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Facebook, YouTube Turn To Machine Learning To Control Content On Their Platform

Facebook, YouTube Turn To Machine Learning To Control Content On Their Platform

AI and Machine Learning have their own subtle differences

While Facebook is fighting a tough battle against fake news, YouTube is aggressively trying to cut down the offensive and extremist content on its platform. And maybe machine learning is the solution to the problem.

In a bid to bring it down, the social media giant will be using “updated machine learning” to detect potential hoaxes and send them to third-party fact checkers.

Facebook said in an updated blog post that it is working to expand a program to offer related articles on a trending topic that offer fact-check articles and other perspectives.

Our applied machine learning researchers and engineers develop machine learning algorithms that rank feeds, ads and search results, and create new text understanding algorithms that keep spam and misleading content at bay. New computer vision algorithms can “read” images and videos to the blind and display over 2 billion translated stories everyday, speech recognition systems automatically caption the videos that play in your news feed, and we create new magical visual experiences such as turning panorama photos into fully interactive 360 photos,” Facebook had said in its research page.

Back in April, Facebook announced it would use Related Articles as a way of to combat the influx of dubious articles. When you clicked on a post sharing an article, the Related Articles section directly below would show articles with different takes on the same topic.

“Since starting this test, we’ve heard that Related Articles helps give people more perspectives and additional information, and helps them determine whether the news they are reading is misleading or false. So we’re rolling this out more broadly,” said Sara Su, Product Manager, News Feed, Facebook.

Not just Facebook but even Google's YouTube announced earlier this month that would use machine learning to curb the number of videos from terrorist-affiliated groups on its platform.

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The Alphabet-owned video portal said it would use machine learning technology to step up its efforts to detect and remove terrorist videos while also putting into place "tougher standards" for determining when other videos are too controversial—even if they do not violate YouTube's specific community guidelines.

Both Facebook and YouTube have drawn flak for its role in perpetuating hoaxes and hosting disturbing content. And finally, it seems it’s only machines that can help in controlling content on these platforms.

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