The early web was heralded as a revolution in participatory media where everyone could make media as well as consuming it.
aaaaand there’s your cover for the book on 2018’s tech backlash https://t.co/1Y7xXakJiN
(https://twitter.com/cwarzel/status/983778368083714053?s=03)
The WikiTribune community reporting on Mark Zuckerberg’s testimony before Congress. It’s also tracking the user data collected by Facebook apps. Add a screenshot and brief description if you received a message from Facebook saying your data was mined by Cambridge Analytica or other apps.
Facebook founder Mark Zuckerberg was brought to Washington D.C. on Tuesday by a scandal surrounding Cambridge Analytica, a political consultancy group that harvested data from roughly 87 million Facebook users without their knowledge. Ahead of his congressional testimony, Facebook contacted those affected by the Cambridge Analytica breach. The social media platform reportedly also posted a link on the newsfeeds of all 2.2 billion users listing the apps they use, and which data these apps were able to scrape(Guardian).
Mark Zuckerberg may have been unwilling to reveal what D.C. hotel he is staying in this week, but he surely didn’t come to his Capitol Hill interrogation Tuesday expecting to enjoy a great deal of personal privacy. Whatever he was thinking, he somehow left the notes he brought with him laying out long enough for a journalist to snap a photo for all the world to see.
Senators grilled Facebook CEO Mark Zuckerberg for five hours on Tuesday, but the big takeaway was hard to pin down.
After watching the Facebook founder and CEO’s 48-hour trip to Capitol Hill, there are two possible conclusions: either Mark Zuckerberg deliberately misled Congress, or Mark Zuckerberg knows very little about his own company. Both are bad.
Mark Zuckerberg did not go to Washington unready: He wore a suit, he brought his notes, and, it’s safe to assume, he logged hours of prep time with his much-alluded-to “team” before taking his (platform-boosted) seat on the Hill. Somewhere along the line, that preparation must have included someone taking Zuckerberg aside and advising him to address each questioner by his or her title as much as humanly possible. Zuckerberg did as he was told, uttering the words “Congressman,” Congresswoman,” and “Senator” more than any 33-year-old has ever previously spoken them in a 26-hour span. If the intent was to show respect, the effect was more strange than anything else: Zuckerberg sounded like he was overdoing it, at times coming off as not just a try-hard but pedantic too. Sometimes even the best-laid strategies can backfire; senator, it’s complicated.
In early 2016, Microsoft launched Tay, an AI chatbot that was supposed to mimic the behavior of a curious teenage girl and engage in smart discussions with Twitter users. The project would display the promises and potential of AI-powered conversational interfaces. However, in less than 24 hours, the innocent Tay became a racist, misogynist and a holocaust denying AI, debunking—once again—the myth of algorithmic neutrality. For years, we’ve thought that artificial intelligence doesn’t suffer from the prejudices and biases of its human creators because it’s driven by pure, hard, mathematical logic. However, as Tay and several other stories have shown,
President Donald J. Trump criticized Amazon for paying “little or no state & local” taxes on Thursday, the latest development in a feud that’s lived on Twitter since 2016.
Trump’s latest tweet was more specific than his previous attacks on the world’s largest retailer, and owner Jeff Bezos.
Axios reports that Trump is “obsessed” with Amazon, seeing the company as a threat to real estate and traditional retail industries.
The researcher whose work is at the center of the Facebook–Cambridge Analytica data analysis and political advertising uproar has revealed that his method worked much like the one Netflix uses to recommend movies.
In an email to me, Cambridge University scholar Aleksandr Kogan explained how his statistical model processed Facebook data for Cambridge Analytica. The accuracy he claims suggests it works about as well as established voter-targeting methods based on demographics like race, age, and gender.
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