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The cybernetic newsroom: Expanding boundaries and expectations

Combining human intelligence and judgment with technological capabilities could safeguard newsgathering organizations to changes in the media industry.

Nov 30, 2017

Over the past decade, the landscape of news and information has shifted dramatically. Journalists now routinely mine huge data sets to uncover hard-to-find stories. Automations fire off news headlines at sub-second speeds. Platforms like Facebook and Twitter dominate the distribution of news.

At Reuters, we filter through the noise and track all of these changes closely. One of the ways we do this is by adapting new tools.

The Reuters News Tracer, is a technology developed by the Thomson Reuters Research and Development team which helps us find news faster.

The Reuters News Tracer algorithmically detects newsworthy events breaking on Twitter. The tracer then rates the likelihood that they’re true so that reporters can get a head start on confirming the news.

Reg Chua, executive editor for Editorial Operations, Data and Innovation at Reuters describes the future of newsrooms as “cybernetic”. A newsroom that marries the strength of human intelligence and judgement with the help of technology.

Speaking about how newsrooms can benefit from emerging technologies, Chua observes that, “It goes far beyond just using technology to help us do what we do more effectively. It’s using technology to rethink what we do and how we do it”.

For example, language generation systems technologies that can understand documents, analyze data and create text have been largely focused on creating short stories at lightning speed, or on turning out vast numbers of relatively simple, routine stories. But machines are capable of much more, especially trawling through huge amounts of data and surfacing interesting patterns and outliers.

Knowing if some trend or change is significant is something that humans (still) do better than machines. So, why not marry the two capabilities – machine analysis and human judgment – into a single system and take advantage of the strengths of both parties? ”

— says Chua.

Human judgement also plays a vital role.

“Knowing if some trend or change is significant is something that humans (still) do better than machines. So, why not marry the two capabilities – machine analysis and human judgment – into a single system and take advantage of the strengths of both parties?,” says Chua.

Reuters are investing this approach – using technology to crawl through multiple proprietary databases, unearth insights, turn them into sentences and paragraphs, and then offer them to journalists, who can use them as tips, integrate them into stories, or simply discard them.

The technologies are very nearly here already, and newsrooms are starting to embrace the possibilities. But there’s probably even more that we haven’t imagined yet, and that we’re just at the start of a brave new era of news and information.

 

A version of this article was originally published on the Thomson Reuters blog.