IF THEN: How the Simulmatics Corporation Invented the Future
– Jill Lepore A brilliant, revelatory account of the Cold War origins of the data-mad, algorithmic twenty-first century, from the author of the acclaimed international bestseller, These Truths. The Simulmatics Corporation, founded in 1959, mined data, targeted voters, accelerated news, manipulated consumers, destabilised politics, and disordered knowledge–decades before Facebook, Google, Amazon, and Cambridge Analytica. Silicon Valley likes to imagine it has no past but the scientists of Simulmatics are the long-dead grandfathers of Mark Zuckerberg and Elon Musk. Borrowing from psychological warfare, they used computers to predict and direct human behaviour, deploying their “People Machine” from New York, Cambridge, and Saigon for clients that included John Kennedy’s presidential campaign, the New York Times, Young & Rubicam, and, during the Vietnam War, the Department of Defense. Jill Lepore, distinguished Harvard historian and New Yorker staff writer, unearthed from the archives the almost unbelievable story of this long-vanished corporation, and of the women hidden behind it. In the 1950s and 1960s, Lepore argues, Simulmatics invented the future by building the machine in which the world now finds itself trapped and tormented, algorithm by algorithm. “A person can’t help but feel inspired by the riveting intelligence and joyful curiosity of Jill Lepore. Knowing that there is a mind like hers in the world is a hope-inducing thing.” –George Saunders “Everything Lepore writes is distinguished by intelligence, eloquence, and fresh insight. If Then is that, and even more: It’s absolutely fascinating, excavating a piece of little-known American corporate history that reveals a huge amount about the way we live today and the companies that define the modern era.” –Susan Orlean “Data science, Jill Lepore reminds us in this brilliant book, has a past, and she tells it through the engrossing story of Simulmatics, the tiny, long-forgotten company that helped invent our data-obsessed world, in which prediction is seemingly […]