me you’re doing research on cultural change,” he said. “Tell me about that.”
I told him we were using computers to quantify cultural trends and predict how they will evolve in places at risk for extremism. “We try to glimpse into the destiny of cultures,” I said, aiming to distill decades’ worth of computational and social theory. Bannon rolled his eyes. “Yeah, yeah, yeah. You can cut the bullshit and tell me what it is you actually do.”
We talked for four hours—not only about politics but about fashion and culture, Foucault, the third-wave feminist Judith Butler, and the nature of the fractured self. On the surface, Bannon seemed utterly predictable—another old, straight white guy—but he spoke with a certain wokeness I hadn’t expected at all. In fact, I quickly decided he was kind of cool. As we started trading ideas on measuring culture, I offered to show him some of our data. I opened a Tableau workbook and called up a map of Trinidad. I clicked a button and a layer of neon-yellow dots began to populate the map. “Those are real people, by the way,” I said. “They are the ones we have demographic data on…gender, age, ethnicity.”
I clicked again and more dots appeared. “And now we are adding in online footprinting—like Internet browsing.”
I clicked again. “And here are records with census information…and now social media profiles.” I continued to add layers and he leaned in. The map lit up more and more, with little clusters of dots growing outward until, after the final click, the map was dazzling, in a multitude of colors. He asked who had paid for it, but I told him I couldn’t say. As I started to outline the types of research into social media networks that DARPA was funding, he asked if something similar could be carried out in America.
“I don’t see why not,” I said.
STEVE BANNON WAS BORN in Virginia in the early 1950s to a working-class Irish Catholic family. He went to a Catholic military high school and graduated with a degree in urban affairs from Virginia Tech, then served in the Navy as a surface warfare officer before a post at the Pentagon writing reports on the status of the U.S. Navy fleet worldwide. In the 1980s, his life took an academic turn—a 1983 master’s in national security studies from Georgetown University, a 1985 M.B.A. from Harvard Business School. After a tour in investment banking, Bannon moved on to making films in Hollywood as an executive producer, director, and writer. He worked on more than thirty films, including a documentary about Ronald Reagan. In 2005, Bannon joined the Hong Kong–based Internet Gaming Entertainment (IGE), and a year later he brought in a $60 million investment, half of which came from his former employer Goldman Sachs. The company eventually rebranded as Affinity Media Holdings, and Bannon continued to help run it until 2012, when he joined Breitbart. Next, Bannon co-founded the Government Accountability Institute, which eventually published the book Clinton Cash, by Breitbart News editor at large Peter Schweizer.
In 2005, the right-wing commentator Andrew Breitbart began Breitbart.com, an online news aggregator, and by 2007 it had grown to publish original content as Breitbart News. The site ran on the undercurrent of Breitbart’s personal philosophy, which has been referred to as the Breitbart Doctrine: Politics flows from culture, and if conservatives wanted to successfully dam up progressive ideas in America, they would have to first challenge the culture. And so Breitbart was founded to be not only a media platform but also a tool for reversing the flow of American culture.
When Andrew Breitbart (who had introduced the Mercers to Bannon) died suddenly in 2012, Bannon took his place as senior editor, and assumed his philosophy. At our first meeting, he was the executive chair of Breitbart and had come to Cambridge in search of promising young conservatives and candidates to staff his new London bureau. The logic, as we later learned with Brexit, was that Britain served as an important cultural signifier for Americans. Win the Brits, and so falls America, Bannon later told me, as the mythologies and tropes of Hollywood had crafted an image of Britain as a country of educated, rational, and classy people. He had a problem, though. For all the site’s sound and fury, it became pigeonholed as a place for young, straight white guys who couldn’t get laid. Gamergate was one of the first, most public instances of their culture war: When several women tried to bring to light the gross misogyny within the gaming industry, they were hounded, doxed, and sent numerous death threats in a massive campaign against the “progressives” imposing their “feminist ideology” onto gaming culture.
Gamergate was not instigated by Breitbart, but it was a sign to Bannon, who saw that angry, lonely white men could become incredibly mobilized when they felt that their way of life was threatened. Bannon realized the power of cultivating the misogyny of horny virgins. Their nihilistic anger and talks of “beta uprisings” simmered in the recesses of the Internet. But growing an army of “incels” (involuntary celibates) would not be sufficient for the movement he fantasized about. He needed to find a new approach.
This is one of the odder moments in the Cambridge Analytica saga—the random airplane conversation that changed history. Several months before I met Bannon, two Republican consultants, Mark Block and Linda Hansen, happened to be sitting next to an ex–military officer who had worked as a subcontractor for a company that utilized “cyberwarfare” in elections. Block fell asleep on the flight, but Hansen and her seatmate started chatting, and the man told her about SCL’s projects in information warfare. When the flight landed, Hansen told Block they needed to contact Nix. Block, who had been the campaign manager for Herman Cain, was well connected to the fringe elements of Republican circles. He knew Bannon and understood immediately that SCL would be of interest to him. So Block connected Bannon with Nix, and I wound up in this hotel suite meeting the man who would later stage a mass manipulation of the American psyche.
By the time I walked through the doors of the Varsity Hotel, Nix had already met with Bannon several times in New York. But when Nix tried to explain our projects, he ran into a problem—he didn’t actually understand what we were working on. He was in deeply unfamiliar territory with Bannon, who cared more about the details of the research than the pedigree of the researchers. Inside SCL, Nix was typically relegated by the other directors to deal with their “less serious” clients. Nix became more active in the company after his father, who was a large shareholder, died in 2007. He had graduated with average marks in art history from the University of Manchester but preferred the various enterprises of wealthy friends and family to galleries or libraries.
Bannon was not a typical client for Nix, who was far more used to dealing with ministers or businessmen from the developing nations of Britain’s old empire. Bannon did not need a second passport from a tropical nation. He was not looking for colonial cosplay in London, and he did not care how Nix pronounced his words or about the tailoring of his bespoke suit. Bannon wanted real things. It was deeply disorienting for a man accustomed to seducing ministers with scantily clad Ukrainian women and inebriated Etonian banter.
Originally, Nix suggested to Bannon that we meet somewhere on London’s Pall Mall, a street lined with grand stone buildings. A couple of blocks north of Buckingham Palace, Pall Mall begins at Trafalgar Square and ends at St. James’s Palace, the sixteenth-century residence of several members of the royal family. The area is home to some of Britain’s most exclusive private gentlemen’s clubs, where black tie is common and Nix socialized with his peers, sucking down drinks in opulent surroundings. Nix had imagined an elaborate dinner in a private dining room at the Carlton Club, meticulously planning the menu and serving staff, only to be rebuffed at the last minute.
Still, Nix knew that everyone, including Bannon, suffers the yearning of an unfulfilled secret self. He realized that the American was lounging in the ancient universities of England to play out a role—when Bannon looked in the mirror, he saw a philosopher. To win him over, Nix would need to help him achieve his fantasy of becoming a thinker of big thoughts. And so my “academic” vibe became just what he needed to lure Bannon into role-play.
Today Bannon is famous, but as we sat in that hotel room in the autumn of 2013, I knew virtually nothing about Steve from America. Even so, I quickly realized we were kindred spirits. We had ended up in politics, but our shared passion was culture, with his ambitions in film and mine in fashion. He indulged my interest in deconstructing trends and agreed that many of our social norms could be boiled down to aesthetics. And we both saw what was bubbling in tech and online spaces. He talked about gamers, memes, and MMORPGs—online games like World of Warcraft with huge numbers of players. He used the word “pwned” in a sentence, which is a gamer expression that implies domination or humiliation of a rival. We connected on all the things that made us weird. As we sat talking together, I found myself growing unexpectedly comfortable with him. He was no political hack, but a fellow nerd given permission to speak freely.
When Bannon said he was interested in changing culture, I asked him how he defined culture. There was a long pause. I told him that if you can’t define something, you can’t measure it, and if you can’t measure it, you can’t know if you are changing it.
Rather than dive deep into theory, I gave Bannon a grossly simplified example of what culture is by using cultural stereotypes. Italians have a reputation for being more passionate and extroverted than other people. (Having dated one, I can testify to the grain of truth behind this reputation.) And while it’s obvious that not all Italians are loud and brimming with passion, if you visit Italy, you’ll probably find more people who are extroverted in their presentation than if you visit, say, Germany or Singapore. This can be thought of as a norm—the peak on a bell-shaped distribution curve of extroversion or loudness. And perhaps Italy peaks a bit further up the scale than other countries.
When we describe cultures, we use the language and vocabulary of personality. We use the same words to describe both people and peoples. On the one hand, we can’t stereotype at the individual level, because every person is different. But on the other hand, we can say that, in a broader sense, Italian culture can be characterized as probably a bit more outgoing than many other cultures.
If we can measure or infer certain traits in individuals using personal data, and then use those same traits to describe a culture, we can chart a distribution, creating an approximate metric for that culture. This framework made it possible for us to propose how we could use personal data found on social media, in clickstreams, or from data vendors to identify, for example, who the most extroverted Italian people are through their patterns of behavior as individual consumers and users. Then, if one wants to shift the culture to make it slightly less extroverted, this data gives us a list of actual named Italians, ordered by their degree of extroversion, whom we could track and target over time, trying to chip away at their extroversion. In other words, culture change can be thought of as nudging the distribution curve of culture up or down. What the data allowed us to do was to disaggregate that culture into individuals, who became movable units of that society.
Bannon was someone who liked to talk, but when I got into a subject that interested him, he was quiet and even deferential. But he was also eager to get back to applications. To understand how this might become a practical campaign, think of public health. When a communicable disease threatens a population, you immunize certain vectors first—usually babies and old people, as they are most susceptible to infection. Then nurses and doctors, teachers and bus drivers, as they are most likely to spread a contagion through wide social interaction, even if they do not succumb to the disease themselves. The same type of strategy could help you change culture. To make a population more resilient to extremism, for example, you would first identify which people are susceptible to weaponized messaging, determine the traits that make them vulnerable to the contagion narrative, and then target them with an inoculating counter-narrative in an effort to change their behavior. In theory, of course, the same strategy could be used in reverse—to foster extremism—but that was not something I had even considered.
THE GOAL IN HACKING is to find a weak point in a system and then exploit that vulnerability. In psychological warfare, the weak points are flaws in how people think. If you’re trying to hack a person’s mind, you need to identify cognitive biases and then exploit them. If you walk up to a random person on the street and ask, “Are you happy?” the chances are high that she will say yes. If, however, you walk up to that same person and first ask, “Have you gained weight in the last few years?” or “Are any people from your high school more successful than you?” and then you ask “Are you happy?”—that same person will be less inclined to answer yes. Nothing about her personal situation or history has actually changed. But her perception of her life has. Why? Because one piece of information in her mind was weighted more than the others.
What we played with as the questioner was how she was weighting that information, which in turn affected her judgment of that information. We biased her mental model of her life. So which is true? Is she happy or not happy? The answer depends on which information is being pulled to the front of her mind. In psychology, this is called priming. And this is, in essence, how you weaponize data: You figure out which bits of salient information to pull to the fore to affect how a person feels, what she believes, and how she behaves.
Unless someone’s parents are secretly Vulcan, no one on earth is a purely rational thinker. We are all affected with cognitive biases, which are the commonly occurring errors in our thinking that generate flawed subjective interpretations of information. It is completely normal for people to process information with bias—in fact, everyone does—and oftentimes these biases are harmless in day-to-day life. These biases are not random in each person. Rather, they are systematic errors, meaning they create patterns in common forms of irrational thinking. In fact, thousands of cognitive biases have been identified in the field of psychology. Some biases are so common and seemingly intuitive that it can be hard for people to even recognize that they are actually irrational.
For example, the psychologists Amos Tversky and Daniel Kahneman conducted a study that asked participants a very simple question: “Suppose you sample a word at random from an English text. Is it more likely that the word starts with a k, or that k is the third letter?” Most people responded with the former, that words that start with k (e.g., kitchen, kite, or kilometer) are more likely. However, the opposite is true, and one is actually twice as likely in a typical English text to encounter words where the third letter is a k, such as ask, like, make, joke, or take. They tested for five letters (k, l, n, r, and v) like this. It is easier for people to think of words by first letter because we are taught to organize (or alphabetize) words by their first letter. However, people conflate this ease of recall with frequency or probability, even when this is far from the truth. This cognitive bias is called the availability heuristic, and is just one of many biases that affect our thinking. The bias is why, for example, people who see more news reports of violent murders on the news tend to think that society is becoming more violent when in fact global murder rates have been declining overall during the last quarter century.
I had been pondering these ideas based on my experiences in politics, then fashion, and then information warfare. Political extremism, for example, is a cultural activity with parallels in fashion: They’re both based on how cultural information proliferates through the nodes of a network. The rise of jihadism and the popularity of Crocs can both be thought of as the products of information flows. When I started my research into cultural information for SCL’s counter-extremism work, I drew upon similar concepts, approaches, and tools to those I was exploring in fashion forecasting—adoption cycles, diffusion rates, network homophily, etc. The work was all about trying to anticipate how people would internalize and then spread cultural information—whether that meant in joining a death cult or in choosing a wardrobe.
Bannon immediately grasped all of this, even telling me that he believed, as I do, that politics and fashion are essentially products of the same phenomenon. It was obvious that he treated intelligence gathering in a broad and deep way, which is not something I’ve seen many people in politics do. And that’s what makes him so powerful. He reads about intersectional feminism or the fluidity of identity not, as I later learned, because he’s open to those ideas but because he wants to invert them—to identify what people attach themselves to and then to weaponize it. What I didn’t know that day was that Bannon wanted to fight a cultural war, and so he had come to the people who specialized in informational weapons to help him build his arsenal.
Bannon and I were clearly on the same wavelength, and the conversation that day flowed so naturally, it felt as if we were flirting—but not, because that would be gross. But intellectually, we were a match. I left that meeting feeling uplifted and validated by someone who had taken the time to listen. Bannon came across as a reasonable guy when I first met him—nice, even. I could tell he appreciated learning new ideas and got excited by their possibilities. But what struck me was how this guy was a cultural maven and a tech nerd. I realized he had a bit of a libertarian streak, but we hadn’t talked that much about politics.
Then I remembered I had lost my wallet. I called Nix to tell him how everything had gone—and that I needed a new ticket. “Chris, I’m busy, sort it out yourself.”
BANNON’S INTEREST IN OUR work wasn’t merely academic; he had big ideas for SCL. He told Nix of a major right-wing donor who might be persuaded to make an investment in the firm. Robert Mercer was unusual for a billionaire. He’d gotten a Ph.D. in computer science in the early 1970s, then went on to become a cog in the wheel at IBM for twenty-some years. In 1993, he joined a hedge fund called Renaissance Technologies, where he used data science and algorithms to inform his investments—and made a stupid amount of money doing it. Mercer wasn’t one of these wheeler-dealer types who frenetically bought and sold businesses. He was an extremely introverted engineer who applied his technical skills very specifically to the art and science of making money.
Over the years, Mercer had donated millions of dollars to conservative campaigns. He also started the Mercer Family Foundation, run by his then-thirty-nine-year-old daughter, Rebekah, which originally supported research and other charities, but had begun to also donate to politically involved nonprofit groups. His wealth and influence placed him alongside the Koch brothers and Sheldon Adelson in the pantheon of Republican donors. The news that Mercer might be willing to invest in SCL made Nix salivate. Mercer’s profile was one of disrupting the financial sector. Renaissance was one of the highest-performing hedge funds in the industry—and Mercer built the firm by eschewing traditional finance backgrounds and instead hiring physicists, mathematicians, and scientists to build his firm’s algorithms. But Mercer, it seemed, wanted us to attempt an even more ambitious version of profitable disruption. By profiling every citizen in a country, imputing their personalities and unique behaviors, and placing those profiles in an in silico simulation of that society (one created inside a computer), we would be building the first prototype of the artificial society. If we could play with an economy or culture in a simulation of artificial agents with the same traits as the actual people they represented, we could just possibly create the most powerful market intelligence tool yet imagined. And by adding quantified cultural signals, we were verging on a new area of something akin to “cultural finance.” We thought that if we got it right, we could run simulations of different futures of whole societies. Forget shorting companies; think about entire economies.
It turned out that what Mercer had in mind went beyond the economy, but at the time our focus was on demonstrating what SCL was capable of doing. After some deliberation, Bannon decided that we should run a proof of concept in Virginia, which felt like a good microcosm of America. It’s a little bit northern and a little bit southern. It has mountains and coastal areas, military towns, wealthy D.C. suburbs, rural areas and farms, and a cross section of rich and poor, black and white. The Virginia experiment would mark the first time we’d played with data in the United States. As I’d done with the LPC and the Lib Dems, we started off with qualitative research—unstructured, open-ended conversations with local people. Nobody on the SCL team was American, and we didn’t know anything about Virginia, which was as foreign to me as Ghana. The obvious first step was to visit the state and talk to people, to learn how they perceived the world and what mattered to them. We couldn’t generate questions until they had introduced themselves to us, in their own way and in their own environment. Once we had a better feel for what Virginians cared about and how they approached things, we could then structure specific questions for quantitative research. Politics and culture are so intertwined that one cannot usually study one without the other.
So, along with Mark Gettleson, Brent Clickard, and a few others, I flew to America, arriving in Virginia in October 2013, shortly before statewide elections there. One of the things we heard in focus groups was concern about the Republican candidate for governor, the former state attorney general Ken Cuccinelli. He was a super-right-wing type who had advocated for initiatives to roll back gay rights and fight environmental protections. The Republican Party in Virginia has an enormous bloc of evangelical Christian voters, and Cuccinelli needed them if he was going to win. But, as we discovered in our research, he went so hard after their votes, he overshot his mark.
One of Cuccinelli’s initiatives was to petition a federal court to reverse its ruling on Virginia’s “Crimes Against Nature” law. Originally passed in 1950 and formally struck down in 2013 by the U.S. Fourth Circuit Court of Appeals (in light of a 2003 U.S. Supreme Court decision to decriminalize sexual activity between consenting adults), the statute technically outlawed oral and anal sex. Cuccinelli argued that the law was needed to combat pedophilia. On paper, he reminded me of crazed politicians we’d encountered in parts of Africa, obsessed with gays and their bedroom sins. But social extremists and weirdos can be found anywhere, even in white-bread America.
People in our focus groups—particularly straight, red-blooded American men—kept saying how weird they thought this was. Ban the gay stuff, sure, but why ban all non-procreative sex? Why was Cuccinelli so opposed to blow jobs? Let’s be real—isn’t that a little weird? These guys kept talking about how they didn’t like thinking about Cuccinelli and getting head, and who could blame them? We kept hearing about this issue, so we decided to try an experiment.
In the five-factor model of personality, conservatives tend to display a combination of two traits: lower openness and higher conscientiousness. In the most general way, Republicans aren’t likely to seek out novelty or to express curiosity about new experiences (with closet cases being the obvious exception). At the same time, they favor structure and order, and they don’t like surprises. Democrats are more open but also often less conscientious. This is in part why political debates often center around behavior and the locus of personal responsibility.
Our qualitative research told us, among many other things, that Virginia Republicans were put off by Cuccinelli’s obsession with blow jobs. And psychometric testing also told us that Republicans don’t like unpredictability. Could we create a strategy, using those two observations, to move the needle of opinion on Cuccinelli?
This was where Gettleson’s brilliance came into play. He was particularly fascinated by alpha-male voters and Cuccinelli’s conundrum with them, but he also knew it would be tricky to thread the needle in terms of message. So he focused on the weirdness factor. People were put off because they thought Cuccinelli was being weird. What if his messaging acknowledged that? We decided to test a message that simply stated, “You might not agree, but at least you know where I stand.” That way, even if people thought his position was crazy, at least he could turn it into a predictable and ordered kind of crazy.
We convened focus groups, online panels, and digital ad tests to try out the slogan, and it outperformed all the other messages we tried—even though it was essentially meaningless. This was a big realization: We were able to sway voters’ opinions by tailoring the candidate’s message to match their psychometric tests. And because so many Republicans display these personality traits, that framing device—I am who I am, and you know where I stand—would probably work equally well for other Republicans. This strategy performed better among high scorers in conscientiousness who had been unsure about Cuccinelli. For them, it framed Cuccinelli as “the devil you know” and positioned his salient “quirkiness” as at least a reliable quirkiness.
It turns out that Republicans can accept a batshit insane candidate, so long as it’s consistent insanity. This finding later informed almost everything that Cambridge Analytica worked on. From there, of course, it’s a short jump to having a candidate brag that he could stand in the middle of Fifth Avenue and shoot somebody without losing support.
IN THE COURSE OF our experiment, we compiled reams of personal information about the people of Virginia. It was easy to get—we just bought access to it through data brokers such as Experian, Acxiom, and niche firms with specialist lists from evangelical churches, media companies, and so on. Even some state governments will sell you lists of hunting, fishing, or gun licensees. Did the state government bureaus care, or even bother to ask, where this data on their citizens was going? Nope. We could have been fraudsters or foreign spies and they wouldn’t have had a clue.
Most people know Experian as a consumer credit reporting company. That’s how it started out, calculating credit scores for people based on a variety of financial factors. The company would collect information from a wide array of sources—airline memberships, media companies, charities, even amusement parks. It also gathered information from government agencies, such as the DMV, fishing and hunting licensing, and gun licensing. As it compiled these detailed profiles, the company realized it could make additional money using them for marketing.
In the 1990s, political strategists started buying personal information to use in campaigns. Think about it: If you know what kind of car or truck a person drives, whether they hunt, what charities they give to, and what magazines they subscribe to, you can start to form a picture of that person. Many Democrats and Republicans have a look. And their look was captured in this data snapshot. You can then target potential voters based on that information.
We also got access to census data. Unlike developing nations with less stringent privacy controls, the U.S. government won’t provide raw data on specific individuals, but you can get information, down to the county or neighborhood level, on crime, obesity, and illnesses such as diabetes and asthma. A census block typically contains six hundred to three thousand people, which means that by combining many sources of data, we could build models that infer those attributes about individuals. For example, by referencing risk or protective factors for diabetes, such as age, race, location, income, interest in health food, restaurant preference, gym membership, and past use of weight-loss products (all of which are available in most U.S. consumer files), we could match that data against aggregated statistics about a locality’s diabetes rates. We could then create a score for each person in a given neighborhood measuring the likelihood that they had a health issue like diabetes—even if the census or consumer file never directly provided that data on its own.
Gettleson and I spent hours exploring random and weird combinations of attributes. Were there people who had gun licenses but also belonged to the ACLU? Were there people who had season tickets to a symphony and a lifetime NRA membership? Are gay Republicans even real? One day we found ourselves wondering whether there were donors to anti-gay churches who also shopped at organic food stores. We did a search of the consumer data sets we had acquired for the pilot and found a handful of people whose data showed that they did both.
I instantly wanted to meet one of these mythical creatures, in part because I was curious but also because I wanted to make sure our data was accurate. We pulled the names that came up, then sent them to a call center, where agents phoned each person to ask if they’d be willing to meet with a researcher to answer some questions. Most said no, but there was one woman who agreed—and whom I couldn’t wait to meet. Her spending habits seemed all over the map—a Whole Foods shopper with an interest in yoga, but also a member of an anti-gay church and a donor to right-wing charities—which made me suspect that either our data was somehow faulty or this person was among the most fascinating characters in the United States.
The woman’s data guided me to a modest split-level in the suburbs of Fairfax County. For a moment, I hesitated. “Ugh, is this going to be awkward?” But I’d come all this way, so I walked up to the door and rang the bell. I heard wind chimes just over my head. Then a perky blonde with blown-out hair opened the door and almost leapt at me. “HEYYYY!!! Come on in!” As we entered the house I noticed she was indeed wearing Lululemon yoga pants. She showed me into her living room, which smelled of incense and had statues of both Buddha and the elephant-headed Hindu god Ganesh. Then I spotted a crucifix on the wall. It was all pretty extra.
When she offered me a glass of homemade kombucha, I accepted. In the kitchen, she opened a large jar of something and poured an extremely ripe and slightly coagulated liquid into a glass.
“It’s really probiotic.”
“Yeah, I can tell,” I answered, looking at the floating chunks in the glass.
As we started talking, she spoke in New Age terms about trying to “align her positive energy,” inspired, no doubt, by the Deepak Chopra on her bookshelf. But when we started talking about morality, she shifted abruptly into fire-and-brimstone evangelical views—particularly about gay people, who she knew were going straight to hell (no pun intended). Yet even the way she expressed that belief was a strange amalgamation: She said that being gay was like a block in your energy—a sinful block. She evangelized to me for two hours as I sat there scribbling notes, as though we were participants in some kind of messed-up therapy session.
I came away from that encounter swirling with ideas. I felt like I was on to something important, because how the hell would a pollster classify this woman? This convinced me we needed to invest more in understanding the nuances behind the demographics. I once met the primatologist Jane Goodall, and she said something that always stuck with me. Mingling at a reception, I asked why she researched primates in the wild instead of in a controlled lab. It’s simple, she said: Because they don’t live in labs. And neither do humans. If we are to really understand people, we have to always remember that they live outside of data sets.
It’s amazing how easy it is to get drawn into something you are interested in. We were a British military contractor, working on big ideas, with a growing team of mostly gay and mostly liberal data scientists and social researchers. So why had we started working with this eclectic mix of hedge fund managers, computer scientists, and a guy who ran a niche right-wing website? Because the idea was a killer one. With free rein to study such an abstract and fluid thing as culture, we could be breaking into a new field of researching societies. If we could put society into a computer, we could start to quantify everything and encapsulate problems like poverty and ethnic violence in a computer; we could simulate how to fix them. And just as the woman did not see the contradictions in her idols, I did not yet see the contradiction in what I was doing.