How to manipulate and win an election: Cambridge Analytica story

The name Cambridge Analytica popped in Kenya a year ahead of the 2017 elections with reports that Uhuru Kenyatta's Jubilee Party had hired the firm.

Its association with the Donald Trump campaign and Brexit had also just cropped up following an exposé by international media through whistleblower Christopher Wylie.

In his book, Mindf*ck: Cambridge Analytica And The Plot To Break America, Wylie suggests that the data-mining firm worked on the 2013 election as well.

In fact, in the book, Wylie details that the death of his predecessor in a hotel room in Nairobi in 2012 did not calm his nerves as he exited the firm in 2014.

He said that he pondered the consequences of going public including risking "the wrath of the president of the United States, his alt-right whisperer Steve Bannon, Downing Street, militant Brexiteers, and the sociopathic Alexander Nix".

He added that if he told the whole truth behind Cambridge Analytica, he risked angering Russians, hackers, WikiLeaks and a host of others who had shown no compunction about breaking laws in Africa, the Caribbean, Europe and beyond.

"I had seen people face serious threats to their safety; several of my former colleagues had warned me to be extremely careful after I left. Before joining SCL [Group], my predecessor, Dan Mureşan, had ended up dead in his hotel room in Kenya. This was a decision that I could not take lightly," Wylie writes.

SCL Group, formerly Strategic Communication Laboratories, was a private British behavioural research and strategic communication company. In the US and other countries, SCL is mainly known mainly through its subsidiary Cambridge Analytica.

Though his book lacks detail of what Cambridge Analytica did in the Kenyan elections, it provides insight into how voters' data has been used in elections worldwide.

From the book, one learns that the use of data for election purposes is as old as  Barack Obama's successful 2008 presidential campaign.

Wylie describes his encounter with the Obama campaign as the eyeopener to the use of data for election targeting.

"I liked roaming around and talking with people, so when it was time to switch focus to the data group, I wasn’t terribly excited to do it. But then I was introduced to Obama’s national director of targeting, Ken Strasma, who quickly changed my mind," Wylie writes of his time with the Obama campaign.

He writes that the sexy part of the Obama campaign was its branding and use of new media like YouTube.

Wylie describes this as "cool stuff", being a visual strategy nobody had used before because YouTube was still so new.

"That was what I wanted to see until Ken stopped me short. Forget the videos, he told me. I needed to go deeper, into the heart of the campaign’s tech strategy," Wylie writes.

He says that Strasma told him that everything that they do is predicated on understanding who the Obama campaign needed to talk to.

"In other words, the backbone of the Obama campaign was data. And the most important work Strasma’s team produced was the modelling they used to analyse and understand that data, which allowed them to translate it into an applied fit —to determine a real-world communications strategy through…artificial intelligence," Wylie says.

He adds, "As soon as I realised how effectively the Obama campaign was using algorithms to deliver its messages, I started studying how to create them on my own. I taught myself how to use basic software packages like MATLAB and SPSS, which let me mess around with data."

Wylie says that his self-teaching led him to start dealing with data on real people such as their age, gender, income, race, homeownership — even magazine subscriptions and airline miles.

"With the right data inputs, you could start to predict whether people would vote for Democrats or Republicans. You could identify and isolate the issues that were likely to be most important to them. You could begin to craft messages that would have a greater chance of swaying their opinions," he writes.

Wylie writes this interaction with the Obama campaign gave him a wholly new way of understanding politics, noting that data was being used as a force for good.

"It was being used to produce first-time voters, to reach people who felt left out. The deeper I got into it, the more I thought that data would be the saviour of politics. I couldn’t wait to get back to Canada and share with the Liberal Party what I’d learned from the next president of the United States," he writes.

It was after Obama's 2008 victory that more politicians started buying into this kind of data-driven campaigns.

After leaving the US, full of newly acquired data wisdom, Wylie went back home to Ottawa where he decided to introduce this new phenomenon to the Liberal Party of Canada.

They created a Voter Activation Network as he had learned in the Obama campaign but they had one problem — there was no data to run this engine.

Wylie's efforts to entrench this new way of campaigning in his party back home were not as successful as he would have liked and, therefore, he decided to leave for London to work with the Liberal Democrats.

"In 2011, one year after I left Ottawa, the LPC was devastated in the federal election by the Conservative Party of Canada, which had invested in sophisticated data systems at the behest of its imported Republican advisers," Wylie says.

But Wylie's luck seemed to have been at a low in London just as in Canada as the Lib Dems did not buy his data idea.

He says the Lib Dems were not happy with his reports that both Labour and the Tories had extensive data coverage of the voting population while they only had two per cent.

"I was showing them data, supplemented by peer-reviewed literature. I was showing them science. And they were responding by calling me pessimistic, problematic, not a team player," he writes.

As fate would have it, in 2014, the Liberal Democrats suffered their most historic defeat, losing 310 council seats and retaining only one of their 12 European Parliament seats.

The next year, the Lib Dems lost 49 of their 57 seats in Parliament. 

Wylie suggests that this would not have been the case if the party had listened to him.

Wylie explains that he joined SCL, Cambridge Analytica's parent company, in 2013 after a Liberal Democrats contact informed him of an opening there.

He says his friend told him that SCL was looking for "data people for some behaviour research project" involving the military.

"It never occurred to me to work on defence projects, but after two failures with political parties, in both Canada and Britain, I was ready to try something new," Wylie writes.

When he met Alexander Nix, the man who has become the face of Cambridge Analytica, Wylie says he was first made to sign a non-disclosure agreement (NDA) after which they had a discussion of the firm's work.

Wylie says he challenged Nix about their operations and told him they could do it better and left thinking that the meeting was a waste of time.

"But it wasn’t. Nix called soon after to ask if I’d be willing to talk some more, to explain what I thought SCL was doing wrong and how they might fix it," the former SCL employee says.

In June 2013 when he started working at SCL, Wylie says that his colleagues did not trust him and when he complained to Nix, he was handed a key to a cabinet in his office.

Here, he says, he found documents on operations SCL had executed for various clients including the British Ministry of Defence, the US government and NATO.

"Others detailed PSYOPS programs in Mexico and Kenya. As Nix had said before, these were projects that government agencies did not want to officially undertake themselves.

Rather, they would hire contractors to enter the region as a 'market research firm' or under some kind of faux-business cover," he writes in the book.

Wylie reveals that Cambridge Analytica was able to penetrate and build databases in developing countries using mobile phone data.

According to him, this data was readily available in a place like Kenya due to advancements in mobile phone payment.

This would perhaps be the explanation as to why a large number of Kenyan political parties have been accused of buying data from mobile money transfer agents in the recent past.

"One unintended consequence of having large pluralities of citizens connected via mobile phone networks was that everybody could be traced, tracked, profiled and communicated with," Wylie writes.

Without identifying the country, Wylie also describes a 2013  meeting with an African minister for Health who procured their services for election purposes.

The project was disguised as a health sector survey but was, in essence, a data-mining exercise for election purposes.

The book also explains how social media comes into play when dealing with data aimed at election manipulation.

Wylie says that Cambridge Analytica was a company that took large amounts of data and used it to design and deliver targeted content capable of moving public opinion at scale.

"None of this is possible, though, without access to the psychological profiles of the target population — and this, it turned out, was surprisingly easy to acquire through Facebook, with Facebook’s loosely supervised 'permissioning' procedures," he writes.

The firm created an app and after spending $1 million to pay $2 to $5 to approximately 320,000 US voters, it collected some 50 million Facebook profiles.

How the Cambridge Analytica team immediately used this data sounds like a scene from a movie as described by Wylie.

To test how credible this data was, the team made phone calls to a number of people whose profiles had been harvested, asking them questions related to the issues that CA had collected.

"It was surreal to think that these people were sitting in their kitchen in Iowa or Oklahoma or Indiana, talking to a bunch of guys in London who were looking at satellite pictures of where they lived, family photos, all of their personal information," Wylie writes.

Due to his work at Cambridge Analytica, Wylie was skeptical when journalists started approaching him for the inside story.

He always thought that it was CA that was out to get him and he had to question the journalists who were approaching him before he could speak.

Wylie had been warned of consequences and one of the men who had worked with CA on the US elections, Steve Bannon, was not part of the Trump administration.

He had to be careful with whom he spoke to about his work at CA and the operations of the data-mining firm.

But when he started speaking, the world started understanding more of what had happened in Brexit and the Trump campaign.

"Most of the people I told about Cambridge Analytica were fascinated with Trump, Brexit, or Facebook, but whenever I got onto the topic of Africa, I usually was met with shrugs," Wylie writes.

He adds, "What Cambridge Analytica was doing in Kenya, Ghana, Nigeria — it was a new era of colonialism, in which powerful Europeans exploited Africans for their resources. And although minerals and oil were still very much part of the equation, there was a new resource being extracted: data."

In the final chapter of his book, Wylie calls for tighter laws to safeguard not only data but also electoral processes.

"If we are to prevent another Cambridge Analytica from attacking our civil institutions, we must seek to address the flawed environment in which it incubated," he writes.

He further notes that for too long the congresses and parliaments of the world have fallen for a mistaken view that somehow “the law cannot keep up with technology.”

"The technology sector loves to parrot this idea, as it tends to make legislators feel too stupid or out of touch to challenge their power. But the law can keep up with technology, just as it has with medicines, civil engineering, food standards, energy, and countless other highly technical fields," he states.