When I ask Mark Zuckerberg if the presidential election changed the way he sees Facebook—if he made poor assumptions, if Facebook functioned in ways he didn’t intend—he pauses. I’ve interviewed Zuckerberg before, and he tends to pause like this, gathering his thoughts in complete silence, sometimes turning to face the empty space across the room. But this dead air lasts particularly long. Five seconds. Six. Seven. Eight. Nine. Ten.

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About a decade ago, a handful of Google’s most talented engineers started building a system that seems to defy logic. Called Spanner, it was the first global database, a way of storing information across millions of machines in dozens of data centers spanning multiple continents, and it now underpins everything from Gmail to AdWords, the company’s primary moneymaker. But it’s not just the size of this creation that boggles the mind.

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This story is part of our special coverage, The News in Crisis. When Edward Snowden leaked the biggest collection of classified National Security Agency documents in history, he wasn’t just revealing the inner workings of a global surveil­lance machine. He was also scrambling to evade it.

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Even before an electrical fire burned her house down in 2014, Jennifer Sneperger had trouble affording home internet. A little more than a year after the fire, she and her young son joined a program that fast-tracked them into a spot in a Sarasota, Florida, public housing complex. But the spot came with a condition: Sneperger had to get a job or go back to school.

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Working on a new product launch? Debuting a new mobile site? Announcing a new feature? If you’re not sure whether algorithmic bias could derail your plan, you should be. Algorithmic bias—when seemingly innocuous programming takes on the prejudices either of its creators or the data it is fed—causes everything from warped Google searches to barring qualified women from medical school.

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In February 1975, a group of geneticists gathered in a tiny town on the central coast of California to decide if their work would bring about the end of the world. These researchers were just beginning to explore the science of genetic engineering, manipulating DNA to create organisms that didn’t exist in nature, and they were unsure how these techniques would affect the health of the planet and its people.

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Last month, in response to news of President Donald Trump’s controversial executive orders, Apple CEO Tim Cook stated that his company, whose founder Steve Jobs was the son of a Syrian immigrant, would not exist if the US didn’t have sound immigration policies.

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Snap Inc. is a camera company. It's very important to Snap Inc. that you understand it's not a social networking app or a messaging service. It's something else. It's a camera company. "We believe that reinventing the camera represents our greatest opportunity to improve the way that people live and communicate," it says in an S1 filing made public today, ahead of its $3 billion public offering.

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To adapt one of our new president’s favorite aphorisms: We knew he was a troll when we elected him. Throughout the campaign, Donald Trump gleefully behaved more like a social-network scourge than a presidential candidate, combining a slash-and-burn approach to social norms with an aggressive strategy of constant provocation. So it’s perhaps not surprising that, in the not-quite-two-weeks since his inauguration, internet companies have struggled to respond to his presidency.

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Neural networks are all the rage in Silicon Valley, infusing so many internet services with so many forms of artificial intelligence. But as good as they may be at recognizing cats in your online photos, AI researchers know that neural networks are still quite flawed, so much so that some wonder whether these pattern recognition systems are a viable path to more advanced—and more reliable—forms of AI.

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