A professor at the University of California has developed an algorithm to detect fake news with 75% accuracy. In our present time, when fake news is now expertly integrating itself into the public news stream, detecting its authenticity with AI will add to how media outlets can regulate content.
Vagelis Papalexakis is a professor of computer science at the University of California, Riverside who developed the algorithm. “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.
The professor expects his algorithm to expand to videos and images soon, as now it is just limited to text content. Papalexakis hails from Greece, and he said the Greek bailout referendum of 2015 is what inspired him to work on catching fake news.
“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.
Even though there are many fake news checkers, most of them rely heavily on human help. A turn to technology would be a very significant step in this regard.
However, the professor said the policy and education should help in regulating fake news in the long term.
You can listen to the complete conversation with Vagelis Papalexakis on the AI Podcast.
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