Trump Knows You Better Than You Know Yourself

Trump Knows You Better Than You Know Yourself
Psychometrics and the (counter)revolution in marketing that is helping bring fascism to power around the world

AntiNote: The following is an unauthorized translation of a December 2016 article that caused quite a stir in the German-language press. Das Magazin (Zurich) occupies a respected position within the German-language cultural and literary media landscape, functionally similar to (though perhaps not quite as prominent as) The New Yorker, and this work by investigative reporters Hannes Grassegger and Mikael Krogerus got a lot of attention—and generated some controversy, for apparently having scooped the English-language media with sensational observations about 2016’s most sensational story, the campaign and electoral victory of a fascist dictator in the United States.

Perhaps for this reason, the article has not appeared in translation in (or even had its investigative threads taken up by) English-language media outlets, even after nearly two months. Antidote presents, therefore, our own preemptive translation to fill this gap. We trust the skill of the reporters who wrote it and the veracity of their claims (which are verifiable by anyone with a search engine—we have embedded links where appropriate), and we question why this particular synthesis of public information is not being made available to non-German-speaking readers by outlets with more reach and respectability than us dirty DIY dicks.

On the occasion of this article’s authorized wider release in English, should that come to pass, we will consider removing this post if we are asked nicely. Until then: Enjoy!

[25 January 2017: There seems to have been a revised English version by Das Magazin circulating privately, which the Antidote Writers Collective was able to obtain. It corrects some minor flaws in the original version as well as dealing with an initial response to the article by Cambridge Analytica. We have now included the Das Magazin version below ours, for your comparison, as we prepare to merge the two.]

“I just showed that the bomb was there.”
By Hannes Grassegger and Mikael Krogerus for Das Magazin (Zurich)
3 December 2016 (original post)

Psychologist Michal Kosinski developed a method of analyzing people’s behavior down to the minutest detail by looking at their Facebook activity—thus helping Donald Trump to victory.

On November 9th, around 8:30 in the morning, Michal Kosinski awoke in his hotel room in Zurich. The 34-year-old had traveled here to give a presentation to the Risk Center at the ETH [Eidgenössische Technische Hochschule or Federal Institute of Technology, Zurich] at a conference on the dangers of Big Data and the so-called digital revolution. Kosinski gives such presentations all over the world. He is a leading expert on psychometrics, a data-driven offshoot of psychology. Turning on the television this morning in Zurich, he saw that the bomb had gone off: defying the predictions of nearly every leading statistician, Donald J. Trump had been elected president of the United States of America.

Kosinski watched Trump’s victory celebration and the remaining election returns for a long while. He suspected that his research could have had something to do with the result. Then he took a deep breath and turned off the television.

On the same day, a little-known British company headquartered in London issued a press release: “We are thrilled that our revolutionary approach to data-driven communications played such an integral part in president-elect Donald Trump’s extraordinary win,” Alexander James Ashburner Nix is quoted as saying. Nix is British, 41 years old, and CEO of Cambridge Analytica. He only appears in public in a tailored suit and designer eyeglasses, his slightly wavy blond hair combed back.

The meditative Kosinski, the well-groomed Nix, the widely grinning Trump—one made this digital upheaval possible, one carried it out, and one rode it to power.

How dangerous is Big Data?

Anyone who didn’t spend the last five years on the moon has heard the term Big Data. The emergence of Big Data has meant that everything we do, online or off-, leaves digital traces. Every purchase with a card, every Google search, every movement with a cellphone in your pocket, every “like” gets stored. Especially every “like.” For a while it wasn’t entirely clear what any of this data would be good for, other than showing us ads for blood pressure medication in our Facebook feeds after we google “high blood pressure.” It also wasn’t entirely clear whether or in what ways Big Data would be a threat or a boon to humanity.

Since November 9th, 2016, we know the answer. Because one and the same company was behind Trump’s online ad campaigns and late 2016’s other shocker, the Brexit “Leave” campaign: Cambridge Analytica, with its CEO Alexander Nix. Anyone who wants to understand the outcome of the US elections—and what could be coming up in Europe in the near future—must begin with a remarkable incident at the University of Cambridge in 2014, in Kosinski’s department of psychometrics.

Psychometrics, sometimes also known as psychography, is a scientific attempt to “measure” the personality of a person. The so-called Ocean Method has become the standard approach. Two psychologists were able to demonstrate in the 1980s that the character profile of a person can be measured and expressed in five dimensions, the Big Five: Openness (how open are you to new experiences?), Conscientiousness (how much of a perfectionist are you?), Extroversion (how sociable are you?), Agreeableness (how considerate and cooperative are you?), and Neuroticism (how sensitive/vulnerable are you?). With these five dimensions (O.C.E.A.N.), you can determine fairly precisely what kind of person you are dealing with—her needs and fears as well as how she will generally behave. For a long time, however, the problem was data collection, because to produce such a character profile meant asking subjects to fill out a complicated survey asking quite personal questions. Then came the internet. And Facebook. And Kosinski.

A new life began in 2008 for the Warsaw-born student Michal Kosinski when he was accepted to the prestigious University of Cambridge in England to work in the Cavendish Laboratory at the Psychometrics Center, the first-ever psychometrics laboratory. With a fellow student, Kosinski created a small app for Facebook (the social media site was more straightforward then than it is now) called MyPersonality. With MyPersonality, you could answer a handful of questions from the Ocean survey (“Are you easily irritated?” – “Are you inclined to criticize others?”) and receive a rating, or a “Personality Profile” consisting of traits defined by the Ocean method. The researchers, in turn, got your personal data. Instead of a couple dozen friends participating, as initially expected, first hundreds, then thousands, then millions of people had bared their souls. Suddenly the two doctoral students had access to the then-largest psychological data set ever produced.

The process that Kosinski and his colleagues developed over the years that followed is actually quite simple. First surveys are distributed to test subjects—this is the online quiz. From the subjects’ responses, their personal Ocean traits are calculated. Then Kosinski’s team would compile every other possible online data point of a test subject—what they’ve liked, shared, or posted on Facebook; gender, age, and location. Thus the researchers began to find correlations, and began to see that amazingly reliable conclusions could be drawn about a person by observing their online behavior. For example, men who “like” the cosmetics brand MAC are, to a high degree of probability, gay. One of the best indicators of heterosexuality is liking Wu-Tang Clan. People who follow Lady Gaga, furthermore, are most probably extroverted. Someone who likes philosophy is more likely introverted.

Kosinski and his team continued, tirelessly refining their models. In 2012, Kosinski demonstrated that from a mere 68 Facebook likes, a lot about a user could be reliably predicted: skin color (95% certainty), sexual orientation (88% certainty), Democrat or Republican (85%). But there’s more: level of intellect; religious affiliation; alcohol-, cigarette-, and drug use could all be calculated. Even whether or not your parents stayed together until you were 21 could be teased out of the data.

How good a model is, however, depends on how well it can predict the way a test subject will answer certain further questions. Kosinski charged ahead. Soon, with a mere ten “likes” as input his model could appraise a person’s character better than an average coworker. With seventy, it could “know” a subject better than a friend; with 150 likes, better than their parents. With 300 likes, Kosinski’s machine could predict a subject’s behavior better than their partner. With even more likes it could exceed what a person thinks they know about themselves.

The day he published these findings, Kosinski received two phonecalls. One was a threat to sue, the other a job offer. Both were from Facebook.

Only Visible to Friends

In the meantime, Facebook has introduced the differentiation between public and private posts. In “private” mode, only one’s own friends can see what one likes. This is still no obstacle for data-collectors: while Kosinski always requests the consent of the Facebook users he tests, many online quizzes these days demand access to private information as a precondition to taking a personality test. (Anyone who is not overly concerned about their private information and who wants to get assessed according to their Facebook likes can do so at Kosinski’s website, and then compare the results to those of a “classic” Ocean survey here).

It’s not just about likes on Facebook. Kosinski and his team have in the meantime figured out how to sort people according to Ocean criteria based only on their profile pictures. Or according to the number of their social media contacts (this is a good indicator of extroversion). But we also betray information about ourselves when we are offline. Motion sensors can show, for example, how fast we are moving a smartphone around or how far we are traveling (correlates with emotional instability). A smartphone, Kosinski found, is in itself a powerful psychological survey that we, consciously or unconsciously, are constantly filling out.

Above all, though—and this is important to understand—it also works another way: using all this data, psychological profiles can not only be constructed, but they can also be sought and found. For example if you’re looking for worried fathers, or angry introverts, or undecided Democrats. What Kosinski invented, to put it precisely, is a search engine for people. And he has been getting more and more acutely aware of both the potential and the danger his work presents.

The internet always seemed to him a gift from heaven. He wants to give back, to share. Information is freely reproducible, copyable, and everyone should benefit from it. This is the spirit of an entire generation, the beginning of a new era free of the limits of the physical world. But what could happen, Kosinski asked himself, if someone misused his search engine in order to manipulate people? His scientific work [e.g.] began to come with warnings: these prediction techniques could be used in ways that “pose a threat to an individual’s well-being, freedom, or even life.” But no one seemed to understand what he meant.

Around this time, in early 2014, a young assistant professor named Aleksandr Kogan approached Kosinski. He said he had received an inquiry from a company interested in Kosinski’s methods. They apparently wanted to psychometrically measure the profiles of ten million American Facebook users. To what purpose, Kogan couldn’t say: there were strict secrecy stipulations. At first, Kosinski was ready to accept—it would have meant a lot of money for his institute. But he hesitated. Finally Kogan divulged the name of the company: SCL, Strategic Communications Laboratories. Kosinski googled them [so did Antidote. Here. —ed.]: “We are a global election management agency,” said the company website [really, the website has even creepier language on it than that. “Behavioral change communication”? Go look already]. SCL offers marketing based on a “psychographic targeting” model. With an emphasis on “election management” and political campaigns? Disturbed, Kosinski clicked through the pages. What kind of company is this? And what do they have planned for the United States?

What Kosinski didn’t know at the time was that behind SCL there lay a complex business structure including ancillary companies in tax havens, as the Panama Papers and Wikileaks revelations have since shown. Some of these had been involved in political upheavals in developing countries; others had done work for NATO, developing methods for the psychological manipulation of the population in Afghanistan. And SCL is also the parent company of Cambridge Analytica, this ominous Big Data firm that managed online marketing for both Trump and the Brexit “Leave” campaign.

Kosinski didn’t know any of that, but he had a bad feeling: “The whole thing started to stink,” he remembers. Looking into it further, he discovered that Aleksandr Kogan had secretly registered a company to do business with SCL. A document obtained by Das Magazin confirms that SCL learned about Kosinski’s methods through Kogan. It suddenly dawned on Kosinski that Kogan could have copied or reconstructed his Ocean models in order to sell them to this election-manipulating company. He immediately broke off contact with him and informed the head of his institute. A complicated battle ensued within Cambridge University. The institute feared for its reputation. Aleksandr Kogan moved to Singapore, got married, and began calling himself Dr. Spectre. Michal Kosinski relocated to Stanford University in the United States.

For a year or so it was quiet. Then, in November 2015, the more radical of the two Brexit campaigns (leave.eu, led by Nigel Farage) announced that they had contracted with a Big Data firm for online marketing support: Cambridge Analytica. The core expertise of this company: innovative political marketing, so-called microtargeting, on the basis of the psychological Ocean model.

Kosinski started getting emails asking if he had had anything to do with it—for many, his is the first name to spring to mind upon hearing the terms Cambridge, Ocean, and analytics in the same breath. This is when he heard of Cambridge Analytica for the first time. Appalled, he looked up their website. His methods were being deployed, on a massive scale, for political purposes.

After the Brexit vote in July the email inquiries turned to insults and reproaches. Just look what you’ve done, friends and colleagues wrote. Kosinski had to explain over and over again that he had nothing to do with this company.

First Brexit, Then Trump

September 19th, 2016: the US presidential election is approaching. Guitar riffs fill the dark blue ballroom of the Grand Hyatt Hotel in New York: CCR’s “Bad Moon Rising.” The Concordia Summit is like the WEF in miniature. Decision makers from all over the world are invited; among the guests is Johann Schneider-Ammann [then nearing the end of his year term as president of Switzerland’s governing council].

A gentle women’s voice comes over the PA: “Please welcome Alexander Nix, Chief Executive Officer of Cambridge Analytica.” A lean man in a dark suit strides towards the center of the stage. An attentive quiet descends. Many in the room already know: this is Trump’s new Digital Man. “Soon you’ll be calling me Mr. Brexit,” Trump had tweeted cryptically a few weeks before. Political observers had already been pointing out the substantial similarities between Trump’s agenda and that of the rightwing Brexit camp; only a few had noticed the connection to Trump’s recent engagement with a largely unknown marketing company: Cambridge Analytica.

Before then, Trump’s online campaign had consisted more or less of one person: Brad Parscale, a marketing operative and failed startup founder who had built Trump a rudimentary website for $1,500. The 70-year-old Trump is not what one would call an IT-whiz; his desk is unencumbered by a computer. There is no such thing as an email from Trump, his personal assistant once let slip. It was she who persuaded him to get a smartphone—the one from which he has uninhibitedly tweeted ever since.

Hillary Clinton, on the other hand, was relying on the endowment of the first social media president, Barack Obama. She had the Democratic Party’s address lists, collected millions of dollars over the internet, received support from Google and Dreamworks. When it became known in June 2016 that Trump had hired Cambridge Analytica, Washington collectively sneered. Foreign noodlenecks in tailored suits who don’t understand this country and its people? Seriously?

“Ladies and gentlemen, honorable colleagues, it is my privilege to speak to you today about the power of Big Data and psychographics in the electoral process.” The Cambridge Analytica logo appears behind Alexander Nix—a brain, comprised of a few network nodes and pathways, like a subway map. “It’s easy to forget that only eighteen months ago Senator Cruz was one of the less popular candidates seeking nomination, and certainly one of the more vilified,” begins the blond man with his British diction that produces the same mixture of awe and resentment in Americans that high German does the Swiss. “In addition, he had very low name recognition; only about forty percent of the electorate had heard of him.”

Everyone in the room was aware of the sudden rise, in May 2016, of the conservative senator within the Republican field of presidential candidates. It was one of the strangest moments of the primary campaign. Cruz had been the last of a series of Republican opponents to come out of nowhere with what looked like a credible challenge to frontrunner Trump. “How did he do this?” continues Nix.

Cambridge Analytica had begun engaging with US elections towards the end of 2014, initially to advise the Republican Ted Cruz, and paid by the secretive American tech billionaire Robert Mercer. Up to that point, according to Nix, election campaign strategy had been guided by demographic concepts. “But this is a really ridiculous idea, the idea that all women should receive the same message because of their gender; or all African-Americans because of their race.” The Hillary Clinton campaign team was still operating on precisely such amateurish assumptions—Nix need not even mention—which divide the electorate up into ostensibly homogeneous groups…exactly the same way as all the public opinion researchers who predicted a Clinton victory did.

Nix clicks to the next slide: five different faces, each representing a personality profile. It is the Ocean model. “At Cambridge, we’ve rolled out a long-form quantitative instrument to probe the underlying traits that inform personality. This is the cutting edge in experimental psychology.” It is now completely silent in the hall. “By having hundreds and hundreds of thousands of Americans undertake this survey, we were able to form a model to predict the personality of every single adult in the United States of America.” The success of Cambridge Analytica’s marketing arises from the combination of three elements: this psychological behavioral analysis of the Ocean model, Big Data evaluation, and ad targeting. Ad targeting is personalized advertisement tailored as precisely as possible to the character of a single consumer.

Nix explains forthrightly how his company does this (the presentation can be viewed on YouTube). From every available source, Cambridge Analytica buys up personal data: “What car you drive, what products you purchase in shops, what magazines you read, what clubs you belong to.” Voter and medical records. On the screen behind him are displayed the logos of global data traders like Acxiom and Experian—in the United States nearly all personal consumer data is available for purchase. If you want to know, for example, where Jewish women live, you can simply buy this information. Including telephone numbers. Now Cambridge Analytica crosschecks these data sets with Republican Party voter rolls and online data such as Facebook likes, and constructs an Ocean personality profile. From a selection of digital signatures there suddenly emerge real individual people with fears, needs, and interests—and home addresses.

The process is identical to the models that Michal Kosinski developed. Cambridge Analytica also uses IQ-Quiz and other small Ocean test apps in order to gain access to the powerful predictive personal information wrapped up in the Facebook likes of users. And Cambridge Analytica is doing precisely what Kosinski had warned about. They have assembled psychograms for all adult US citizens, 220 million people, and have used this data to influence electoral outcomes.

Nix clicks to the next slide. “This is a data dashboard that we prepared for the Cruz campaign for the Iowa caucus. It looks intimidating, but it’s actually very simple.” On the left, graphs and diagrams; on the right, a map of Iowa, where Cruz had done surprisingly well in the caucuses. On this map, hundreds of thousands of tiny dots, red and blue. Nix begins to narrow down search criteria to a category of Republican caucus-goers he describes as a “persuasion” group, whose common Ocean personality profile and home locations are now visible, a smaller set of people to whom advertisement can be more effectively tailored. Ultimately the criteria can be narrowed to a single individual, along with his name, age, address, interests, and political leanings. How does Cambridge Analyica approach this person with political messaging?

Earlier in the presentation, using the example of the Second Amendment, Nix showed two variations on how certain psychographic profiles are spoken to differently. “For a highly Neurotic and Conscientious audience, you’re going to need a message that is both rational and fear-based: the threat of a burglary and the ‘insurance policy’ of a gun is very persuasive.” A picture on the left side of the screen shows a gloved hand breaking a window and reaching for the inside door handle. On the right side, there is a picture of a man and child silhouetted against a sunset in tall grass, both with rifles, obviously duck hunting: “for a Closed and Agreeable audience, people who care about traditions and habits and family and community, talking about these values is going to be much more effective in communicating your message.”

How to Keep Clinton Voters Away

Trump’s conspicuous contradictions and his oft-criticized habit of staking out multiple positions on a single issue result in a gigantic number of resulting messaging options that creates a huge advantage for a firm like Cambridge Analytica: for every voter, a different message. Mathematician Cathy O’Neil had already observed in August that “Trump is like a machine learning algorithm” that adjusts to public reactions. On the day of the third presidential debate between Trump and Clinton, Trump’s team blasted out 175,000 distinct variations on his arguments, mostly via Facebook. The messages varied mostly in their microscopic details, in order to communicate optimally with their recipients: different titles, colors, subtitles, with different images or videos. The granularity of this message tailoring digs all the way down to tiny target groups, Nix explained to Das Magazin. “We can target specific towns or apartment buildings. Even individual people.”

In the Miami neighborhood of Little Haiti, Cambridge Analytica regaled residents with messages about the failures of the Clinton Foundation after the 2010 earthquake in Haiti, in order to dissuade them from turning out for Clinton. This was one of the goals: to get potential but wavering Clinton voters—skeptical leftists, African-Americans, young women—to stay home. To “suppress” their votes, as one Trump campaign staffer bluntly put it. In these so-called dark posts (paid Facebook ads which appear in the timelines only of users with a particular suitable personality profile), African-Americans, for example, are shown the nineties-era video of Hillary Clinton referring to black youth as “super predators.”

“Blanket advertising—the idea that a hundred million people will receive the same piece of direct mail, the same television advert, the same digital advert—is dead,” Nix begins to wrap up his presentation at the Concordia Summit. “My children will certainly never understand this concept of mass communication. Today, communication is becoming ever increasingly targeted.

“The Cruz campaign is over now, but what I can tell you is that of the two candidates left in this election, one of them is using these technologies. And it’s going to be very interesting to see how they impact the next seven weeks. Thank you.” With that, he exits the stage.

It is not knowable just to what extent the American population is being targeted by Trump’s digital troopers—because they seldom attack through the mainstream broadcast media, but rather mostly with highly personalized ads on social media or through digital cable. And while the Clinton team sat back in the confidence that it was safe with its demographic calculations, a new crew was moving into the Trump online campaign headquarters in San Antonio, Texas, as Bloomberg journalist Sasha Issenberg noted with surprise after a visit. The Cambridge Analytica team, apparently just a dozen people, had received around $100,000 from Trump in July; in August another $250,000; five million in September. Altogether, says Nix, they took in around fifteen million.

And the company took even more radical measures: starting in July 2016, a new app was prepared for Trump campaign canvassers with which they could find out the political orientation and personality profile of a particular house’s residents in advance. If the Trump people ring a doorbell, it’s only the doorbell of someone the app has identified as receptive to his messages, and the canvassers can base their line of attack on personality-specific conversation guides also provided by the app. Then they enter a subject’s reactions to certain messaging back into the app, from where this new data flows back to the control rooms of Cambridge Analytica.

The company divided the US population into 32 personality types, and concentrated on only seventeen states. And just as Kosinski had determined that men who like MAC cosmetics on Facebook are probably gay, Cambridge Analytica found that a predeliction for American-produced cars is the best predictor of a possible Trump voter. Among other things, this kind of knowledge can inform Trump himself which messages to use, and where. The decision to focus candidate visits in Michigan and Wisconsin over the final weeks of the campaign was based on this manner of data analysis. The candidate himself became an implementation instrument of the model.

What is Cambridge Analytica Doing in Europe?

How great an influence did these psychometric methods have on the outcome of the election? Cambridge Analytica, when asked, did not want to disclose any documentation assessing the effectiveness of their campaign. It is possible that the question cannot be answered at all. Still, some indicators should be considered: there is the fact that Ted Cruz, thanks to the help of Cambridge Analytica, rose out of obscurity to become Trump’s strongest competitor in the primaries; there is the increase in rural voter turnout; there is the reduction, compared to 2008 and 2012, in African-American voter participation. The circumstance of Trump having spent so little money on advertising could also speak for the effectiveness of personality-specific targeting, as could the fact that three quarters of his marketing budget was spent in the digital realm. Facebook became his ultimate weapon and his best canvasser, as a Trump staffer tweeted. In Germany, the rightwing upstart party Alternative für Deutschland (AfD) may like the sound of this, as they have more Facebook friends than Merkel’s Christian Democrats (CDU) and the Social Democrats (SPD) combined.

It is therefore not at all the case, as is so often claimed, that statisticians lost this election because their polls were so faulty. The opposite is true: statisticians won this election. It was just certain statisticians, the ones using the new method. It is a cruel irony of history that Trump, such a detractor of science, won the election thanks to science.

Another big winner in the election was Cambridge Analytica. Steve Bannon, a Cambridge Analytica board member and publisher of the ultra-rightwing online site Breitbart News, was named Trump’s chief strategist. Marion Maréchal-Le Pen, ambitious Front National activist and niece of the presidential candidate, has tweeted that she has accepted the firm’s invitation to collaborate. In an internal company video, there is a live recording of a discussion entitled “Italy.” Alexander Nix confirms that he is in the process of client acquisition, worldwide. They have received inquiries out of Switzerland and Germany.

Kosinski has been observing all of this from his office at Stanford. After the election, the university was in an uproar. Kosinski responded to the developments with the most powerful weapon available to researchers: a scientific analysis. Along with his research colleague Sandra Matz, he conducted a series of tests that will soon be published. The first results seen by Das Magazin are unsettling: psychological targeting, as Cambridge Analytica deployed it, increases the clickthru rate on Facebook ads by more than sixty percent. And the so-called conversion rate (the term for how likely a person is to act upon a personally-tailored ad, i.e. whether they buy a product or, yes, go vote) increases by a staggering 1400 percent.*

The world has been turned upside down. The Brits are leaving the EU; Trump rules America. It all began with one man, who indeed tried to warn of the danger, and who still gets accusatory emails. “No,” says Kosinski quietly, shaking his head, “this is not my fault. I did not build the bomb. I just showed that it was there.”

Translated by Antidote

Featured image: cartoon by Christiane Pfohlmann; text is untranslatable wordplay in which Trump is saying “I can’t do anything about it” and “I have Nix to thank.” Source: toonpool.com

Paul-Olivier Dehaye contributed to the preparation of the original article, which also included a link to his website where you can request your data from Cambridge Analytica: PersonalData.IO

* The study mentioned made a series of comparisons: a product was advertised online in two ways—one tailored to fit the character profile of a consumer and the other designed to clash with their character—and the respective conversion rates measured.

*         *         *

“I did not build the bomb. I only showed that it exists.”
The strange connection between psychologist Michal Kosinski and Donald Trump’s victory

By Hannes Grassegger and Mikael Krogerus (*)

On 9 November at around 8.30 a.m., Michal Kosinski woke up in the Hotel Sunnehus in Zurich. The 34-year old researcher had come to give a lecture at the Swiss Federal Institute of Technology (ETH) about the dangers of Big Data and the digital revolution. Kosinski gives regular lectures on this topic all over the world. He is a leading expert in psychometrics, a data-driven sub-branch of psychology. When he turned on the TV that morning, he saw that the bombshell had exploded: contrary to forecasts by all leading statisticians, Donald J. Trump had been elected President of the United States.

For a long time, Kosinski watched the Trump victory celebrations and the results coming in from each state. He had a hunch that the outcome of the election might have something to do with his research. Finally, he took a deep breath and turned off the TV.

On the same day, a then little known British company based in London sent out a press release: “We are thrilled that our revolutionary approach to data-driven communication has played such an integral part in President-elect Trump’s extraordinary win,” a certain Alexander James Ashburner Nix was quoted as saying. Nix is British, 41 years old, and CEO of Cambridge Analytica. He is always immaculately turned out in tailor-made suits and designer glasses, with his wavy blonde hair combed back from his forehead.

Of these three players – reflective Kosinski, carefully groomed Nix and grinning Trump – one of them enabled the digital revolution, one of them executed it and one of them benefited from it.

How dangerous is Big Data?

Anyone who has not spent the last five years living on another planet will be familiar with the term Big Data. Big Data means that everything we do, both on and offline, leaves digital traces. Every purchase we make with our cards, every search we type into Google, every movement we make when our mobile phone is in our pocket, every “like” is stored. Especially every “like”. For a long time, it was not entirely clear what use this data could have – except, perhaps, that we might find adverts for blood pressure on our monitors just after we’ve Googled “reduce blood pressure”. It was also unclear whether Big Data would endanger or benefit humanity. On 9 November the answer became clear. The company behind Trump’s online campaign, as well as behind the Brexit campaign, was a Big Data company: Cambridge Analytica, whose CEO is Alexander Nix.

To understand the outcome of the election – and what might hit Europe in the coming months – we have to begin with a strange incident at Cambridge University in 2014, at Kosinski’s Psychometrics Centre.

Psychometrics, sometimes also called psychographics, focuses on measuring psychological traits, such as personality. In the 1980s, two teams of psychologists proved that every trait of a human being can be assessed based on five dimensions of personality, known as the “Big Five”. These are: openness (how open you are to new experiences?), conscientiousness (how much of a perfectionist are you?), extraversion (how sociable are you?), agreeableness (how considerate and cooperative you are?) and neuroticism (are you easily upset?). Based on these dimensions – they are also known as OCEAN an acronym for openness, conscientiousness, extroversion, agreeableness, neuroticism – we can make a relatively accurate assessment of the kind of person in front of us. This includes his or her needs and fears, and how he or she is likely to behave. The “Big Five” has become the standard technique of psychometrics. But for a long time, the problem with this approach was data collection, because it involved filling out a complicated, highly personal questionnaire. Then came the Internet. And Facebook. And Kosinski.

Michal Kosinski was a student in Warsaw when his life took a new direction in 2008. He was accepted by Cambridge University to do his PhD at the Psychometrics Centre, one of the oldest Institutions of this kind worldwide. Kosinski joined fellow student David Stillwell (now a lecturer at Judge Business School at the University of Cambridge) about a year after Stillwell had launched a little Facebook application in the days when the platform had not yet become the behemoth it is today. Their MyPersonality app enabled users to fill out different psychometric questionnaires, including a handful of psychological questions from the Big Five personality questionnaire (“I panic easily”– “I contradict others”). Based on the evaluation, users received a “personality profile” – individual Big Five values – and could opt-in to share their Facebook profile data with the researchers. Kosinski had expected a few dozen college friends to fill in the questionnaire, but before long, hundreds, thousands, then millions of people had revealed their innermost convictions. Suddenly, the two doctoral candidates owed the largest dataset combining psychometric scores with Facebook profiles ever to be collected.

The approach that Kosinski and his colleagues developed over the next few years was actually quite simple. First, they provided test subjects with a questionnaire in the form of an online quiz. From their responses, the psychologists calculated the personal Big Five values of respondents. Kosinski’s team then compared the results with all sorts of other online data from the subjects: what they “liked”, shared or posted on Facebook, or what gender, age, place of residence they specified, for example. This enabled the researchers to join the dots and make correlations. Remarkably reliable deductions could be drawn from simple online actions. For example, men who “liked” the cosmetics brand MAC were slightly more likely to be gay; one of the best indicators for heterosexuality was “liking” Wu-Tang Clan. Followers of Lady Gaga were most probably extroverts, while those who “liked” philosophy tended to be introverts. While each piece of such information is too weak to produce a reliable prediction, when tens, hundreds, or thousands of individual datapoints are combined, the resulting predicitions become really accurate.

Kosinski and his team tirelessly refined their models. In 2012, Kosinski proved that on the basis of an average of 68 Facebook “likes” by a user, it was possible to predict their skin colour (95% accuracy) their sexual orientation (88% accuracy), and their affiliation to the Democrat or Republican party (85%). But it didn’t stop there. Intelligence, religion, as well as alcohol, cigarette and drug use, could all be determined. From the data it was even possible to deduce whether deduce whether someone’s parents were divorced. The strength of a model was illustrated by how well it could predict a subject’s answers. Kosinski continued to work on the model incessantly: before long, his model was able to evaluate a person better than the average work colleague, merely on the basis of ten Facebook “likes”. Seventy “likes” were enough to outdo what a person’s friends knew, 150 what their parents knew, and 300 “likes” what their partner knew. More “likes” could even surpass what a person thought they knew about themselves. On the day that Kosinski published these findings, he received two phone calls. The threat of a lawsuit and a job offer. Both from Facebook.

Only weeks later Facebook “likes” became private by default. Before, the default setting was that anyone on the internet could see your Likes. But this was no obstacle to data collectors: while Kosinski always asked for the consent of Facebook users, many apps and online quizzes today require access to private data as a precondition for personality tests. (Anybody who wants to evaluate themselves based on their Facebook “likes” can do so on Kosinski’s website applymagicsauce.com, and then compare their results to those of a classic Ocean questionnaire: discovermyprofile.com/personality.html.)

But it was not just about “likes” or even Facebook: Kosinski and his team could now ascribe Big Five values based purely on how many profile pictures on Facebook or on how many contacts a person has (a good indicator of extraversion). But we also reveal something about ourselves when we’re offline. For example, the motion sensor on our phone reveals how quickly we move and how far we travel (this correlates with emotional instability). Our smartphone, Kosinski concluded, is a vast psychological questionnaire that we are constantly filling out, both consciously and unconsciously. Above all, however – and this is key – it also works in reverse: not only can psychological profiles be created from your data, but your data can also be used the other way round to search for specific profiles: all anxious fathers, all angry introverts, for example – or maybe even all undecided Democrats? Essentially, what Kosinski had invented was sort of a people search engine.

Kosinski started to recognise the potential – but also the inherent danger – of his work. To him, the Internet had always seemed like a gift from heaven. What he really wanted was to give something back, to share. Data can be copied, so why shouldn’t everyone benefit from it? It was the spirit of a whole generation, the beginning of a new era that transcended the limitations of the physical world. But what would happen, wondered Kosinski, if someone abused his people search engine to manipulate people? He began to add warnings to most of his scientific work. His approach, he warned, “could pose a threat to an individual’s well-being, freedom, or even life”. But no one seemed to grasp what he meant.

Around this time, in early 2014, Kosinski was approached by a young assistant professor called Aleksandr Kogan. He was inquiring on behalf of a company that was interested in Kosinski’s method. The company wanted to access the myPersonality database, Kosinski remembers. Kogan wasn’t at liberty to reveal for what purpose; he was bound to secrecy. At first, Kosinski and his team considered this offer, as it would mean a great deal of money for the institute – but then he hesitated. Finally, Kosinski remembers, Kogan came out with the name of the company: SCL – Strategic Communication Laboratories. Kosinski Googled the company: “[We are] the premier election management agency”, it says on the company’s website. SCL provides marketing based on psychological modelling. One of its core focuses: Influencing elections. Influencing elections? Perturbed, Kosinski clicked through the pages. What kind of company was this? And what were these people planning?

What Kosinski did not know at the time: SCL is the front for a group of companies. Who exactly owns SCL and its diverse branches is unclear, thanks to convoluted corporate structures – as can be seen in the UK Companies House, the Panama Papers and the Delaware company registry . Some of the SCL offshoots have been involved in overthrowing governments in developing countries, whereas others have developed methods for psychologically manipulating Afghan citizens for NATO. And meanwhile, SCL is also the parent company of Cambridge Analytica, that ominous Big Data outfit that later worked for Trump’s online campaign and Brexit.

Kosinski knew nothing about all this, but he had a bad feeling. “The whole thing started to stink,” he recalls. On further investigation, he discovered that Aleksandr Kogan had secretly registered a company doing business with SCL. As revealed later by the Guardian in December 2015, and from documents seen by Das Magazin, it emerges that SCL found out about Kosinski’s method from Kogan. Suddenly it dawned on Kosinski that they might have reproduced (or copied?) the Facebook Likes-based Big Five measurement tool in order to sell it to this election-influencing company. He immediately broke off contact with him and informed the director of the institute, sparking off a complicated conflict within the university. The institute was worried about its reputation. Aleksandr Kogan then moved to Singapore, married, and changed his name to Dr. Spectre. Michal Kosinski finished his PhD, got a job offer from Stanford and moved to the USA.

All was quiet for about a year. Then, in November 2015, the more radical of the two Brexit campaigns, “Leave.EU”, supported by Nigel Farage, announced that it had commissioned a Big Data company to support its online campaign: Cambridge Analytica. The company’s core strength: innovative political marketing – microtargeting – by measuring people’s personality from their digital footprints, based on the OCEAN model.

Now Kosinski received emails asking what he had to do with it – the words Cambridge, personality, and analytics immediately made many people think of Kosinski. It was the first time he had heard of the company. Horrified, he looked at the website. Was his methodology being used on a grand scale for political purposes?

After the Brexit result, friends and acquaintances wrote to him: Just look at what you’ve done. Everywhere he went, Kosinski had to explain that he had nothing to do with this company.

Months passed. 19 September 2016 comes around; the U.S. elections are fast approaching. Guitar riffs fill the dark-blue hall of the New York Grand Hyatt hotel; Creedence Clearwater Revival’s “Bad Moon Rising”. The Concordia Summit is a kind of World Economic Forum in miniature. Decision-makers from all over the world have been invited, among them Swiss President Schneider- Ammann. “Please welcome to the stage Alexander Nix, Chief Executive Officer of Cambridge Analytica,” a smooth female voice announces. A slim man in a dark suit walks onto the stage. A hush falls. (The video is on Youtube). Many people present know that this is Trump’s new digital strategy man. “Soon you’ll be calling me Mr. Brexit,” Trump had tweeted somewhat cryptically a few weeks earlier. Political observers had indeed noticed some striking similarities between Trump’s agenda and that of the right-wing Brexit movement. But few had noticed the connection with Trump’s recent hiring of a marketing company named Cambridge Analytica.

Up to this point, Trump’s digital campaign had consisted of more or less one person: Brad Parscale, a marketing entrepreneur and failed start-up founder who created a rudimentary website for Trump for 1,500 dollars. The 70-year-old Trump is not digitally savvy – there isn’t even a computer on his office desk. Trump doesn’t do emails, his personal assistant once revealed. She herself talked him into having a smartphone – from which he now tweets incessantly.

Hillary Clinton, on the other hand, relied heavily on the legacy of the first “social-media President”, Barack Obama. She had the address lists of the Democratic Party, worked with cutting-edge big data analysts from “BlueLabs” and received support from Google and DreamWorks. When it was announced in June 2016 that Trump had hired Cambridge Analytica, the establishment in Washington just turned up their noses. Foreign dudes in tailor-made suits who don’t understand the country and its people? Seriously?

“It is my privilege to speak to you today about the power of Big Data and psychographics in the electoral process.” The logo of Cambridge Analytica – a brain composed of network nodes, like a map, appears behind Alexander Nix. “Only eighteen months ago, Senator Cruz was one of the less popular candidates,” explains the blonde man in a cut-glass British accent, which puts Americans on edge the same way that a standard German accent can unsettle Swiss people. “Less than 40 per cent of the population had heard of him”, another slide says. At the end of 2014, Cambridge Analytica had become involved in the U.S. election campaign, initially as a consultant for Republican Ted Cruz, funded by the secretive U.S. software billionaire Robert Mercer. Everyone in the room knows about the meteoric rise of the conservative Senator Cruz. It was one of the strangest events of the election campaign: How had Senator Cruz become the last serious challenger to Trump in the Republican primaries, rising from 5 to 35 percent? “So how did he do this?” Up to now, explains Nix, election campaigns have been organised based on demographic concepts. “A really ridiculous idea. The idea that all women should receive the same message because of their gender – or all African Americans because of their race.” What Nix means is that other campaigners so far have relied on demographic whereas Cambridge Analytica is using psychometrics.

Though this might be true, Cambridge Analytica’s role within Cruz’s campaign isn’t undisputed. In December 2015 the Cruz team credited their rising success to psychological use of data and analytics. In “Advertising Age” a political client called the embedded Cambridge staff “like an extra wheel”, but found their the core product, Cambridge’s voter data modeling, still “excellent”. Similarly it remains unclear how deeply CA was involved in the “Leave”-campaign. Cambridge Analytica will not discuss such questions.

Nix clicks to the next slide: five different faces, each face corresponding to a personality profile. It is the Big Five or OCEAN Model. “At Cambridge,” says Nix, “we were able to form a model to predict the personality of every single adult in the United States of America.” The hall is now captivated. According to Nix, the success of Cambridge Analytica’s marketing is based on a combination of three elements: behavioural science using the OCEAN Model, Big Data analysis, and ad targeting. Ad targeting is personalised advertising, in other words, advertising that is aligned as accurately as possible to the personality of an individual consumer.

Nix candidly explains how his company does this. First Cambridge Analytica buys personal data from a range of different sources like e.g. land registries, automotive data, shopping data, bonus cards, club memberships, what magazines you read, what churches you attend. Nix displays the logos of globally active data brokers like Acxiom and Experian – in the U.S., almost all personal data is for sale. For example, if you want to know where Jewish women live, you can simply buy this information, phone numbers included. Now Cambridge Analytica aggregates this data with the electoral rolls of the Republican party and online data such as Facebook “likes” – today the company claims to not have used Facebook data – and calculates a Big Five personality profile. Digital footprints suddenly become real people with fears, needs, interests – and residential addresses.

The methodology looks quite similar to the models that Michal Kosinski once developed. Cambridge Analytica also uses according to Nix “surveys on Social Media” and Facebook data. And Cambridge Analytica does exactly what Kosinski warned of: “We have profiled the personality of every adult in the United States of America – 220 million people,” Nix boasts. He opens the screenshot. “This is a data dashboard that we prepared for the Cruz Campaign.” A digital control center appears. On the left are diagrams; on the right, a map of Iowa, where Cruz won a surprisingly large number of votes in the primary. And on the map, there are hundreds of thousands of small red and blue dots. Nix narrows down the criteria: “Republicans” – the blue dots disappear; “not yet convinced” – more dots disappear; “male”, and so on. Finally, only one name remains, including age, address, interests, personality and political inclination. How does Cambridge Analytica now target this person with an appropriate political message?

Nix shows how psychographically categorised voters can be differently addressed, based on the example of gun rights, the 2nd Amendment: “For a highly neurotic and conscientious audience the threat of a burglary – and the insurance policy of a gun.” An image on the left shows the hand of an intruder smashing a window. The right side shows a man and a child standing in a field at sunset, both holding guns, clearly shooting ducks: “Conversely, for a closed and agreeable audience. People who care about tradition, and habits, and family.”

How to keep away Clinton voters from the ballot box

Trump’s striking inconsistencies, his much-criticized fickleness, and the resulting array of contradictory messages, suddenly turned out to be his great asset: a different message for every voter. That Trump acted like a perfectly opportunistic algorithm purely following audience reactions, is something the mathematician Cathy O’Neil remarked already in August 2016. “Pretty much every message that Trump put out was data-driven”, Alexander Nix remembers. On the day of the third presidential debate between Trump and Clinton, Trump’s team tested 175,000 different ad variations for his arguments, in order to find the right versions above all via Facebook. The messages differed for the most part only in microscopic details, in order to target the recipients in the optimal psychological way: different headings, colours, captions, with a photo or video. This fine-tuning reaches all the way down to the smallest groups, Nix explains in an interview with Das Magazin. “We can address villages or apartment blocks in a targeted way. Even individuals.”

In the Miami district of Little Haiti, Trump’s campaign provided inhabitants with news about the failure of the Clinton Foundation following the earthquake in Haiti – in order to stop them voting for Hillary Clinton. This was one of the goals: to keep potential Clinton voters (which include wavering left-wingers, African-Americans and young women) away from the ballot box, to “suppress” their vote, as one Trump employee puts it. These “dark posts” – sponsored news-feed- style ads in Facebook timelines that can only be seen by users with specific profiles – included videos aimed at Afro-Americans in which Hillary Clinton refers to black men as predators, for example.

Nix finishes his lecture at the Concordia Summit by stating that blanket advertising is dead. “My children will certainly never, ever understand this concept of mass communication.” And before leaving the stage, he announces that one of the remaining presidential candidates is using this new technology.

Just how precisely the American population was being targeted by Trump’s digital troops at that moment was not visible – because they attacked less on mainstream TV, and more with personalised messages on social media or digital TV. And while the Clinton team thought it was in the lead, based on demographic projections, Bloomberg journalist Sasha Issenberg was surprised to note on a visit to San Antonio – where Trump’s digital campaign is based – that a “second headquarters” was being created. The embedded Cambridge Analytica team, apparently only a dozen people, received 100,000 dollars from Trump in July, 250,000 in August, and five million in September. According to our conversation with Mr. Nix, it earned over 15 million dollars overall.

And the measures were radical: From July 2016, Trump’ canvassers were provided with an app, with which they could identify the political views and personality types of the inhabitants of a house. It was the same app provider used during Brexit. Trump’s people only rang at the doors of houses that the app rated as receptive to his messages. The canvassers came prepared with guidelines for conversations tailored to the personality type of the resident. In turn, the canvassers fed the reactions into the app – and the new data flowed back to the dashboards of the Trump Campaign.

Again, this is nothing new. The Clinton team did similar things – but as far as we know they did not use psychometrical profiling. CA however divided the U.S. population into 32 personality types, and focused on just 17 states. And just as Kosinski had established that men who like MAC cosmetics are slightly more likely to be gay, Cambridge Analytica discovered that a preference for cars made in the US was a great indication of a potential Trump voter. Among other things, these findings now showed Trump which messages worked best and where. The decision to focus on Michigan and Wisconsin in the final weeks of the campaign was made on the basis of data analysis. The candidate became the instrument for implementing a model.

What is Cambridge Analytica doing in Europe?

But to what extent did psychometric methods influence the outcome of the election? When asked, Cambridge Analytica is unwilling to provide any proof of the effectiveness of its campaign. And it is quite possible that the question, how important psychometrical targeting in the outcome of the 2016 election was, is impossible to answer. And yet there are clues: There is the fact of the surprising rise of Ted Cruz during the primaries. Also there was an increased number of voters in rural areas. There was the decline in the number of African-American early votes. The fact that Trump spent so little money may also be explained by the effectiveness of personality-based advertising. As does the fact that he invested far more in digital than TV campaigning compared to Hillary Clinton. Facebook proved to be the ultimate weapon and the best election campaigner, as tweets of several Trump employees show.

Many voices have claimed that the statisticians lost the election because their predictions were so off the mark. But what if the opposite is true: statisticians in fact helped win the election – but only those who were using the new method? It is an irony of history that Trump often grumbled about scientific research, but used a highly scientific approach in his campaign.

Another big winner is Cambridge Analytica. Its widely reported board member Steve Bannon, former executive chair of the right-wing online newspaper Breitbart News, has been appointed as Donald Trump’s Senior Counselor and chief strategist. Marion Maréchal-Le Pen, the aspiring Front- National activist and niece of France’s presidential candidate, already tweeted that she would accept his invitation to collaborate with him , and in an internal company video of Cambridge Analytica, a recording of a meeting is entitled “Italy”. Already in 2012 SCL Elections has been active in Italian politics. Whilst Cambridge Analytica is not willing to comment alleged ongoing talks with UK Prime Minister Theresa May, Alexander Nix claims that he is building up his client base worldwide, and that he has received inquiries from Switzerland and Germany.

Kosinski has observed all of this from his office at Stanford. Following the U.S. election, the university is in turmoil. Kosinski is responding to developments with the sharpest weapon available to a researcher: a scientific analysis. Together with his research colleague Sandra Matz, he has conducted a series of tests, which will soon be published. The initial results, which have been seen by Das Magazin, are alarming: The study shows the effectiveness of personality targeting by showing that marketers can attract up to 63% more clicks and up to 1,400% more conversions in real-life advertising campaigns on Facebook when matching products and marketing messages to consumers’ personality characteristics. They further demonstrate the scalability of personality targeting by showing that the majority of Facebook Pages promoting products or brands are affected by personality and that large numbers of consumers can be accurately targeted based on a single Facebook Page.

The world has been turned upside down. Great Britain is leaving the EU, Donald Trump is President-elect of the United States of America. And in Stanford the Polish researcher Michal Kosinski, who wanted to warn against the danger of using psychological targeting in a political setting, is once again receiving accusatory emails. “No,” says Kosinski quietly and shaking his head, “this is not my fault. I did not build the bomb. I only showed that it exists.”

* * *

After the publication of the German version of this article a Cambridge Analytica spokesman gave the following statement:

Cambridge Analytica does not use data from Facebook.

It has had no dealings with Dr Michal Kosinski.

Cambridge Analytica did not engage in efforts to discourage any Americans from casting their vote in the presidential election. Its efforts were solely directed towards increasing the number of voters in the election.

Nevertheless we have contradicting statements and evidence from the same company.

(*) additional research for this report was provided by Paul-Olivier Dehaye; www.personaldata.io