Good News About Fake News: AI Learning to Detect It

by Allison Toh

There’s nothing fake about this news.

With “fake news” embedding itself into, well, our news, it’s become more important than ever to distinguish between content that is fake or authentic.

That’s why Vagelis Papalexakis, a professor of computer science at the University of California, Riverside, developed an algorithm that, so far, detects fake news with 75 percent accuracy.

“I want [the algorithm] to be a tool that helps educate folks about what it is they’re about to read,” said Papalexakis in a conversation with AI Podcast host Noah Kravitz.

While the algorithm is starting with text, Papalexakis hopes to expand to videos and images.


Since fake news is a “big umbrella term,” as Papalexakis calls it, his team didn’t come up with their own definition of fake for the algorithm.

Instead they rely on “well-known definitions that people use and have been using in the past.” Such solutions include a crowd-sourced tool called B.S. Detector.

Greeking Out

The Greek bailout referendum of 2015 inspired Papalexakis, who is from Greece, to start working on a fake news detector.

“I sort of observed [the referendum] from a distance because I was in California, and I was not sure what was going on on either side. And so I wasn’t able to trust anything that I read from either side because there was so much conflicting information that I just gave up,” said Papalexakis.

“About a year ago, we decided to try to help from a technological point of view and at least try to provide citizens with tools so that they can help then decide about what they’re reading,” he said.

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With his research, Papalexakis dove into why and how people fall for fake news.

“I really hope that [this research] can actually have a tangible impact, especially if you try to turn this into guidelines and sort of education that starts from a young age,” said Papalexakis.

But Papalexakis cautions the solution to fake news won’t just come from technology, but also from policy and education.

“There needs to be a holistic approach to this,” Papalexakis said. “We’re merely a part of the puzzle.”

Listen to the complete discussion on the AI Podcast.

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