Machine Learning Project Takes Aim at Disinformation

There’s nothing new about conspiracy theories, disinformation, and untruths in politics. What is new is how quickly malicious actors can spread disinformation when the world is tightly connected across social networks and internet news sites. We can give up on the problem and rely on the platforms themselves to fact-check stories or posts and screen out disinformation—or we can build new tools to help people identify disinformation as soon as it crosses their screens. Preslav Nakov is a computer scientist at the Qatar Computing Research Institute in Doha specializing in speech and language processing. He leads a project using machine learning to assess the reliability of media sources. That allows his team to gather news articles alongside signals about their trustworthiness and political biases, all in a Google News-like format. “You cannot possibly fact-check every single claim in the world,” Nakov explains. Instead, focus on the source. “I like to say that you can fact-check the fake news before it was even written.” His team’s tool, called the Tanbih News Aggregator, is available in Arabic and English and gathers articles in areas such as business, politics, sports, science and technology, and covid-19. Business Lab is hosted by Laurel Ruma, editorial director of Insights, the custom publishing division of MIT Technology Review. The show is a production of MIT Technology Review, with production help from Collective Next. This podcast was produced in partnership with the Qatar Foundation. Show notes and links Tanbih News Aggregator Qatar Computing Research Institute “Even the best AI for spotting fake news is still terrible,” MIT Technology Review, October 3, 2018