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AI Could Help Reporters Dig Into Grassroots Issues Once More

Twitter’s media science chief says machine learning will help journalists understand a world fragmented by digital technologies and political polarization.
November 9, 2017
Justin Saglio

Last year’s divisive American presidential race highlighted the extent to which mainstream media outlets were out of touch with the political pulse of the country. Deb Roy, the director of the Laboratory for Social Machines at the MIT Media Lab, says part of the problem is that many local news operations are being closed or hollowed out because of economic pressures, depriving national newsrooms of valuable grassroots insights.

Speaking on Wednesday—which, coincidentally, marked the first anniversary of Donald Trump’s election—Roy told the audience at MIT Technology Review’s annual EmTech MIT conference that it’s vital to develop new ways of gauging the health of political discourse. The current prognosis for America isn’t encouraging. “The patient is sick, and the level of hostility [to opposing ideas] is real”, said Roy, who is also chief media scientist at Twitter.

Through work on its Electome project, which applies big-data analytics to social media, Roy’s team at MIT has demonstrated the increasing prevalence of online social-media “cocoons,” which isolate people from opposing views. Throw in the phenomenon of fake news (which is set to become even more of a challenge), and it all adds up to a hot-button issue that has triggered a backlash against big social-media companies.

Roy said that Internet giants are responding, but they can’t tackle this complex issue by themselves. “It’s a systemic set of dynamics, and no one company on its own can hit the undo button,” he explained.

What’s needed, he says, is an approach to bridging political and societal divisions. He sees Cortico, a nonprofit he’s launched in collaboration with the Media Lab, as part of that effort. It plans to give existing newsrooms and local news entrepreneurs access to top-class machine learning, natural-language processing, and other tools. Reporters can use them to mine multiple data sources, identify grassroots concerns, and then develop stories that emphasize common ground between citizens with differing political views.

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