Bringing a Critical AI to News: Extracting Insight from Coverage

by Brian Caulfield

In 2015, Sean Gourley penned an article called “Robot Propaganda” for Wired magazine.

It contained this then-bold prediction: “We are likely to see versions of these bots deployed on U.S. audiences as part of the 2016 presidential election campaigns.”

Well, we all know how that turned out.

Gourley recently joined the AI Podcast to talk about bots, propaganda and fake news and how they relate to the work his own company is doing in natural language understanding and generation.

Gourley — who holds a Ph.D. in physics from Oxford University — is founder and CEO of Primer, a San Francisco-based machine intelligence company.

It builds machines that can read and write, automating the analysis of very large datasets.

In short, it automates the job of wringing insights out of news and other sources of information.

As a result, it grapples with the problems created by “fake news” and propaganda in a very real way for customers that include government agencies, financial institutions and Fortune 500 companies.

“The big thing for us is building systems that can help us understand the world that we’re living in,” Gourley said.

The best way to do that: track current events, and the events detailed by reputable sources closely.

“That’s become a really important piece in starting to kind of navigate a world where there’s an increasing volume of fake information and increasingly sophisticated fake information that’s out there.”

For more from Gourley, tune into the AI Podcast.

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