Google Is Making It Easier For AI Developers To Keep Users’ Data Private

Google has announced a new module for its machine learning framework, TensorFlow, that lets developers improve the privacy of their AI models with just a few lines of extra code.

TensorFlow is one of the most popular tools for building machine learning applications, and it’s used by developers around the world to create programs like text, audio, and image recognition algorithms. With the introduction of TensorFlow Privacy, these developers will be able to safeguard users’ data with a statistical technique known as “differential privacy.”

PRIVACY IS IMPORTANT WHEN AI TOOLS VACUUM UP DATA

Introducing this tool is in keeping with Google’s principles for responsible AI development, Google product manager Carey Radebaugh tells The Verge. “If we don’t get something like differential privacy into TensorFlow, then we just know it won’t be as easy for teams inside and outside of Google to make use of it,” says Radebaugh. “So for us it’s important to get it into TensorFlow, to open source it, and to start to create this community around it. READ MORE ON: THE VERGE

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DataYusra Hamid