If you have used the internet, you will know that finding a courtesy conversation is a real challenge. Whether you're on Youtube, Facebook, Twitte or your favorite news site, many rogue characters can dominate and disrupt conversations. Today, Alphabet company Jigsaw announced that it is using machine learning to solve this problem. Today released PerspecTIve is an "early" technology for machine learning that recognizes "toxic" comments on the web. In addition, the media can add this technology to their website through an open API interface, which will enable them to have a better conversation.
In order to train PerspecTIve through machine learning, Jigsaw has collected thousands of comments that are considered harmful by critics. The machine learning software then looks at other comments and scores based on similarities. Like all machine learning systems, PerspecTIve becomes smarter and more accurate each time it discovers new harmful comments, or when we guide and correct what is wrong with its recognition.
Jigsaw not only tested and trained PerspecTIve in its own company's lab, the company said it has worked with the New York Times to test it. Currently, the New York Times has some dedicated administrators who will review each comment before posting; the team will check out about 11,000 comments per day. But this kind of manual review means that the media only commented on about 10% of the stories. Working with Jigsaw's Perspective, the New York Times' review team can post comments faster and open up comments on more articles.
Perspective is not the only tool of Jigsaw, and there are many products in Jigsaw that can regulate the Internet order. Last year, the company allowed any news organization to sign up for Project Shield, a tool to defend against attacks. While these tools are useful, Perspective may affect how people browse publications and news sites every day. I hope that the New York Times and Jigsaw can share some data to reveal how Perspective has an impact on website reviews.
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