If Then by Jill Lepore

Long before Amazon, Twitter and Facebook, a company called Simulmatics Corporation sought to predict and control human behaviour through the analysis of big data. If Then tells the story of that company, from its humble beginnings in a tiny office on Madison Avenue to the hallways of political power in Washington DC.

The story starts and ends with Ed Greenfield. Greenfield was an ad man, businessman and an early adopter of new technology. An optimist might call him an entrepreneur in the vein of Bill Gates. A cynic might call him a huckster, a Hollywood-style conman whose life seems almost too bizarre to be true, until you start to read the closing credits read: Based on a true story.

In 1959, Ed Greenfield witnessed the landslide victory of President Eisenhower over Democratic opponent Adlai Stevenson. As an avid Democrat himself, Greenfield promised himself that it would never happen again. That year, he set up Simulmatics Corporation, a tech company with the aim of helping future Democrats get elected through predictive data.

But before he could, he needed a team.

If Then here begins to sound a bit like a heist movie. Picture the opening scenes of Ocean’s Eleven, where George Clooney and Brad Pitt start assembling a crew to rob a Vegas casino. Only this time, imagine a team being assembled by just one man. Ed Greenfield, a man capable of convincing just about anyone to come work for him.

First off was Eugene Burdick, a surfer and novelist who studied psychology at Stanford. Burdick, as many novelists do, fictionalized his own life. In a novel written in the 1960s, he created a character called Mike Freesmith who developed the Fear Principle:

There is one thing that the masses know: real authority. And a real authority is someone who can satisfy their desire to hate and their fear. A good authority works the two of them together.

Hate and fear, powered by technology. Where have I heard this story before?

In many ways, Simulmatics comes across as a 1960s precursor to Cambridge Analytica in 2016. In both instances, a tech company realized that people could be manipulated through targeted messaging. In Burdick’s case, he realized that people could not only be understood through big data, but that, through predictions, they could be controlled.

In 1962, the French sociologist Jacques Ellul wrote of this type of activity as propaganda. “Emotionalism, impulsiveness, excess – all these characteristics of the individual… are well known and very helpful” to the propaganda artist. The key to propaganda, Ellul says, is to make the individual “live in a separate world,” constructed out of constant messaging that occupies “every moment of the individual’s life.” A sentence could never have been more perfect to describe big tech, and in particular, social media.

Second in the Simulmatics line-up was Bill MacPhee, author of a dissertation on voting behaviour. Ed Greenfield read the dissertation in 1960, hired MacPhee, and turned the paper into a business plan. The idea was to create a People Machine, a computer program capable of analyzing voter data and public opinion surveys in order to predict how people would react to campaign strategies.

Public opinion polling would be broken down by demographic, with features like age, race, sex and location. The machine would then be able to answer any political question. It could tell a candidate whether to campaign in a particular state, for instance, by predicting the percentage effect of doing so on a particular demographic. This could help win national elections.

Today, we might compare it to the news media’s own obsession with polling. Every action by a politician – a scandal, a debate performance, a kiss on a baby’s head – is now viewed in the light of opinion poll data that reflect the public’s perceived reaction to it. Once enough data is gathered, the future becomes predictable. Hence the name, If Then.

Where If Then falters as a story is where it digresses from this core narrative arc. As soon as the ball gets rolling on the history of Simulmatics as a company, the book backpedals into a comprehensive history of U.S. politics. The underlying motivation to discuss politics makes sense. Greenfield was motivated to setup Simulmatics in order to influence U.S. elections, after all. But is it relevant to discuss decades of political history in between only a few short segments on the book’s central characters?  Maybe not.

Even constructing the linearity of this review required jumping through entire segments of the book which barely mentioned Simulmatics at all. Possibly, the author lacked the requisite primary source material to create a history of Simulmatics itself. Even then, a choice needed to be made: either tell the history of U.S. politics or the history of a single U.S. technology company. In the end, the book does neither well.

But I digress.

Having assembled a team, Greenfield began traversing the corridors of media and political power. In 1960, he sent reports and recommendations from his People Machine to the Kennedy campaign, who insisted in public that they did not read them. In 1962 and 64, Simulmatics signed a contract with the New York Times to predict the midterm and presidential elections respectively. It turned out a bit of a disaster, but they got paid for the disaster regardless. In 1966, the company went to Vietnam to run surveys of the Vietnamese people to understand the effects of the US military’s psychological warfare.

See how quickly that went from politics to killing people?

What this all tells us is that these sorts of tools –the psychological manipulation of people through big data- has always had a certain appeal with our political leaders. Instead of winning votes through evidence and logic, politicians would rather use psychological manipulation through big tech. In the 1960s, this was done through crude national opinion poll surveys. Today, we might consider our social media feeds, likes and shares, our purchase history, our Google searches and our past behavioural data.

The powerful pretend to want to know us in order to better serve our needs. What they really want is data points to exploit our weaknesses. When we become mere numbers on a page, ticking up or down based on our behaviour, we become malleable to a new kind of politics. A politics that does not listen to the people, but seeks to control how those people speak and what they might say. The risk in companies like Simulmatics, Google, Facebook and so on, is when we begin to worship, praise and lionize those who wish to control our lives.

  • This was originally published on Australian Book Review.

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