In 2014, the term “fake news” hadn’t yet become part of the American lexicon and the 2016 U.S. presidential race was only beginning to make headlines. But in California, a man named Jestin Coler was hard at work creating one of the most divisive media trends in modern history.
Dubbed the godfather of the fake news industry, Coler’s efforts began with publishing fabricated stories — including an article about Colorado food stamp recipients using welfare benefits to buy marijuana — that garnered enough traffic to generate tens of thousands of dollars a month in ad revenue. The idea quickly caught on. Competing sites sprang up around the world as other publishers raced to create fake news masterpieces of outrageous, conspiratorial, and highly partisan news ahead of the election.
Since then, the fake news phenomenon has created the means for people (including public leaders) to dismiss reports of their wrongdoings and infuse otherwise legitimate political debates with falsehoods. Even amateur web users can doctor images and videos to create evidence of events that never happened.
There’s no easy answer to the problem. But artificial intelligence can help.
Sixty-two percent of Americans look to social media for information on what’s happening in the world. How we engage with the articles and videos we find on these platforms influences which stories and posts we’ll see in the future. If we like, comment on, or share more conservative news items than we do liberal ones, for instance, social algorithms will show us similar content the next time we sign on. Our online contacts also factor into this equation. Having a disproportionate number of liberal-leaning friends or followers skews our feeds as well.
Blatantly false news isn’t the only thing that should concern us. Headlines and stories that frame accurate information in misleading ways also distort our perceptions. As Kim LaCaria, content manager for Snopes, told Quartz: “There’s information and then there’s how it’s presented, and those two aren’t always the same.”
Colombia Journalism Review has advised journalists to look at creation dates and source materials to verify videos, along with clues from content creators’ online backgrounds. Video analysis programs and other verification tools also help. Nearly 60 percent of people repost articles without reading past the headline, so the odds of readers vetting every article seem slim. Even if we all had sufficient time and inclination to become digital detectives, the sheer amount of online content means that making a dent is unfeasible. Millions of online interactions occur each minute, and no human can keep up with them all. An artificial intelligence system, on the other hand, might be able to help stem the fake news tide.
An AI system trained to analyze text, videos, images, and audio could work around the clock at rates that far exceed even the most efficient human. Computer science researchers at one university are developing a machine-learning approach to fake news detection. The program will analyze the content of an article and then score it based on how likely it is to be fake news. It can also generate a breakdown of why the score was assigned so readers can understand why the AI system flagged something as fake news.
