From hidden connections in big data to bots spreading fake news, journalism is increasingly computer-generated. An expert in computer science and media explains the present and future of a world in which news is created by algorithm.

Amid the push for self-driving cars and the roboticization of industrial economies, automation has proven one of the biggest news stories of our time. Yet the wide-scale automation of the news itself has largely escaped attention. In this lively exposé of that rapidly shifting terrain, Nicholas Diakopoulos focuses on the people who tell the stories―increasingly with the help of computer algorithms that are fundamentally changing the creation, dissemination, and reception of the news.

Diakopoulos reveals how machine learning and data mining have transformed investigative journalism. Newsbots converse with social media audiences, distributing stories and receiving feedback. Online media has become a platform for A/B testing of content, helping journalists to better understand what moves audiences. Algorithms can even draft certain kinds of stories. These techniques enable media organizations to take advantage of experiments and economies of scale, enhancing the sustainability of the fourth estate. But they also place pressure on editorial decision-making, because they allow journalists to produce more stories, sometimes better ones, but rarely both.

Automating the News responds to hype and fears surrounding journalistic algorithms by exploring the human influence embedded in automation. Though the effects of automation are deep, Diakopoulos shows that journalists are at little risk of being displaced. With algorithms at their fingertips, they may work differently and tell different stories than they otherwise would, but their values remain the driving force behind the news. The human–algorithm hybrid thus emerges as the latest embodiment of an age-old tension between commercial imperatives and journalistic principles.

About the Author:

Nicholas Diakopoulos is an expert on computational and data journalism whose work has been featured on BBC Radio 4 and CBC Radio and in The Atlantic, Slate, Wall Street Journal, Washington Post, and Boston Globe. He is Director of the Computational Journalism Lab (CJL) and an Assistant Professor in the School of Communication at Northwestern University, and is a Tow Fellow at Columbia University School of Journalism. A consultant specializing in research, design, and development for computational media applications, he cofounded Georgia Tech’s program in Computational Journalism.

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