Delip Rao, one of its organizers and the founder of Joostware, a company that creates machine-learning systems, said spotting fake news has so many facets that the challenge is actually going to be done in multiple steps. The first step is “stance detection,” or taking one story and figuring out what other news sites have to say about the topic. This would allow human fact checkers to rely on stories to validate other stories, and spend less time checking individual pieces.

The Fake News Challenge released data sets for teams to use, with 50 teams submitting entries. Talos Intelligence, a cybersecurity division of Cisco, won the challenge with an algorithm that got more than 80 percent correct—not quite ready for prime time, but still an encouraging result. The next challenge might take on images with overlay text (think memes, but with fake news), a format that is often promoted on social media, since its format is harder for algorithms to break down and understand.

“We want to basically build the best tools for the fact checkers so they can work very quickly,” Rao said. “Like fact checkers on steroids.”

Even if a system is developed that is effective in beating back the tide of fake content, though, it’s unlikely to be the end of the story. Artificial-intelligence systems are already able to create fake text, as well as incredibly convincing images and video. (see “Real or Fake? AI Is Making It Very Hard to Know”). Perhaps because of this, a recent Gartner study predicted that by 2022, the majority of people in advanced economies will see more false than true information. The same report found that even before that happens, faked content will outpace AI’s ability to detect it, changing how we trust digital information.

What AdVerif.ai and others represent, then, looks less like the final word in the war on fake content than the opening round of an arms race, in which fake content creators get their own AI that can outmaneuver the “good” AIs (see “AI Could Set Us Back 100 Years When It Comes to How We Consume News”). As a society, we may yet have to reevaluate how we get our information.