2 college students built a tool to fight fake news on Facebook using artificial intelligence

2 college students built a tool to fight fake news on Facebook using artificial intelligence

  • In late April, the two computer science majors built a Facebook Messenger bot that, when fed a link, will tell you whether the article in question is or isn’t “fake news.”
  • Bhat, who has built civic tech tools before in his spare time, thought that perhaps they could use machine learning to build a bot that would help put articles people find on Facebook in context.
  • To teach the algorithm to recognize right-leaning content they fed it thousands of articles from Breitbart, a hyperconservative news website.
  • NewsBot has also begun offering short news summaries of top articles.
  • Right now you can mark an article as fake news from a small drop down at the top, but if you’re a user just scrolling, the feed hasn’t really changed in any way.

This could change how you read the news.
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WHEN COMPUTERS LEARN TO SWEAR: – Jigsaw – Medium

Introducing Perspective, using machine learning to improve discussions online.

  • We think technology can help.Today, Google and Jigsaw are launching Perspective, an early-stage technology that uses machine learning to help identify toxic comments.
  • Through an API, publishers — including members of the Digital News Initiative — and platforms can access this technology and use it for their sites.HOW IT WORKSPerspective reviews comments and scores them based on how similar they are to comments people said were “toxic” or likely to make someone leave a conversation.
  • Each time Perspective finds new examples of potentially toxic comments, or is provided with corrections from users, it can get better at scoring future comments.Publishers can choose what they want to do with the information they get from Perspective.
  • Publishers could even just allow readers to sort comments by toxicity themselves, making it easier to find great discussions hidden under toxic ones.We’ve been testing a version of this technology with The New York Times, where an entire team sifts through and moderates each comment before it’s posted — reviewing up to 11,000 comments every day.
  • We’ve worked together to train models that allows Times moderators to sort through comments more quickly, and we’ll work with them to enable comments on more articles every day.WHERE WE GO FROM HEREPerspective joins the TensorFlow library and the Cloud Machine Learning Platform as one of many new machine learning resources Google has made available to developers.

Imagine trying to have a conversation with your friends about the news you read this morning, but every time you said something, someone shouted in your face, called you a nasty name or accused you…
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When computers learn to swear: Using machine learning for better online conversations

Neat, Google trained a computer to understand whether a comment is toxic or not

  • Unfortunately, this happens all too frequently online as people try to discuss ideas on their favorite news sites but instead get bombarded with toxic comments.
  • According to the same report, online harassment has affected the lives of roughly 140 million people in the U.S., and many more elsewhere.
  • News organizations want to encourage engagement and discussion around their content, but find that sorting through millions of comments to find those that are trolling or abusive takes a lot of money, labor, and time.
  • As a result, many sites have shut down comments altogether.
  • Through an API, publishers—including members of the Digital News Initiative—and platforms can access this technology and use it for their sites.

Google and Jigsaw announce the launch of Perspective, an early-stage technology that uses machine learning to identify toxic comments.
Continue reading “When computers learn to swear: Using machine learning for better online conversations”