AI Fact Checker Will Tackle Fake News, KAIST Professor Says | Be Korea-savvy

AI Fact Checker Will Tackle Fake News, KAIST Professor Says


Professor Cha Mi-young, who teaches computing at the Korea Advanced Institute of Science & Technology (KAIST), said big-data efforts to quickly discover and prevent fake news from spreading are more important than ever in the age of automated journalism. (Image: Yonhap)

Professor Cha Mi-young, who teaches computing at the Korea Advanced Institute of Science & Technology (KAIST), said big-data efforts to quickly discover and prevent fake news from spreading are more important than ever in the age of automated journalism. (Image: Yonhap)

DAEJEON, Nov. 10 (Korea Bizwire) – A KAIST professor has said artificial intelligence-based fact checkers could be more effective than humans in tackling fake news in the future.

Professor Cha Mi-young, who teaches computing at the Korea Advanced Institute of Science & Technology (KAIST), said big-data efforts to quickly discover and prevent fake news from spreading are more important than ever in the age of automated journalism.

According to a study Cha cited during a policy forum on Thursday, artificial intelligence-based fact checkers are able to identify fake news with an 80 percent accuracy rate, even better than humans.

Cha spoke during the event ‘Dinner and 4.0′, a monthly research conference for the fourth industrial revolution at KAIST where professors give presentations to researchers and students.

“Nearly half of the top 20 news articles on Facebook with the most likes during the 2016 U.S. presidential election turned out to be fake news. (Fake news) took advantage of the fact that most people just see a photo, or read a title or a lead, instead of clicking to read the full article,” Cha said.

The widely shared notion that the most-clicked articles have high-quality content on online media outlets played into the hands of fake news, according to some analysts.

According to Cha, fake news tends to attract views over a longer period of time than credible news, which is often read soon after its published.

“Fake news tends to be spread among unlikely people, as they share it among each other sporadically.”

It is thought that fake news tends to begin with sentences like, ‘I’ve heard it from somewhere,’ ‘It is not clear,’ or ‘According to someone,’ all of which avoid direct responsibility.

During the conference, predictions were made for the future of the media, with some suggesting news could be graded on a scale of one to five based on credibility.

A KAIST professor has said artificial intelligence-based fact checkers could be more effective than humans in tackling fake news in the future. (Image: Yonhap)

A KAIST professor has said artificial intelligence-based fact checkers could be more effective than humans in tackling fake news in the future. (Image: Yonhap)

“People might want real news, but also other types of news at the lower end of the credibility scale for entertainment purposes,” Cha said while laughing.

“In a new era for the media where decisions are made automatically, such as robot journalism, big data research to swiftly identify fake news and stop it from spreading is becoming increasingly necessary,” Cha added.

Hyunsu Yim (hyunsu@koreabizwire.com)

 

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