I gnorance of history is a badge of honour in Silicon Valley. "The only thing that matters is the future," self-driving-car engineer Anthony Levandowski told The New Yorker in 2018 (ref. 1). Levandowski, formerly of Google, Uber and Google's autonomous-vehicle subsidiary Waymo (and recently sentenced to 18 months in prison for stealing trade secrets), is no outlier. The gospel of 'disruptive innovation' depends on the abnegation of history 2. 'Move fast and break things' was Facebook's motto. Never look back. Another word for this is heedlessness. And here are a few more: negligence, foolishness and blindness. Much of what technology leaders tout as original has been done before-and long ago. Yet few engineers and developers realize that they're stuck in a rut. That lack of awareness has costs, both economic and ethical. Consider the strange trajectory of the Simulmatics Corporation, founded in New York City in 1959. (Simulmatics, a mash-up of 'simulation' and 'automatic', meant then what 'artificial intelligence (AI)' means now.) Its controversial work included simulating elections-just like that allegedly 'pioneered' by the now-defunct UK firm Cambridge Analytica on behalf of UK Brexit campaigners in 2015 and during Donald Trump's US presidential election campaign in 2016. Journalists accused Trump's fixers of using a "weaponized AI propaganda machine" capable of "nearly impenetrable voter manipulation". New? Hardly. Simulmatics invented that in 1959. They called it the People Machine. As an American historian with an interest in politics, law and technology, I came across the story of the Simulmatics Corporation five years ago when researching an article about the polling industry 3. Polling was, and remains, in disarray. Now, it's being supplanted by data science: why bother telephoning someone to ask her opinion when you can find out by tracking her online? Wondering where this began took me to the Massachusetts Institute of Technology (MIT) A cold-war-era corporation targeted voters and presaged many of today's big-data controversies.
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