Contrary to popular belief, the steadfast march toward automation is affecting all sorts of fields — not just blue-collar industries like manufacturing and transportation. Already, artificially intelligent systems (AI) are reviewing contracts and mining documents in discovery, determining which job candidates get callbacks, and selecting the inventory retailers choose to highlight for particular customers.
Now, at least one publication is using it to help supply generate “thought starters” that might later become published articles.
According to a report in Digiday this morning, Forbes’ product team recently began internally testing an AI tool that supplies story threads. It builds on the publisher’s semi-automated topics recommendation feature in Bertie, its content management system (CMS), that produces writing prompts based on reporters’ previous work.
The CMS sources both Forbes and competitors for links to contextually relevant articles about topics, along with images that might improve the story. In that respect, it’s not unlike Reuters’ Lynx Insights, which launched in March. Like Bertie, Lynx Insights surfaces key data related to stories — helping reporters to, for example, quickly analyze historical trends in commodities pricing.
The topics suggestion feature, which Forbes has been piloting, is expected to become available to all Forbes contributors in North America and Europe in the first quarter of this year. The AI story-writing tool does not have a firm rollout date, however.
It reflects something of a trend. As Digiday notes, Forbes and Reuters aren’t the only news organizations experimenting with AI that promises to automate the publishing process.
The Washington Post‘s in-house Heliograf tech, which generates short stories on a range of topics, like the Olympics, congressional and gubernatorial races, and high school football games, spit out 850 articles in 2017, a number that grew to “thousands” in 2018. The Associated Press, meanwhile, in partnership with startup Automated Insights, deployed an AI writer in 2015 that’s able to generate roughly 2,000 articles a second with fewer errors than their human-produced equivalents.
Despite appearances, AI-assisted reporting tools aren’t necessarily a harbinger of machine-driven newsrooms, contends Jeremy Gilbert, director of strategic initiatives at the Washington Post. In an interview with Digiday, he says that platforms such as Heliograf can spot unexpected trends in news events or undertake some of the time-consuming legwork currently performed by human reporters.
In 2014, for example, the Los Angeles Times used a machine learning algorithm to comb through eight years’ worth of public records — findings that contributed to a report on the Los Angeles Police Department’s history of misclassifying violent crimes.
“We think we can help people find interesting stories,” he said.
That jibes with the AP’s strategy. It estimates that its automation tools have freed up 20 percent of reporters’ time spent covering corporate earnings alone.
“One of the things we really wanted reporters to be able to do was when earnings came out to not have to focus on the initial numbers,” Philana Patterson, an assistant business editor at the AP, told the Verge in an interview. “That’s the goal, to write smarter pieces and more interesting stories.”
Indeed, the Tow Center predicted in a 2016 report that automated journalism “will likely replace journalists who merely cover routine topics.” And in a survey published by Tata Communications in September, Ken Goldberg, a leading AI researcher and UC Berkeley professor, said he expects that AI’s continued advances into workplaces (including newsrooms) won’t come at the expense of jobs, but will rather “create new ways of working” and “new jobs” in companies.
“Robots and AI are not going to take away this creative, insightful, empathetic aspect of almost every job,” Goldberg said.
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